Assignment 2: Testing for Correlation by Linear Regression The goal of many studies is to determine if there is a relationship between factors. In other words, does one factor influence the outcome of another factor? If there is a relationship between the factors, then there is a correlation. Through this modules lectures and readings, you will know that findinga correlation does not necessarily mean that you have found a causal relationship. This would need to be determined by another layer of investigation. Indeed, many times correlation does not always lead to the determination of causation, but it can help to identify if there is not a causal relationship between the variables in the study. One way to determine correlation is to see if there is a linear relationship between the factors. A linear relationship can be tested by graphing a scatter plot of the data in the study and seeing if a best-fit line can be drawn to represent this data. This method of analysis is called . T
he formulas for linear regression are cumbersome, but luckily, most spreadsheets have built-in functions for performing these tedious calculations. In this assignment, you will use a spreadsheet to examine pairs of variables, using the method of linear regressions, to determine if there is any correlation between the variables. Afterwards, postulate whether this correlation reveals a causal relationshipwhy or why not? to open the Excel spreadsheet containing the data for this assignment. Notice that there are several tabs on the spreadsheet, each containing a different set of data from different studies. On each of these sample tabs, you will also find the question that was explored in that study. Select the data set that you find interesting, and perform the analysis below. You are only required to perform this analysis on one set of data. There is a tab labeled where you can see how your analysis should look when done. In the Excel spreadsheet, perform the following operations: