Discuss how you would use regression to learn more about the nature of the relationship between the variables
Regression is a significantly common technique used for analyzing data. Regression analysis is employed to delineate the relationships between a group of independent variables and the dependent variable. In this case, the dependent variable is substance abuse. On the other hand, the set of independent variables comprise of exposure to substance abuse, ethnicity, age, and gender, poverty, and loneliness. Regression would play a significant role in helping with the learning process regarding the nature of the relationship between the variables. The analysis will particularly entail descriptive statistics as well as regression, correlation, and ANOVA analysis. Descriptive statistics will be used to present demographic data and provide measures of central tendency such as averages and median, while the statistical analyses will be important for testing the relationship between the dependent and independent variables (Draper and Smith, 2014).
One-way ANOVA is delineated as an approach that can be utilized for the comparison of means of two or more samples. There are different necessitated conditions for a one-way ANOVA. First of all, the variances of populations are the same. Secondly, the response variable residuals follow a normal distribution and lastly, the responses for a particular group are independent and they are also random variables that are normally distributed and are identical (Weiers, 2010). The analysis will seek to analyze the F-Statistic. Basically, this is the figure that is attained subsequent to conducting a regression analysis or subsequent to running an ANOVA test. This is purposed to ascertain whether the means of two populations are substantially different (Weiers, 2010).
Specifically, this research study will use multiple regression analysis. This is because there are different sets of variables. This analysis is meant to determine the correlation and trends in these sets of data. Therefore, in this case, the different independent variables will be set in regard to the different predictors including: (x1)1, (x2)1, (x3)1, Y1).
The equation used in the research study will be:
Multiple regression: Y = b0 + b1 x1 + b0 + b1 x2…b0…b1 xn
In this case Y = substance abuse
(x1) will be level of exposure
(x2) will be ethnicity
(x3) will be age
(x4) will be gender
(x5) will be poverty
(x5) will be loneliness
Discuss any issues associated with measurement error that could be plaguing your study
Measurement error takes into account the dissimilarity between a measured quantity and its true value. There are two types of measurement error including random error, which is an error that naturally takes place and is anticipated to be present with any sort of experiment, and also systematic error, which is instigated by misconstrued research instrument that impacts all measurements. There are a number of issues linked with measurement error that could be adversely impacting my research study. Notably, this is an epidemiological research study, which measures characteristics of a population. Bearing in mind that the parameter of interest in this particular case is the prevalence of an exposure, and that the research study is carried out on individuals, it is subject to bias (Trochim, 2006). There are different types of measurement error. One of them is systematic error, which is a kind of error that brings about measurements that incessantly shift away from the true value in the similar direction. The second type of error is the random error, which takes into account the variance between a person’s reported understanding of the research instrument’s reading compared to the actual reading. Third, there is gross errors, which take into account the physical errors in investigation tool or...
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