# Module 7 ICJ 715 Read the description carefully !! ###### Andrew Newman
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Module 7 Discussion
Question
Propose a research hypothesis that can be tested using any of the five test statistics discussed in this module. State the null hypothesis.
Identify the variables in your proposed hypothesis (i.e. the independent/dependent or predictor/outcome)
Describe the levels of measurement of each variable in your hypothesis.
Determine what test statistic you would chose to test your proposed hypothesis. Briefly justify your choice.
Remember to comment on at least two other students’ posts by providing constructive feedback.

Refer to the Attendance and Participation section of the Syllabus for requirements related to original posts and replies/comments.

All posts due no later than Sunday, November 22nd 11:55 p.m.

Detailed Learning Objectives
OBJECTIVE 1: Know the Core Concepts of Research

Two types of research: quantitative and qualitative
The five steps of the research process
Initial Observation
Generate Theory
Generate Hypotheses
Collect Data to Test Theory
Analyze Data (and report findings)
Variables
Types: independent and dependent
The levels of measurement: nominal, ordinal, interval, ratio
Hypotheses
Types of hypotheses: Alternative (H1) and Null (H0)
Two types of alternative hypotheses: directional (i.e. one-tailed) and non-directional (i.e. two-tailed)
OBJECTIVE 2: Correlation and Regression

Understand the theoretical foundations behind Correlation and Regression tests
Know when it is most appropriate to run Correlation and Regression tests
Have a basic understanding on interpreting effect size
Know how to run these tests in Excel and interpret the results (e.g. strength and direction of correlation, statistical significance)
OBJECTIVE 3: Independent Samples T-Test and ANOVA

Understand the theoretical foundations behind the Independent Samples T-Test and ANOVA tests
Know when it is most appropriate to run these tests
Have a basic understanding on interpreting effect size
Know how to run these tests in Excel and interpret the results
OBJECTIVE 4: Chi-Square Test

Know how to build 2×2 contingency tables
Be able to use the data from these contingency tables to calculate expected counts when the number of respondents in each category is different
Know how to run the Chi-Square test in Excel and interpret the descriptive results, as well as report the chi-square test statistics.
Be able to calculate and interpret odds ratios.

Module Overview

In this module, you will learn about the core concepts of research. Specifically, you will learn the foundations for what you need to know to better understand the more complex inferential statistical tests that include: Correlation; Regression; T-Test, ANOVA, and Chi-Square. Importantly, for each of these statistical tests, you will learn the theoretical foundations, understand the types of hypotheses that can be tested using these tests, the characteristics of the variables (i.e. levels of measurement, normality of distribution) and how these tests can be used to examine hypotheses and test proposed relationships.

Note that the Correlation and Regression tests measure similarities that are shared between two or more variables, while the T-test and ANOVA allow researchers to study the differences between groups of subjects. Very often, researchers run into variables that are categorical (i.e. nominal) in nature. In the latter case, the Chi-square test is the most suitable test to use to examine the relationships between these variables.