D5 Hypothesis Testing with Two Samples, Linear Regression, and Correlation

Predicting the probability of achieving the desired results often involves the comparison of two groups. For
example, politicians would like to know who is more likely to vote for them, and they will compare the data of
potential voters: younger and older, males and females, urban and rural, and so on. Similarly, employees would
like to know whether their salary depends more on experience or level of education. Hence, hypothesis testing
with two samples may be of great value. In addition, statisticians often make better predictions if they know
whether one variable is related to the other. That is, when comparing two variables and attempting to see
whether there is a relationship between them, analysts will try to determine whether changes made to one
variable trigger corresponding changes in the other variable.
Describe the purpose of scatter diagrams, and discuss how you would determine whether positive, negative, or
no correlation exists between two variables by looking at the scatter diagram.