Regression Analysis Essays Examples

Regression Analysis Is the Technique

Its name tells us the criterion used to select the best fitting line, namely that the sum of the squares of the residuals should be least. In other words, the least squares regression equation is the line for which the sum of squared residuals is a minimum (Dallal, 2008).

Multiple regression - the general purpose of multiple is to learn more about the relationship between several independent variables and a dependent variable. For example, a real estate agent might record for each listing the size of the house in square feet, the number of bedrooms, the average income in the respective neighborhood, and a subjective rating of appeal of the house. As soon as this information is compiled for different houses it would be exciting to see whether these measures relate to the price for which a house is sold.

One good example for a simple linear regression analysis can be found in the financial industry, specifically in the stock market. Let's assume that a stock broker would like to estimate the tradeoff between risk and returns he/she would use linear regression to estimate the returns compared to the risk. If the risk increases the return will increase and vice…… [Read More]

Regression Analysis and Business Rules of Thumb

Regression Analysis and Business

Rules of thumb, instinct, convention, and simple financial analysis are frequently no longer adequate for addressing such common decisions found in business such as make-versus-buy, facility site selection, and process redesign. Generally, the forces of competition are commanding a need for more efficient decision making at all levels in companies. "Decision analysts provide quantitative support for the decision-makers in all areas including engineers, analysts in planning offices and public agencies, project management consultants, manufacturing process planners, financial and economic analysts and experts supporting medical and technological diagnosis"(Tools for Decision Analysis: Analysis of Risky Decisions, 2012).

Modeling for decision making comprises two distinct entities, one is the decision-maker and the other is the model-builder who is known as the analyst. The function of the analyst is to help the decision-maker in their decision-making process. Consequently, the analyst must be outfitted with more than a set of analytical methods. Specialists in model building are frequently lured to study a problem, and then go off by themselves to develop a complex mathematical model for use by the manager. Unfortunately the manager may not comprehend this model and may either use it blindly or decline it all together. The specialist…… [Read More]

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Regression Analysis on Retirement

Regression Analysis on Retirement

Definition of Regression

Regression can be defined as a multipurpose and dominant arithmetical technique which is utilized to concurrently form the outcomes of numerous independent variables on one single dependent variable (for example, Cohen & Cohen, 1983; Fox, 1997; Pedhazur, 1997). The instantaneous assessment of independent variables is what makes it feasible or easier to better comprehend, calculate, and clarify a dependent variable; to guess their independent and collective effects; to discard unauthentic effects; to resolve more precisely the course and force of their outcomes; and to manage the likelihood of Type I errors.

Over the years, there have been many analysis made and researches done on the relationship of retirement and the incentives given i.e. pensions and social security provided. Most of these researches have been done in the perspective of a single-equation, reduced-form model, which are most commonly and regularly utilized in behavioral and policy studies. A good example to explain this would be that the Social Security Administration has signed up a deal to use this type of a model in order to foresee the results of an alteration in the existing policy, to be exact, raising the age of entitlement for the…… [Read More]

Regression Analysis of Auto Sales

Table 3: Predicting Elasticities of Variables

From the analysis completed in Table 3, the elasticity of each variable can be easily seen. As one would expect, the greater the variability in a given variable the higher the elasticity, especially when the variables either measure purchasing power as pi does directly or how the variables stock, and index of consumer sentiment also are shown as a result of their large variances. Taking a step back from the statistical analysis and thinking logically about this, elasticity would be defined by the level of car stocks or inventories on hand, customer attitudes and behaviors and the amount of money they had to spend. These three variables delivered a 75% R2 correlation coefficient. Elasticity is a function of price and demand so these series of relationships make sense.

Forecasting

The first step in completing a forecast is to define the confidence intervals. Both 90% and 95% confidence intervals are typically chosen, for purposes of this exercise the latter figure, 95% has been selected. A 95% confidence interval ensures statistically significant results and a higher level of reliability when applying the results. Presented below are the results of a one-tailed Z-Test and t-test for confidence…… [Read More]

Multiple Regression Analysis Data Set

In this study, these variables are considered protective factors. In the third step, childhood SES would be entered. On the fourth step, childhood maltreatment would be entered. The results of the analysis would determine to what extent each of these additional steps adds to the ability to explain the variance in resilience scores. While all of these variables may ultimately be correlated with resilience, either positively or negatively, not all of these variables will continue to "add" something to our ability to predict resilience after the contribution of other variables have been allowed for first.

Below is a screen shot of the "Variable View" in SPSS of how the variables would be entered into SPSS in order to be able to conduct a Multiple Regression Analysis.

Below is a screen shot of the SPSS Data view of the data entered into SPSS for each variable. Gender, Race, Recruitment, Mentor and Family Mentor are all categorical variables, while the remaining variables are interval, or scale variables. Each line in this screen shot represents an individual participant.

After using this sample data set to run a regression analysis, the output is as…… [Read More]

Multiple Regression Analysis Is an

It includes a way to track bidirectional changes focused on the individual who operates within the two cultural environments. Methods of data reduction have been incorporated in order to develop a psychometrically strong tool. Indexes to validate the results are included in the process as well. As a part of the BAS, scales are used to measure the various areas of acculturation rather than examining items based on the cultural dimension. The working of the scale requires using a wide range of behaviors to be used in the study and generating items in order to display the Hispanic and non-Hispanic domain under consideration. A study conducted in San Francisco, California, using this approach presented different results. Multiple subscales were used along with the regular scales. Alpha coefficients were calculated for the different subscale. All of them were pretty consistent. Validation was performed by measuring them against standards established by researchers in the past, who worked on other acculturation scales. This form of validation utilizes factors such as current status, length or duration, age of the individual and relation with previous acculturation measures. (Marin and Gamba, 1996)

References

Marshall, M.(1996) Sampling for quantitative research Family Practice 13(6), 522-525

Mason, C. And…… [Read More]

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Analyzing the Workplace Regression Analysis

Workplace Regression Analysis

Give an example from your workplace regarding how regression analysis could be used by your leadership to analyze one or multiple outcomes that occur because of what your agency does. Indicate the dependent variable and at least two independent variables

To begin with, regression analysis is defined as the relationship between variables. referring to the example under consideration, the management in the workplace can use regression analysis to analyze the relationship of the tips received in the various servings compared to the corresponding amount of the bill. The dependent variable is the focus of the analysis. On the other hand, the independent variable is the 'variable that influences value of the dependent variables'. In particular, the management can use regression analysis to evaluate the impact of pricing on the behavior (tips offered) of consumers. For example, the management of the workplace can consider altering the prices on a number of products offered on different occasions. In this case, the data from the quantity sold and tips received for every price level can be employed to undertake a regression analysis. The dependent variable will be the quantity of the product sold. The independent variables will include the price…… [Read More]

Regression Analysis Real Estatee Sales Prices and

Regression Analysis: Real Estatee Sales Prices and Distance to City

This regression analysis seeks to answer the question of how the sales price of Real Estate listed houses changes with the distance from the city. Does the sales price increase or decrease as the distance from the city increases or is there a relationship between the variables at all? Given the attraction of city living and the general trends of suburban house prices, it appears reasonable to hypothesize that the sales price of the houses will decrease as the location of the house moves further away from the city.

Raw Data from Real Estate Listings:

Key: Distance is measured in miles and Sales Price in thousands of dollars.

The regression line, which best illustrates the relationship between the two variables of the data set, takes the equation ? = b + ax. This equation is based on the least squares formula ? (Y -- ?)2, which calculates the minimal possible error of the total data points from a common line. In other words, the regression line produces the most accurate representation of the total data set by minimizing the sum total distance of each data point from the given line.…… [Read More]

Regression Analysis the Methodology for

It has even moved into the legal and political realms, which focus on its ability to forecast information based on similar or manipulated environmental conditions (Sykes, 2012). It is often used in quantitative research methodologies, but also conserve as a way to test for reliability in mixed methods and qualitative studies using triangulation, or more than one method to prove the same results hold true (Dizikes, 2010). In this, the research suggests that "the investigator assembles data on the underlying variables of interest and employees regression to estimate the quantitative effect of the casual variables upon the variable that they influence" (Sykes, 2012). The type of regression used in any particular situation depends on the number of variables. Simple linear regression focuses on one dependent and one independent variable. From there, more complicated forms of aggression include a greater number of independent variables, like that of multiple regression, which is a more complicated process using more than one independent variable (Sykes, 2012).

The assumptions involved are quite complex but can be easily used and evaluated for those who are trained to understand its results. Regression analysis helps uncover the "average casual effect" the independent variables have on the dependent upon…… [Read More]

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Regression for HR a Look

In short, it's the veteran employees, who seem to not be using their vacation time, that are creating the perceived problem.

By taking a regression that analyzes length of tenure vs. vacation time taken in the most recently completed calendar year (2005), we can see if employees are taking more time off as they accrue more vacation days. Our hypothesis is that they are not and that there will be no correlation between length of tenure and time off taken.

The main statistic we will analyze is the coefficient of determination. According to Aczel and Sounderpandian, the coefficient of determination measures the strength of the regression relationship on a scale of zero to 1; the closer the figure is to 1, the stronger the relationship (p.457). As Aczel and Sounderpandian indicate, it is difficult to state definitively how close to 1 our coefficient of determination must be before we declare a strong relationship, but we will use their general rule that a value higher than 0.9 is considered very good; more than 0.8 is good; and more than 0.7 is satisfactory (p.459).

Results

The regression results clearly demonstrate that there is very little correlation between the amount of time an…… [Read More]

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Analysis of Survey on Job Satisfaction

Job Satisfaction

The main objective of this research is to examine the various factors affecting job satisfaction given that satisfaction is a dynamic phenomenon that includes a person's attitudes and behaviors. The author also seeks to examine organizational injustices and how they affect job satisfaction and organizational commitment. Organizations in the modern business environment consider job satisfaction as a legitimate factor that has strong impacts on organizational commitment. In light of this significance, it's important for organizations to evaluate and identify factors that affect job satisfaction. Therefore, this research primarily seeks to study the various factors affecting job satisfaction.

Data Analysis Methodology

To achieve the aims of this study, the researcher conducted 26 surveys on 26 different employees to determine issues that are affecting the job satisfaction in their different working environments. The researcher developed surveys with open ended questions that act as a framework of understanding what employees want from their managers. Notably, the surveys were not carried out on any specific organization but on a group of participants who provided their personal experience on job satisfaction. The research participants were selected randomly though they were required to meet certain criteria to be included in the study. The use…… [Read More]

Analysis of Null Hypothesis Significance Testing

Nhst

Compare and Contrast Null Hypothesis Significance Testing (NHST)

The most commonly used statistical technique for testing the impact of the factor being discussed on observations is Null Hypothesis Significance Testing (NHST). Consequently, NHST is the famous approach to inferential statistics, especially when conducting quantitative research. Despite being the dominant approach, NHST has also become increasingly controversial given the belief by a considerable number of people that it is a flawed statistical method. The controversy and consideration of Null Hypothesis Significance Testing as a flawed statistical approach has contributed to the development of alternatives whose proponents consider more beneficial or advantageous unlike NHST. However, an understanding of Null Hypothesis Significance Testing requires correct interpretation of p values.

Meaning of p = .05

P value is commonly used across statistical approaches including regression analysis and t-tests because it determines the statistical importance or significance in testing a hypothesis. According to Frost (2014), p values are usually used to determine the statistics to be published as well as projects that require funding. Regardless of its importance in determining the statistical significance in a hypothesis test, p value is usually a slippery concept that is incorrectly interpreted and understood. An example of incorrect…… [Read More]

Effect of IQ on GPA Regression and Correlation

Regression, Correlation: Effect of IQ on GPA

Effective teaching begins with understanding the thinking and reasoning abilities of one's students and devising ways to ensure that the classroom setting is accommodative of the inherent differences in cognitive capabilities and that all students get to benefit from the learning process. One way of measuring a child's intellectual ability is by administering the Wechsler Intelligence Scale for Children -- Forth Edition (WISC-IV), which measures IQ on the basis of a child's processing speed, working memory, perceptual reasoning, and verbal comprehension skills. Children below the average range in IQ are thought to have lower understanding, thinking, and reasoning abilities compared to their peers. It is the instructor's duty to follow up such children's class activities with therapeutic interventions to ensure that they remain at par with the rest of the class. This text presents the hypotheses, regression results, and descriptive statistics of a study that sought to determine the relationship between IQ and GPA by administering the WISC-IV to forty, 14-year-old ninth-graders.

Hypothesis

Numerous studies have shown that ceteris paribus, children with higher cognitive abilities are likely to be better academic achievers than their peers with lower cognitive abilities. Towards this end:

H1:…… [Read More]

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Regression vs Correlation Correlation Is Used to

Regression vs. correlation?

Correlation is used to test whether two variables covary, the strength of the relationship, and the direction of the association. A correlation calculation will generate a P-value and a correlation coefficient (r). By comparison, regression will generate the slope and intercept for a best-fit line that can be used to predict unknown values for the dependent variable.

What percentage of depression is not associated with Facebook usage?

The coefficient of determination (r2) is 0.661, which means that 66.1% of the variance in depression is due to the amount of time spent on Facebook; therefore, 33.9% of the variation in depression cannot be explained by time spent on Facebook.

Q3: Variables that could be contributing to the variance not explained by time spent on Facebook?

The unexplained variance in depression scores is the amount of error between measured levels of depression for a study subject and what was predicted by the regression line. This error is due to other variables, possibly naturally-occurring variation. Natural variation in depression could be explained in part by genetic differences or environmental factors like early life experiences (Klengel & Binder, 2013). The amount of variation explained by genetic factors is represented by the…… [Read More]

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Economic and Quantitative Analysis Topics Roughly Six

economic and quantitative analysis topics, roughly six in total. Those topics, in order, are focus on a non-core variable (and model) for the country of Nigeria, analysis of the World Bank World Development Indicators (WDI) model, comments on regression and the validity questions rising from within, the general problems and issues with regression analysis in general, whether any of the variable in the author's personal model have problems related to non-stationarity, and finally a suggestion of any changes to the models mentioned previously based on the outcomes that came about and the policy implications that can be garnered from this analysis.

Nigeria Non-Core Variable

The government and economics of Nigeria heavily focuses on exports of its vast mineral, petroleum and natural gas resources. An industry that has been a microcosm as compared to those exports over the recent years and decades has been the service sector (Nigeria, 2012). In many ways, Nigeria is the polar opposite of the modern-day United States, which has a higher (and growing) service economy while its manufacturing (especially of simpler goods) is falling rapidly.

The wider GDP of Nigeria (inclusive of both common staple exports like oil and minerals as well as everything else) has…… [Read More]

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Communicating the Results of a Multiple Regression

Communicating the Results of a Multiple Regression Analysis

Business Theory: "Communicating the Results of a Multiple Regression Analysis"

This report has the stated objective of examining the communication of the results of a multiple regression analysis and as such, a multiple regression analysis is described both in theory and in form demonstrating the progression of such an analysis. The multiple regression in this study examines bivariate factors in predicting the success of sales people for XYZ corporation.

The presentation of a multiple regression analysis is addressed in the work of Kuiper (2008) that the goals of multiple regression analysis are to: (1) describe or develop a model that describes the relationship between the explanatory variables and the response variable; (2) predict or use a set of sample data to make predictions; and (3) confirm in that theories are reported as often developed about individual variables including confirmation of which variables or which combination of variables should be included in the model. Regression is then used to determine if the contribution of each explanatory variable in a model captures much of the variability in the response variable. (Kuiper, 2008) Standard information to report in a multiple regression table includes those stated…… [Read More]

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Correlation and Simple Linear Regression

Correlation, Simple Linear Regression

In this paper, we perform a linear regression analysis on previously collected data related to the number of daily e-mails received (R) and sent (S) by a particular user (the author). We have depicted the original daily e-mail data as a time series, incrementing N. By 1 for each day's measurement. The computed regression coefficient r is the slope of the regression line.

A time series consists of sequencing successive data points at uniform time intervals. As such, this exercise represents a meaningful statistical analysis to determine whether a natural temporal ordering is inherent in the data. It should be recalled that the collection of data for each of R. And S. consisted of 15 daily samples, which were collected during two exercises spanning 10 and 5 days respectively. This factor will be noted in the analysis to follow. Table 1 illustrates the predicted values and subsequent regression analysis for the e-mails received (R). Table 2 illustrates the predicted values and subsequent regression analysis for the e-mails sent (S).

This section summarizes the regression analysis for e-mails received (R).

Time Series (N)

E-mails Received (R)

Predicted Value

1

2.581

2

0.147

3

6.098

4

2.311

5…… [Read More]

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Linear Regression Examples

Linear Regression

Predictions and Hypothesis Testing

What benefit does a variable provide when developing and examining models?

Statistics can be used to describe a phenomenon or conduct hypothesis testing, but statistics can also used to predict outcomes (Hanneman, Kposowa, & Riddle, 2012, p. 7). To enable predictions to be made, variables are required in the statistical model. Variables allow researchers to model the mathematical relationship between two or more phenomenon. For example, the relationship between tree circumference and the number of leaves could be described by the two variables girth and leaves. This relationship may or may not be causal, but it could be correlational. If a causal relationship is suspected, then maybe reducing the number of leaves inhibits expansion of tree girth. In this case, leaves would be the independent variable and girth the dependent variable. If the model is valid, then the tree girth could be predicted for any value of leaves. Variables therefore allow researchers to test hypotheses and make predictions.

2. Explain the purpose of simple linear regression and scatter diagrams. Please provide a simple linear regression model and define each variable used.

Linear regression is a statistical tool for quantifying the relationship between two variables…… [Read More]

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Correlations and Regression

Correlation & Regression

A fifth grade science teacher wants to know if there is a relationship between final exam scores and overall coursepoints after adjusting for a quiz score.

In order to determine whether there was a significant relationship between overall coursepoints and final exam scores, after controlling for quiz scores, a hierarchical regression was run. All assumptions were assessed using SPSS. There was independences of residuals, as assessed by a Durbin-Watson statistic of 1.08. An examination of various scatterplots indicated a general linear relationship between variables of interest, although perfect linearity was not observed.

Overall Scatterplot

Partial Regression Plot: Final Exam Score & Quiz Score

Figure 3. Partial Regression Plot: Final Exam Score & Course Points

The assumption of homoscedasticity was violated, as the scatterplot in Figure 1 demonstrates (i.e., the values were not evenly spread across the scatterplot). There was no evidence of multicollinearity as evidenced by no correlations between independent variables greater than .7 and no tolerance statistics less than .1. Additionally, no outliers were detected, as evidence by no studentized deleted residuals values greater than +/- 3 standard deviations. An examination of the leverage scores indicated that there were none greater than .5, and as such,…… [Read More]

Statistical Analysis Reported in Two Journal Articles

Statistical Analysis Reported in Two Journal Articles

Research endeavors, albeit it clinical, empirical, descriptive, historical, or case study oriented, must at all times adhere to the rigors of effective or best-fit research practice. Without stringent controls placed on the area of investigation no research endeavor will advance any body of knowledge. To this end all research must be finely tuned and described as to intent or purpose, phenomenon to be assessed and reported upon, and relevance and efficacy of conclusions drawn. The remainder of this report will focus one a particular component in a research endeavor that is crucial for the acceptance of findings and conclusions drawn, namely the statistical technique employed to analyze the measured data obtained. However, prior to the actual evaluative critique pertaining to the two articles chosen I first want to present to the reader a brief scenario as to the importance of selecting the most appropriate statistical tool when analyzing measured data.

The primary purpose of the statistical process is to make order out of chaos (Ohlson, 1997). By properly applying selected statistical processes to assessment or measurement data the researcher can determine whether or not the research variables (i.e., independent and dependent) under investigation…… [Read More]

ANOVA Analysis Is Derived From Analysis of

ANOVA analysis is derived from ANalysis of Variance and is used bets where the dependent variable is categorical. In the field of science, this type of analysis is frequent where samples from two or more subjects are analyzed for the inherent properties that they have (Explorable, 2012).

In this case, the size of the maple leaves being dependent on the location of the tree will be used. Maple trees under the shades of taller trees are smaller than the maple leaves from the trees out in the open and even smaller are the maple tree leaves from the median of parking lots. In order to put such a hypothesis to test, 5 groups of 10 maple leaves from the three locations will be collected.

Group I will be the leaves from the shade, group II will be the leaves from the open fields and group III will be those from the parking lots. In such a scientific analysis, the ANOVA analysis comes in appropriately. Apparently it is likely that the groups could be broadly similar, for instance the range between the largest leaves and the smallest in group I could a large fraction of the leaves in the other two…… [Read More]

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Managerial Assessments of the Applications of Regression

Managerial Assessments of the Applications of Regression

Management

The commentary of the article begins with the subject of the research in the article: Organizational Politics within Academic Departments. This subject is valid of research as it is a factor of which many students are unaware, yet are apart of and by which they are affected. Uninformed views or stereotypes of academia may not include the order of politics evident among faculty and staff within each department, yet they exist. Therefore the first piece of criticism is to validate the subject matter of the study. Furthermore, the authors argue for the importance of their study as there is little research in the area, for reasons that some of which are obvious and self evident.

The specific behavioral focus for the article is conflict. The authors wish to understand the nature of conflict within organizations and the impact conflict has upon perceptions. There are nine hypotheses the researchers intend to prove or invalidate, some of which are:

Hypothesis 1: Departments with higher levels of intra-departmental task and relationship conflict will have more politicized climates. Hypothesis 3: Paradigm development will be negatively related to political climate such that departments belonging to well-developed paradigms…… [Read More]

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Multiple Regression it Is Hypothesized That Self-Efficacy

Multiple Regression

It is hypothesized that self-efficacy, appraisal, challenge and resources will negatively predict perceived stress whilst avoidant strategies will increase levels of perceived stress.

Sample Description

The sample consisted of 100 participants, 27 males and 73 females. Forty percent of the participants were not students, 30 were studying as part time students and 29% were studying as full time students. Fifty-five percent of the sample was employed full time, 25% were employed part-time and 20% reported being unemployed. Participants in the sample ranged from 16 to 70 years of age, with an average age of 35.6.

The assumption of normality was met for each individual variable. All of the variables included in the regression analysis displayed relatively normal distributions. The distribution for Self-Efficacy has a slight negative skew, but not one that should influence the interpretation of the results. An examination of scatter plots also revealed no problems with respect to linearity.

The correlation matrix shows that many of the predictor variables are correlated with one another, indicating that their unique contribution to predicting the outcome variable of perceived stress might be limited, however no multicolinearty is evident.

A small number of univariate outliers were found on individual measures,…… [Read More]

Economic Analysis of the Operating Cost That

economic analysis of the operating cost that are incurred in the running of a metro station. The paper also reveals the variables that are tied to the cost efficiency of the whole process of running a metro station. The cost of operating the stations is however grouped under the semi-fixed costs that are involved. This is because these costs do not vary proportionately with the output of the metro business. This paper seeks to shed light on some of the main factors that affect these costs. Empirical analysis reveals that very strong system specific factors influences costs but it is worth mentioning that there are other station specific details that also influences the costs. These include the number of platforms in the station, the length of the passageways, the interchange demand, availability of toilet facilities etc.We also discover that presence of air-conditioning has a great effect in the propulsion of the expected station operating cost by over forty percent.

Introduction

The study of the cost structure of the railway transportation industry has receives a considerable chunk of academic literature attention. For example Caves et al. 1980,1981a,1981b.1985;Freeman et al. 1985;Dodgson et al. 1985;Wunch 1996;Oum et al. 1999; Cantos et al. 1999.All…… [Read More]

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Correlation and Regression Using an

For example, children whose last names end with a vowel may have a statistically higher chance of manifesting type II diabetes. The reasons for this might be the poverty and discrimination faced by many Latinos, the letters of whose names more often end with a vowel than other ethnicities. Poverty often leads to a poorer diet, less access to places to exercise safely, less access to healthcare, and a lack of opportunities to become educated about how to live a healthy lifestyle. It is poverty that is the causative factor to the child's ill health, however, not the child's name, and changing the child's name will not affect the outbreak of type II diabetes in the Latino community.

Reference

Sykes, Alan O. An introduction to regression analysis. University of Chicago Law School.

Retrieved February 8, 2010 at http://www.law.uchicago.edu/files/files/20.Sykes_.Regression.pdf… [Read More]

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Correlation Statistics V Regression Statistics

Correlation and regression are two important test statistics that are utilized in a study that focuses on understanding the relationship between two variables and/or the effect of one variable on another. In correlation statistics, there are two variables that are related to each other whereas in regression, and explanatory variable and a response variable are utilized ("Introduction to Correlation and Regression Analysis," 2013). Generally, the main aim of correlation statistics is to examine whether two measurement variables co differ and determine the strength of the link between variables. On the contrary, regression statistics focuses on expressing the relationship between two measurement variables using an equation. As a result, of the difference in focus, correlation statistics and regression statistics are suitable for different circumstances.

Regression statistics is suitable for situation where the problem of interest or issue being examined is the nature of relationship between a dependent variable and an independent variable. In this case, the dependent variable is considered as the response variable whereas the independent variable is regarded as the explanatory variable. For instance, if the problem of interest is the impact of age on height, a regression analysis is the most suitable test statistics since it will help…… [Read More]

Statistical Analysis in Reaching Their

The median is the mid-point of a given data set; rather than the mean, which produces a single number that takes into account the extremes of the data set as well as the middle, the median tends to be more stable, finding the half-way point between extremes rather than directly incorporating them. For wage comparisons, especially over time, the median is useful and an excellent choice of statistical tool precisely for this stability and lack of influence by extremes that are exceptions to the general findings of the data set.

Conclusion

The examinations of the statistical tools herein have been brief, but hopefully effective. Understanding the different methods of analysis and presentation that are at one's disposal is essential in order to carry out effective research in a way that is meaningful to other researchers and practitioners, in the filed of human resource management and in all other areas of scientific research as well.

References

Edwards, C. (2009). "The pursuit of happiness (human resource management)." Engineering & technology 4(4), pp. 76-9.

Gill, G. (2004). "Perception of safety, safety violation, and improvement of safety in aviation: Findings of a pilot study." Journal of air transportation 9(3), pp. 43-55.

Hwang, J. &…… [Read More]

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Correlation Regression and T-Tests Linear Regression Analyses

Correlation, Regression, and T-Tests

Linear regression analyses are conducted after correlation has been established (Cohen, West & Aiken, 2014). Correlation shows how two variables are related, that is how one variable behaves when the other changes. Regression analyses somehow quantify this relationship -- we use it to predict the value of the dependent variable at different values of the independent variable. Since regression analyses yield numerical values, they can only be performed on quantitative, measurable values. RQ1 in the week one assignment -- how does engagement in social media relate to loneliness -- fits the qualification for simple regression analyses -- the independent variable (engagement in social media is measured in terms of the number of hours one spends on the internet) whereas the dependent variable is measured in terms of quantified categories ranging from 'very low' to 'very high', where quantification would involve assigning numbers to categories, for instance, 'very low' is assigned a low value of 1, 'low' is assigned a relatively higher value of 2, and 'very high' is assigned the highest value, say 5.

Regression analysis in this case will help the researcher predict i) how one's degree of loneliness would change with changes in the…… [Read More]

A Cat Statistical Analysis Report

Statistical Analysis Report for the A-CAT

A-CAT was one of the Indian leading producers of electrical appliance within the medium-scale industry. The A-CAT manufactured and distributed domestic appliance to the rural population India. Moreover, A-CAT had two medium-sized manufacturing units in a small town of Gondia located at the remote district in Vidarbha, a less develop area in India. The company primary flagship product was 500 kilovolt amps voltage regulator branded with VR-500 tag. Established in 1986, the company could boast of 40 employees. A-CAT had established a partnership alliance with Jupiter Inc. and Global Electricals for the production of cabinets and TV signal boosters respectively. Since 1986, the A-CAT had been in operation and the company budget between 2010 and 2011 provided the annual sales of Rs. 9,800,000 ($147,128). The functional company department are design department, manufacturing department, purchasing department, and sales and service department. Contrary to other companies that focus on the urban areas for the marketing operations, the A-CAT focuses on rural areas, and offers 100 different household electrical appliances that include FM radio kits, TV signal boosters, battery chargers, electronic ballasts, and voltage regulators.

However, the company has recorded a decline in the sale voltage regulators…… [Read More]

Pest and Five Forces Analysis for Comcast

large organizations like Comcast to use both PEST and Porter's 5 Forces analysis in helping its leaders to understand their particular external environment?

Globalization has created an interesting dynamic in regards to Comcast's external environment. What once was a handful of competitors has now grown to include both international and online competition. To better grasp the current competition with an eye towards future innovations, a PEST and Porter's 5 forces analysis is necessary. This is particularly true as the business dynamics in Comcast's external markets has fundamentally changed over the years. Competition is now outside of the fundamental cable providers. Innovation and strategic mergers have created new product offerings for consumers. Globalization has created a rising middle class in many of Comcast's international markets. Finally, substitutes via the internet have placed pricing pressure on Comcast's core product offers. All of these factors thus contribute to management's view of the future operations of the business and how to effectively mitigate these forces on its external environment.

To begin, a PEST analysis consists of the strategic review of a company's Political, Economic, Social and Technological factors. A PEST analysis much like a Porter's 5 forces analysis, is used to identify threats and…… [Read More]

Using Meta Analysis Approach for Research

managers and the employees play an important role. In the present day, organizations incessantly experience and go through rapid technological changes, decreasing product life cycles, globalization, international global economic setting and also the extensive accessibility to information. As a result, in order for these organizations to continue surviving and being relevant in the market, style of management becomes a significant element in the success of the organization. The role of a manager as a leader within an organization can result in different styles of management chosen. The different styles selected by the managers have an influence on the behavior patterns within the organization, which in turn impacts the morale and motivation of the employee. In the end, the managerial style influences the level of satisfaction of the employee, which directly influences the level of productivity. According to Olmedo-Cifuentes and Martinez-Leon, Managers utilizing the fitting style of leadership can increase employee job satisfaction, productivity and commitment towards the organization in the long run (Olmedo-Cifuentes and Martinez-Leon,). Therefore, style of management, strategies employed, attitudes demanded and the culture nurtured are all elements that govern and largely impact the level of success of the organization. In essence, managerial styles can act as a…… [Read More]

Prison Overcrowding Empirical Analysis of

This view stresses a sociological approach to crime, suggesting that the behavior of criminals is more easily adapted and changed when law enforcement agents understand the circumstances and immediate environment an offender lives in that may contribute to offensive behaviors, and to one's behavioral characteristics.

Literature Review

The purpose of the preliminary literature presented is to provide an overview of the historical foundations leading to prison overcrowding, an exploration of the populations of people incarcerated and empirical evidence that provides an explanation for overcrowding. By examining this evidence the researcher will find support for the hypothesis presented, develop appropriate research questions and present insight into the significance and importance of the study topic selected for this research. The preliminary research review will include an overview of texts, primary and secondary research articles and studies that explore prison overcrowding, criminal behavior and law enforcement policies and procedures during the last three decades. Much of the research presented focuses on empirical evidenced gathered between the 1980s through the present. The results of this literature review will contribute to the meaning and impact of the primary research study proposed by the author.

History Incarceration and Prison Overcrowding

Alexander (1998) provides some history about…… [Read More]

References:

Final Term Paper State Health Systems and Regressional Analysis

knowledge management system would be beneficial in helping the SH administration with the patient data. This system is important because solving problems and making ideal resolutions on health care is heavily reliant on admission to knowledge. In today's progressively difficult environment, it quickly turns out to be vital for healthcare organizations to successfully achieve both internal knowledge and externally produced knowledge, so as to provide the best likely health care, attain operational superiority, and nurture innovations.

This would offer the best solution for the problem that SH is having for the reason that it assists with managerial competencies. When individuals in an organization experience information overload or lack the knowledge needed for decision-making, such as in the case of the incorrect prescriptions, adverse drug reactions, identical or needless lab tests, and misdiagnosis by the doctors, they become chaotic (Ashton, 2009). Form SH, without having this system, clinicians and managers can be handicapped or less productive. Also for SH, putting knowledge management systems in place can permit the movement of data and outcome in better, more-knowledgeable selections.

This system would be beneficial for the SH because it has a structured data that is a document, produced from data that has been…… [Read More]

Analysis of Gwa Genome Wide Association Study for OCD

GWA (Genome-Wide Association ) Study Analysis for OCD

The OCD (Obsessive Compulsive Disorder) is a type of mental disorder that makes people doing the same thing repeatedly. In other words, the OCD is characterized by unreasonable obsessive fear and thoughts that lead to repetitive behaviors. People suffering from OCD are unable to control their activities and thoughts. While the cause of OCD is unknown, however, the risk factors include stress and history of child abuse. (Moran, 2013).The OSD is characterized by the neuropsychiatric disorder with features of compulsion and obsession or combination of both features. (Moran, 2013). Within the last decade, the OCD is increasingly demanding high attention from psychiatric and medical institutions due to the higher rates of its clinical diagnosis. In the United States, people suffering from OCD are approximately between 1 and 5% of the total population, however, the OSD is common among adolescent and adults. Most psychologists believe that OCD is characterized by the neurotic disorder that includes general anxiety, and panic disorder. In essence, severe OCD can affect personal life of individuals in a negative way. However, majority of people suffering from OCD can still perform many essential activities because the disease is different from…… [Read More]

Linear Regression Models Meier Chapter

g. with the same group being tested on a pre- and post-test).

Variations between t-tests are the following:

a. T-test on independent samples that have unequal variance. The problem here is determining sampling error in order to accurately determine whether two samples are or are not really different. This test is also used when the number of cases in each sample is different or when the number of cases in one or both the samples is small.

Steps:

1. Hypothesis is formulated. Means and SD for groups are worked out

2. Standard error for each group is calculated as is overall standard error

3. The t-score for the difference of means is calculated

4. The t-score is looked up and probability result applied to hypothesis.

B. T-test for independent samples with equal variances.

Since you want to avoid a Type 1 error, it is important to ensure that both groups do indeed have equal variances. To do so, perform a Levene test. Alternately, test for unequal variances can be used, unless one is absolutely certain that both groups have equal variances.

The only difference in calculation here to that of unequal variances is that instead of standard error worked out…… [Read More]

Resources:

Behavioral Finance and Analysis of American Financial

Behavioral Finance and Analysis of American Financial Crisis

Financial theories are the cornerstone of the modern corporate world. They lay the foundation for most tools used in areas like asset pricing and investment banking. Most theoretical concepts like general equilibrium analysis and information economics are planted in the field of microeconomics. There are several different financial theories based on both consumer behavior, as well as how they impact decisions made by financial managers.

One financial theory that many business managers use is The Modern Portfolio Theory,

or MPT. It suggests how investors use diversification to enhance their portfolios, as well as how to price an asset based on the risk, in relation to the market as a whole. Modern portfolio theory displays the return of an asset as a variable, and the portfolio as a combination of all of the assets. The return of a portfolio is also a random variable and it has an expected value with variance.

The type of risk in this model is viewed with the general variance of a portfolio return. It assumes that an investor picking from multiple portfolios, all with the same expected rate of return, will choose the portfolio with the least…… [Read More]

Works Cited:

Thematic Analysis of Literature in Order to

thematic analysis of literature in order to influence of transformational leadership on organizational outcome. The data is identified from relevant literature on organizational behavior and then used in the creation of a more coherent picture. Recommendations and conclusion is then presented on the benefits of transformational leaders to various organizations.

The concept of transformational leadership has been suggested to lead to an improvement in the level of organizational outcomes (Tucker & Russell, 2004). The work of Bass (1994) indicates that transformational leadership comprises of four main elements. That is; individualized consideration, idealized influence, inspirational motivation and intellectual stimulation. In this paper, we investigate if indeed transformational leadership enhances the level of organizational outcomes.

Research questions

This paper will be guided by the following research questions

What are the effects of leadership in general on organizational performance?

2. What are the ways in which leadership can be used in enhancing organizational performance?

3. What are the attributes of transformational leadership that are necessary in realizing organizational success?

4. What is the impact of transformational leadership on follower satisfaction?

5. What is the impact of transformational leadership in the level of organizational commitment?

Literature review

Extant literature has been dedicated to the…… [Read More]

Sources:

Statistical Analysis and Forecasting of

Their pricing approaches, while in the boundaries of solid statistical analysis, are somewhat opportunistic. For Zillow to be more accurate, the use of a range of valuations for each property could be included. This would be more realistic to the true conditions of the market. Finally, the methodology used for this analysis is based on the latest 30 home sales; therefore the data itself and analysis are much timelier in reflecting the market conditions..

Zillow Analysis

In evaluating the strengths and weaknesses of Zillow.com, it is immediately apparent that this website is much more navigable than realtor.com, and also gets away from the troublesome opt-in screens realtors use before allowing properties to be sold. The mash-up with Google Maps is also very well done. In summary, the strengths and weaknesses of Zillow.com are provided here:

Strengths

Excellent mash-up using Google Maps and their own pricing databases to provide an easy-to-navigate website and pricing comparison engine.

Easy for potential purchasers to get a quick idea of what the comparable sales are in their area of interest and check on the pricing of the last five sales in the immediate neighborhood.

Excellent use of pop-up windows and property pictures and features.

Useful…… [Read More]

Multiple Liner Regression to Determine the Time

multiple liner regression to determine the time taken to dispatch daily subscription newspapers from the New York Times Printing Plant to several offices and homes in New York City and its neighborhood. The newspaper delivery routes are to be the shortest and most efficient in terms of conserving fuel that would otherwise be wasted on traffic jams. The Logistics Manager suggested that the variables that are most crucial are the distance to be traveled by the delivery vans and total number of newspapers to be delivered in any particular area. The logistics Manager pooled observations from 25 offices and homes on the average newspaper delivery times. This data was then used to model the econometric model and an analysis carried out.

This paper concludes with recommendations to the New York Times CTO on the most important changes on the logistics department of the firm. This paper prescribes the best possible solution that would yield an increase in the company's ROI.

Introduction

Econometrics is the development and the application of quantitative together with statistical techniques in the study of economics. It combines both the theories of economics and statistics in the analysis and the analysis of relationships that exists in economics.…… [Read More]

Resources:

U8D1 Regression Discontinuity and Correlation

Predictors of stress included being male, young, Hispanic, living in a rural residence, and not belonging to any religious institution. Also being male and young were associated with high burnout rates, whilst involvement in religious activity were associated with lower burnout rates.

The child worker whose job status was that of professional was more likely to show burnout and compassion fatigue than another not of that status.

The variables here were dependent variable -- burnout and stress, independent variable -- status of the worker as well as personality and environmental characteristics (namely those described above).. Explain how the research exemplifies regression discontinuity or correlation research, and identify the specific design, if appropriate.

This is an example of correlation research. The researchers wished to see whether any specific factors were associated with burnout and stress and whether the occurrence of these variables showed positive association (or negative association) with an increase or decrease of stress / burnout. Analyze the aspects of the research that enabled the researcher to draw conclusions about the results. Include a description of the threats to validity that are particularly relevant to this study, and describe what the researcher did to reduce these threats.

The researchers used…… [Read More]

Bibliography:

Run Linear-Linear and Log-Log Regression

Display

The effectiveness of using display as a marketing mix variable is average. It has a coefficient of 0.253. This is in regard to all of the brands.

Feature

The effectiveness of using feature as a marketing mix variable is noted to be the most efficient for all of the brands. This is due to its high level of significance (0.315).This means that it is the variable which should be perfected by all of the brands

(c) Store 4 is the largest store in the market with more than 40% of market share (see "Statistics"). As a brand manager for Coca-Cola, you are not happy about the fact that sales of Coca-Cola lag behind Pepsi, your major competitor, in the store. Can you explain why this happens? Also, can you recommend how to stimulate sales in store 4 by marketing more effectively? It would be useful to provide some numerical examples.

Why Coca-Cola lags behind Pepsi in sales

A review of the statistical variable outcomes reveals that the most important marketing variables in order of important are feature, display and then price. A review of the feature variable of Coca-Cola reveals that it lies below the one for Pepsi by…… [Read More]

Sorting and Regression-Discontinuity Design in

However, their measurable test gains may be less than students who do not have such challenges. Quality of instruction is also an issue: perhaps good instructors and smaller class size is best, but what is 'better' -- an average teacher with a small class or a good teacher with a large class? Baker suggests the former scenario is superior, given that smaller class sizes can increase the need for teachers -- good or bad -- leaving many students in the hands of less competent teachers. However, at some threshold class management becomes impossible, even for a good teacher, and the line is difficult to draw. Benefits may be different based upon student's gender, preparation level of the student, social class, and also the preparation level of the teacher. More experienced teachers may be better able to cope with larger classes, and also more adept at using smaller class size to individualize their curriculum while still meeting benchmarks.

The benefits of small class sizes may be cumulative, even if the overall, measured year-to-year effects are small. That would explain such problems as the discrepancies between different grade levels in measured effects of class sizes. But Baker sees such shifts as based…… [Read More]

Factor Analysis Cluster Analysis and Such

transforms correlations among a set of observed variables into smaller number of factors, containing essential information about the linear inter-relationships among the original test scores (Kriegel, Kroger, Sander, & Zimek, 2011). Factor analysis is used in behavioral sciences, social sciences, and other applied sciences dealing with large quantities of data. In addition, factor analysis is subdivided into two major groups; exploratory and confirmatory. Cluster analysis on the other hand entails dividing a set of variables into groups; clusters with data in the same cluster being similar to each other as opposed to those in other clusters. Cluster analysis is mainly used in statistical analyses such as information retrieval, and bioinformatics. Just like factor analysis, cluster analysis has two subgroups; exploratory and confirmatory.

Q-sort vs. R-sort Factor and Cluster Analyses

In both factor and cluster analysis, Q-sort entails ranking sets of statements based on how strongly subjects agree or disagree with them (Storch & Fischel). In line with this, Q-sort is a reflection of the respondent's view about the topic and its analysis helps in identifying specific respondent groups. Despite being complex forms of regression, both Q-sort and R-sort are vital in revealing data similarities and check for possible similarities as…… [Read More]

Bibliography:

Investment Report and Analysis Harley-Davidson

Harley-Davidson Retail Sales and Deliveries

Source: Seeking Alpha (2007)

Over the past four years, account receivable growth has outpaced sales and the result is there is more inventory on dealer's lot than at any time in the history of HOG. The analysis states: "If the additional dealer inventory build was taken out of Harley's EPS from the previous two years and shipments evenly distributed throughout the quarters then Harley would have reported $3.41 last year and $3.14 in 2005 or a full $1.00 less of EPS over the past two years. Without dealer build, HOG would have reported net income without inventory build of $891 MM in 2006 and $838 MM in 2005 versus $889 MM in the base year 2004 placing the current P/E of the firm at an estimated 18x versus the current 15.6x. " (Seeking Alpha, 2007)

Accounts Receivable Trends Over Past Four Years

Source: Seeking Alpha (2007)

The Seeking Alpha analysis states that investigation of Harley-Davidson makes it "readily apparent there was a high correlation between deliveries of new cycles and the company's EPS. By controlling for the 15% of share buyback Harley has engaged in since q1 2004, a robust EPS model was built that…… [Read More]

References:

Profit Analysis Is a Financial Accounting Methodology

Profit analysis is a financial accounting methodology that has myriad uses in the manufacturing industry and other sectors like the restaurant, energy, and banking industry (Brugger, 2013). It helps in business management. Some of the specific uses of cost volume profit analysis include goal setting, pricing strategy, operational efficiency, and marketing strategies (Brugger, 2013).

Cost profit volume (CVP) analysis is principally used to position management to se more informed, data driven, and realistic business goals (Brugger, 2013). Setting realistic business goals calls for integration of short and mid term objectives with annual objectives. By using CVP the goals are deemed tangible as opposed to being treated as wish-lists (Brugger, 2013). This is because the goals can be tied to specific data.

Companies engage in marketing with a view to attaining profitability. Companies must therefore know the costs that are associated with production of goods and the volume necessary to make the company to break-even (Brugger, 2013). Business enterprises must be in a position to adjust matrices like the volume of goods produced to determine changes that come along with such an action before such actions are implemented. This is integral in deciding if a particular marketing strategy is worthwhile (Brugger,…… [Read More]

Sources:

Policy Analysis Critique - Hong Kong Health

Policy Analysis Critique - Hong Kong Health Care System

Policy Analysis Critique: Hong Kong Health Care System

The health care system in Hong Kong is believed to be one of the best in the world. The majority of people there live longer than people in many other developed nations, and the infant mortality rate is also very low. Those things show that people in Hong Kong are committed to their health and that they have a government that enacts policies to protect them and allow them to have full access to health care. Many countries do not offer that to their citizens, so Hong Kong is actually something of a rarity - and allows its people to enjoy a life expectancy of upwards of 80 years for both men and women. That is the second-longest life expectancy of any country in the world. Of course, there are imperfections in the health care in Hong Kong, just as there are anywhere else. People who live there still pass away, and some of them still die from diseases that are preventable or that went untreated or improperly diagnosed. Such is the nature of medicine.

Addressed here will be one specific policy in…… [Read More]

Works Cited:

Multivariate Analysis Is Appropriate for a Quantitative

multivariate analysis is appropriate for a quantitative study. Conclude your posting by describing your personal interests in one of the multivariate statistical tests and its potential usefulness to you in future research.

The question of whether to use a multivariate vs. univariate or bivariate statistical tests is rather straightforward. Multivariate statistics provide analyses in cases where there are more than one independent variable and/or more than one dependent variable (Tabachnick & Fidell, 2012). Univariate analyses are statistical tests that involve one variable, whereas bivariate tests/statistics involve two variables such as a Pearson correlation coefficient (Runyon, Coleman, & Pittenger, 2000). It is certainly possible to do many different univariate or even bivariate analyses in the place of a multivariate one; however, the researcher loses statistical power, increases the probability of a TType I error, and is unable to determine all of the relationships in the data that can be analyzed with a multivariate analysis (Tabachnick & Fidell, 2012). Multivariate statistics are extension of univariate and bivariate statistics and represent the general case, whereas univariate and bivariate statistics are special cases of the multivariate model (Tabachnick & Fidell, 2012). Multivariate statistics allow for the simultaneous analyzing of multiple dependent and/or independent variables…… [Read More]

Statistical Analysis Is Recession Raises

The author did not apprise the reader of the measure of poverty, so it is assumed that the way poverty is measured is the same over the decades. This may not be true so in this instance the comparison can be misleading.

The use of the median as a measure of income level is a consistent use of a statistical measure. The median is a more robust measure of national income than the mean since it is not as susceptible to the influence of outliers in the data (Gravetter & Wallnau, 2008). The use of the median provides a more precise measure of the middle class challenge. The conclusion that the middle class is stagnating is a legitimate conclusion based on the lack of income growth within that group. In this instance, the statistics were used appropriately.

The use of data to show increases while legitimate can provide an inaccurate picture of the state of a problem. The author used counts to show that the numbers of persons without health care increased from 46 million in 2008, to 51 million in 2009. This is an increase in counts but it may not represent a percentage increase; it is possible that…… [Read More]

References:

Genome Wide Association Study Analysis for OCD Complications

¶ … Genome-Wide Association Study for OCD Complications

The OCD (Obsessive -- compulsive disorder) is referred as repetitive behaviors and thoughts experienced by individuals. (Visscher, Brown, McCarthy, et al. (2012). Typically, the genes' characteristics of twins and families have revealed that the OCD has the feature of multifactorial familial condition involving both environmental and polygenic factors. (Moran, 2013). Genetic studies have revealed that the interaction of the glutamatergic, serotonergic, and dopaminergic systems and genes affecting them play a crucial role in functioning of the circuit. (Yang, Lee, Goddard, Mand et al. 2011). Meanwhile, the environmental factors that include psychological trauma, adverse perinatal effects and neurological trauma may modify the risk genes, which can consequently manifest the compulsive-obsessive behaviors. (Visscher, Brown, McCarthy et al. 2012). The OCD is a frequent and, relative common debilitating neuropsychiatric disorder affecting 2% of the U.S. population. (Arnold, Sicard, Burroughs, et al. (2006). Typically, the OCD is obsessions of repetitive behaviors and thoughts experienced as unwanted. (Baxter, Scott, Vos, et al. 2012). In other words, the OCD is a health and clinically heterogeneous disorder consisting of different types of symptomatic expression. (Murray, and Lopez, 1996). In the United States, the OCD can affect people in early…… [Read More]