Hypotheses for Significance Difference and Correlational Statistical Tests

Statistically significant difference is usually a comparison between two dichotomous groups within a sample or between two samples. Correlations are tests of the statistically significant strength of relationship between two dependent variables.
In this assignment, you will compose hypotheses for significance difference and correlational statistical tests.
Note: Scholarly references are not required for this assignment.
Step 1. Evaluate
First, evaluate the variables in the Sample Dataset you created in Module 4 and are using for the remainder of the course. Choose two variables you could compare for statistically significant difference. Consider comparing groups on some observed value.
Note: this would be two measures, not one measure between two groups.
Step 2. Compose
Compose a hypothesis for a statistically significant difference test using the following format:
There is a statistically significant difference in ____ between ____ and _ _ _.
Compose a hypothesis for a statistically significant correlation test using the following format:
There is a statistically significant relationship between ____ and _ __.
Compose null and alternative hypotheses from both statements in the previous step:
H0: There is no statistically significant…
H1: There is a statistically significant…
Clearly label the null and alternative hypotheses for both the significant difference and correlational tests.
Step 3. Reflect
In a few paragraphs, respond to the following prompts:
Consider why a null hypothesis is necessary and under what conditions is it rejected.
Explain why a null hypothesis is necessary when conducting research with applied statistics.
Consider how to report the findings if the null hypothesis could or could not be rejected in each case. What would it mean in real terms regarding the differences, or relationship, between the groups?