Regression and Correlation Analysis & ANOVAOverview and Rationale This assignment is designed to provide you with hands-on experiences in performing regressions and correlation analysis. The data set

Regression and Correlation Analysis & ANOVA

Overview and Rationale This assignment is designed to provide you with hands-on experiences in performing regressions and correlation analysis. The data set is provided in an Excel workbook and contains a wide range to data types that you will need to work with.

Course Outcomes

This assignment is directly linked to the following key learning outcomes from the course syllabus:

CO1: Explore the use of statistical software in data analysis through hands-on applications

CO5: Conduct regression and chi-squared test of independency to study associations between numerical and categorical variables respectively; and justify the legitimacy of the regression model.

Assignment Summary

Using the data provided in the attached Excel workbook, apply regression and correlation analysis on two data sets.

Follow the instructions in this project document to analyze the data presented in the Excel workbook. Then complete a report summarizing the results in your Excel workbook (or R script file). Submit both the report and the Excel workbook (or R script file).

Project Description

Using the Data worksheet found in the Module 6 Project_ US Occupations.xlsx Excel workbook, complete the following analyses’ regarding US occupation data. Place the results in the worksheet specific in each part of the assignment.

In some parts of this project, you are asked to create random samples from a given population. Random sampling methods have been covered in Module 3, and tutorials are available in the Instructor Perspective folder in your Blackboard course page.

Part 1 (Q1)

The location quotients are given for NY (population 1) and LA (population2) in columns B and D, respectively, of worksheet Q1. The location quotient (LOC_QUOTIENT) represents the ratio of an occupation’s share of employment in a given area to that occupation’s share of employment in the U.S. as a whole. For example, an occupation that makes up 10 percent of employment in a specific metropolitan area compared with 2 percent of U.S. employment would have a location quotient of 5 for the area in question.

1. Use the random sampling method explained in the Instructor Perspective of Module 3 to draw a random sample of 350 from the NY LOC QUOTIENTs and a random sample of size 350 from the LA LOC QUOTIENTs.

2. Copy your samples into columns F and G of worksheet Q1.

3. Standardize both sets samples of LOC QUOTIENTs and display the standardized values (