For this assignment, utilize the "fwi," "chick," and "mf" objects from the "Beginning.RData" data set. Complete the assignment by executing the following steps. Include relevant details for each model for all steps.
1. For each data object, demonstrate the relation that holds for each variable in the object by creating pair-wise scatter plots. Provide a screenshot of the results in a Word document. Provide a short discussion on the interpretation of the results for "fwi," "chick," and "mf."
2. Perform a multiple regression analysis on the "mf" object only. Assume that Length is the response variable (i.e., y variable) and that the rest of the variables are the predictor (i.e., x variables). Use the Summary command to generate the results. Provide a screenshot of the results in a Word document.
3. Using the confint() command, obtain confidence interval results for the predictor variables. Provide a screenshot of the results in a Word document.
4. Revise the multiple regression model that you ran in step 2. Include only the predictor variables that were statistically significant at 0.1 in step 2. Provide a screenshot of the results in a Word document. Summarize your results.
5. Discuss which model should be used and justify the selection of that model.
Multiple Regression in R The purpose of this assignment is to create and visualize regression models graphically. For this assignment, utilize the "fwi," "chick," and "mf" objects from the "Beginning.RData" data set. Complete the assignment by executing the following steps. Include relevant details for each model for all steps. 1. For each data object, demonstrate the relation that holds for each variable in the object by creating pair-wise scatter plots. Provide a screenshot of the results in a Word document. Provide a short discussion on the interpretation of the results for "fwi," "chick," and "mf." 2. Perform a multiple regression analysis on the "mf" object only. Assume that Length is the response variable (i.e., y variable) and that the rest of the variables are the predictor (i.e., x variables). Use the Summary command to generate the results. Provide a screenshot of the results in a Word document. 3. Using the confint() command, obtain confidence interval results for the predictor variables. Provide a screenshot of the results in a Word document. 4. Revise the multiple regression model that you ran in step 2. Include only the predictor variables that were statistically significant at 0.1 in step 2. Provide a screenshot of the results in a Word document. Summarize your results. 5. Discuss which model should be used and justify the selection of that model.