# Psychological Statistics – Generating hypotheses for t-tests and ANOVAs

Please don’t send a handshake if you don’t no Statistics. If you mess over me I will write a two page review discrediting you. I need this no later than tomorrow at 12 in the afternoon.

This for a discussion. Please do not sent it back in an essay form.

Post a null hypothesis that would use a t test statistical analysis. Use the same hypothetical situation taken in the t test hypothesis, and turn it into a null hypothesis using a one-way ANOVA analysis and a two-way ANOVA.

For this assignment, you can choose one research question and modify it to fit each of the statistical tests. If you find it easier, you can choose three different research questions; one for each test.

A useful strategy for this assignment is to first jot down the requirements for each type of test and what each is typically used for. Then you can devise your research question and tailor it to meet the requirements.

Be sure that you understand the difference between independent and dependent samples before you attempt to respond to this assignment. Your text has extensive discussions of both types (dependent samples are also called related samples).

I think you will find the following videos very helpful in understanding the difference between z-tests and t-tests and when to use each of them.

Also, two questions on “ Genenerating  hypotheses for t-tests and Anovas.

This is an example of what the professor is looking for:

T-Test is a comparison of one dependent variable (counterproductive work behavior) across two groups (stress and aggression):

No differences exist in the percentage of male workers that exhibit counterproductive work behavior by levels of stress and aggression in industrial factories in 2013.

One-way ANOVA is a comparison of one dependent variable (counterproductive work behavior) across two or more groups (stress, aggression, and theft):

No differences exist in the percentage of male workers that exhibit counterproductive work behavior between or among levels of stress, aggression, and theft in industrial factories in 2013.

Two-way ANOVA is a comparison of two independent variables and a dependent variable:

No differences exist in the percentage of male workers that exhibit counterproductive work behavior based on levels of stress in industrial factories in 2013.

No differences exist in the percentage of male workers that exhibit counterproductive work behavior based on levels of aggression in industrial factories in 2013.

No interaction occurs between levels of stress and aggression in male workers that result in counterproductive work behavior in industrial factories in 2013.

References