Business Statistics

Overview

You have three options for selecting a dataset:

1. the dataset from your Unit 1 discussion,
2. a dataset available from the dataset link, or
3. a dataset from the additional dataset file.

Note: The dataset selected must have at least two quantitative variables.

Complete the following information for the selected dataset.

1. What are the names of the dataset and the two quantitative variables of interest?
2. Create a scatterplot with a simple linear regression. Attach the scatterplot to your post.
3. For the variables selected, run the regression available in the Excel Data Analysis Tools, or use another linear regression method. Share the output.
4. What is the correlation coefficient (r)?
5. Summarize the results.
   • State whether the relation is strong or weak. What evidence supports your assertation?
   • State whether the relation is positive or negative. What evidence supports your assertation?
   • Is this result what you expected?
6. Use the regression analysis output to determine the linear regression (best-fit prediction line) equation and state the equation.
7. Peer Reply 1:Choose a classmate's thread and review the linear regression (prediction line) equation.
   1. Select a value for the independent variable (X) and calculate the predicted value (Y). Be sure to show your work.
   2. Explain why the predicted value does/does not seem reasonable.
   See guidance for calculating a predicted Y value based on a selected X value.
8. Peer Reply 2:Choose another classmate's thread.
   • What is the coefficient of determination, r², for the regression model?
   • Comment on the correlation between the two variables and why you believe the regression equation is a good or poor model for prediction.
   See guidance for calculating the coefficient of determination and deciding if the regression equation is a good or poor model.