Frequency and Descriptive Statistics in Nursing Research
This paper examines the application of frequency and descriptive statistics within nursing research. Using a purposive sample of 100 patients, the study analyzes key variables including age, highest school grade completed, race, ethnicity, and family income. Descriptive statistics such as means, standard deviations, and skewness values are calculated to summarize and interpret the data. Frequency statistics are used to characterize the racial and employment composition of the sample. The paper demonstrates how these foundational statistical methods enable researchers to meaningfully describe health-related data sets without drawing broader inferential conclusions about the population.
- Introduction: Defines descriptive and frequency statistics in nursing
- Methodology: Quantitative approach using summary and frequency statistics
- Sample Size and Data Collection: Purposive sample of 100 patients with vitals
- Results and Statistical Findings: Mean, skewness, race, and income data presented
- References: Cited sources supporting statistical methods used
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What makes this paper effective
- Clearly distinguishes between descriptive statistics and frequency analysis at the outset, giving the reader a precise conceptual framework before the data are presented.
- Grounds every statistical measure (mean, standard deviation, skewness) in an interpretive statement, connecting numbers to meaning rather than merely reporting them.
- Uses a focused, real-world nursing dataset to ground abstract statistical concepts, making the analysis immediately applicable to health science readers.
Key academic technique demonstrated
The paper demonstrates the technique of linking statistical outputs to interpretive criteria — notably using the ±3 skewness range as a decision rule for normality. This shows awareness that descriptive statistics are not ends in themselves but tools for evaluating data quality and distribution before further analysis.
Structure breakdown
The paper follows a standard quantitative report structure: an introduction defining key terms and scope, a methodology section outlining analytical approach, a sample description, and a results section presenting grouped findings (continuous variables first, then categorical, then distributional shape). The reference list supports claims with both methodological and discipline-specific sources. The structure is lean and appropriate for a short applied statistics report at the undergraduate level.
Introduction
Statistical analysis has been applied across many fields, including — but not limited to — health sciences, social sciences, and physical sciences. This paper assesses the application of frequency and descriptive statistics in health science, with a specific focus on nursing. Descriptive statistics are a branch of statistics that aims to describe data sets without making inferences about the broader population from which the data were sampled (Gholami et al., 2020). Their purpose is to characterize the study's variables in a meaningful way. Frequency analysis, by contrast, summarizes data by depicting the number of times a given value occurs in the data set or output (Gray & Grove, 2020). This entails analyzing where data are concentrated or clustered, the range of values, the presence of extreme values, and the identification of intervals that make sense for categorizing variable values.
Methodology
This section outlines the procedures used to conduct the study. A quantitative technique was employed, analyzing data sets through summary statistics and frequency statistics. The study sought specifically to apply frequency and descriptive statistics in a nursing context.
Sample Size and Data Collection
Data were collected using purposive sampling. A sample of 100 patients was gathered, comprising compiled vitals, pain scores, and medications for each patient.
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