Youngstown State University 
MATH 2625 Course Content Page 
Week 12 (4/6 to 4/12) 
The focus of this week is still on Chapter 10: Correlation and Regression. The goals are to learn the basic concepts in analyzing and modeling the correlation between two quantitative variables. You need to know the concept of linear correlation, computing the correlation coefficient, and be able to test statistical hypothesis on zero correlation. You need to know the basic concepts in regression modeling, be able to use SPSS to build basic regression models and interpret the model, be able to test and identify significant factor in the study, be able to model the response variable using quantitative variable, and be able to use SPSS for basic prediction for the response variable using the explanatory variable. All the test and regression modeling procedures can be done by SPSS. You need to be able interpret the SPSS output to conclude the analyses.To Do List:1. Read sections 1, 2, and 3 in chapter 10.2. Download lecture notes and view recorded lecture for chapter 10 (V.41 and V. 42). (The lecture notes are on the right next to video links in the lecture video web page.)3. Try the review exercise problems for sections 1, 2, and 3 for chapter 10 and pay more attention to sections 2 and 3.Assignments: (For details click on the following underscored links.)1. Start CONNECT Homework 9. [Due Wednesday of Week 14]2. Complete Assignment 4: Inference on Mean and Proportion. [Due Wednesday of Week 11 through Blackboard assignment dropbox] Please view SPSS video instructions or text instruction about linear regression using SPSS or R Commander Instructions to learn how to use the software to compute the confidence interval and for testing mean.3. Start Assignment 5: Correlation. [Due Monday of Week 15 through Blackboard Assignment Dropbox] Please view SPSS video instructions or text instruction about linear regression using SPSS or R Commander Instructions to learn how to use the software to compute and perform the chisquare test and the test for zero correlation. 
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