Required information Lab Note: The tools presented in this lab periodically change. Updated instructions, if applicable, can be found in the eBook and lab walkthrough videos in Connect. Case Summary: After running diagnostic analysis on Dillard's transactions, you have found that there is a statistically significant difference between the amount of money customers spend in online transactions versus in-person transactions. You decide to take this a step further and design a predictive model to help determine how much a customer will spend based on the transaction type (online or in-person). You will run a simple regression to create a predictive model using one explanatory variable in Part 1 , and in Part 2 you will extend your analysis to add in an additional explanatory variabletender type (the method of payment the customer chooses). Data: Dillard's sales data are available only on the University of Arkansas Remote Desktop See your instructor for login credentials. ote: Submit your answers for the following Analysis Questions in the text entry field below. Q1. How would you interpret the results of your analysis of Q1 in plain English? What does it imply to have both a very low R Square value and a very low gnificance F value or p-value? \begin{tabular}{|c|c|c|c|c|c|c|c|c|} \hline SUMMARY OUTPUT & & & & & & & & \\ \hline \multicolumn{9}{|c|}{ Regression Statistics } \\ \hline Multiple R & 0.093420397 & & & & & & & \\ \hline R Square & 0.008727371 & & & & & & & \\ \hline Adjusted R Square & 0.008725632 & & & & & & & \\ \hline Standard Error & 38.68813696 & & & & & & & \\ \hline Observations & 570060 & & & & & & & \\ \hline \multicolumn{9}{|l|}{ ANOVA } \\ \hline & df & SS & MS & F & Significance F & & & \\ \hline Regression & 1 & 7512162.621 & 7512162.621 & 5018.909303 & 0 & & & \\ \hline Residual & 570058 & 853246819.3 & 1496.771941 & & & & & \\ \hline \multirow[t]{2}{*}{ Total } & 570059 & 860758982 & & & & & & \\ \hline & Coefficients & Standard Error & t Stat & P-value & Lower 95\% & Upper 95% & Lower 95.0% & Upper 95.0% \\ \hline Intercept & 23.71511553 & 0.052785405 & 449.2741051 & 0 & 23.61165782 & 23.81857324 & 23.61165782 & 23.81857324 \\ \hline 0 & 15.57323951 & 0.219823586 & 70.8442609 & 0 & 15.14239228 & 16.00408673 & 15.14239228 & 16.00408673 \\ \hline \end{tabular}