Reference no: EM131796416

T test

When we report the outcome of a t test, we present the following:
- Group I - M, SD
- Group II - M, SD
- t statistic with its df
- p

2. Why do we need to report ALL four of the above to provide the WHOLE picture? Explain.

Explain each one's contribution to the WHOLE picture.

Learning Outcomes

Upon successful completion of this module, the student will be able to satisfy the following outcomes:

- Case
o Choose a t test when appropriate per the study hypotheses and variables' level of measurement.
o Review, conduct, and interpret statistical t tests.

- SLP
o Implement within a "real-world" project: The definition of research questions and their derivative hypotheses; Examine data; perform appropriate statistical test: t test, ANOVA/ANCOVA, Chi Square; interpret and report results.

- Discussion
o Explain the relevance of reporting the various outputs of the outcome of a t test.

Module Overview

1. We will now begin to look at Inferential statistical procedures which utilize research data sampled from a study population to make inferences about that particular study population.

2. Inferential statistics generally come from the family of statistical models known as the General Linear Model.

3. The statistical methods used frequently in research are the t-test (Module 3), ANOVA/ ANCOVA (Module 4), and MANOVA/MANCOVA, regression analysis, factor analysis covered in the following course of RMS618).

4. In this module we will focus on: The t test.

5. The t test compares the means of two sample nominal categories (sub-groups) on a continuous dependent variable. For example: the academic scores (DV) of students based on their Gender (IV): females and males.

6. The t test statistic and its level of significance (p value) allows us to decide whether the difference between subgroup A and subgroup B is statistically significant, and consequently decide on our null hypothesis.

7. It is recommended that you FIRST view the modular Case and SLP assignments, and see what is required of you to do. With this in mind, review the Background page for reading and support materials.
T-Test - 95% CI

- When reporting a t test of independence, we will also report the CI 95% of the difference between the Means.

- For example, I have examined exam scores in Spanish across students' religion. The report should be as follows:

An independent samples t test was run to examine differences in Spanish scores across students' religion, yielding a non- significant statistical difference with: Christians M=79.65 (15.465), and Moslems M=80.18 (14.015), t(623.55)=-.595, p= .552 . The 95% CI of the difference of the means -.538 was (-2.314, 1.238).

Research Question & Hypothesis

RQ: Is there a difference in students' academic achievement between males and females?

Hypothesis:
H_o: There is no statistical significant difference in academic achievement between males and females.
H_a: There is a statistical significant difference in academic achievement between males and females.

Question: What Statistical test is used to test this hypothesis?
Question: What are the IV and the DV in the hypothesis above?

Attachment:- Assignment Background.rar