Applying Basic Statistical Tests to a Research Scenario

For statistical analysis purposes, we can simplify Stevens’s four levels of measurement into two:

Nominal variable (often referred to as categorical): Political affiliation is an example of a nominal variable, and could be measured as 1 (Republican), 2 (Democrat), and 3 (Independent). The mean, or average, of political affiliation has no meaning.

Metric variable (often referred to as scale variable, which includes ordinal, interval, and ratio): Political philosophy is an example of a metric variable when measured on a Likert-type scale of 1 (very conservative), 2 (conservative), 3 (liberal), and 4 (very liberal). The mean, or average, of political philosophy does have meaning.

Basic inferential statistical analyses can be categorized as mean difference, correlation, and association. The Statistical Analysis Decision Table, in this week’s Learning Resources, will help in the selection of an appropriate inferential analysis procedure, which will be the focus of the Discussion. Specifically, you will select an appropriate inferential statistical analysis for your quantitative scenario.

To Prepare

Review the lead-in for the Discussion and this week’s Learning Resources. Pay particular attention to the levels of measurement (categorical or metric) associated with variables in different types of statistical tests.

Review your inferential quantitative scenario developed to date.

Using the Statistical Analysis Decision Table, in this week’s Learning Resources, determine which inferential statistical test you would use given the level of measurement (categorical or metric) of each variable.

Alignment of scenario elements is important. See the Examples of Aligned and Misaligned Scenarios document, which can be downloaded from the Week 7 Learning Resources area of the classroom.

Discussion posts are pass/fail but have minimum criteria to pass. See the Discussion Rubric to ensure you understand the pass/fail criteria.

By Day 3

This week is only about the quantitative scenario. Repost, or build on or refine as needed, your quantitative scenario using the following headings and according to the italicized instructions given for each element:

Program of Study: Identify your specific program of study and, if applicable, your concentration area.

Social Problem: Briefly describe the social problem or phenomenon of interest. Typically, this can be done in 3 or fewer sentences.

Quantitative Research Problem: Complete the following sentence: The scholarly community does not know…

Quantitative Research Purpose: Typically, this is a 1-sentence statement addressed by completing the following sentence: The purpose of this quantitative study is…

Quantitative Research Question: Typically, this is a 1-sentence question unless you have more than one research question.

Theory or Conceptual Framework: Identify a specific psychological or sociological theory or specific aspects of a conceptual framework that guides the scenario. Briefly describe how the specific theory or conceptual framework guides your research question and will aid in interpretation of results.

Quantitative Research Design: Identify a specific quantitative research design. Do not use broad terms, such as survey design, cohort design, longitudinal design, causal-comparative design, cross-sectional design, and so on. Briefly describe how the selected design fits your scenario.

Quantitative Sampling Strategy: Be specific.

Quantitative Data Collection Method: Be specific.

Variables: Briefly describe each of your variables to include their range of measured values, level of measurement (nominal, ordinal, interval, or ratio), and identification as either an independent or dependent variable.

Statistical Analysis: Describe and defend a specific statistical procedure you would use to answer the research question.

Note: Use proper APA format. If helpful, support your postings and responses with specific references to the Learning Resources.

# Applying Basic Statistical Tests to a Research Scenario For statistical analysis

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