Using how a simple linear regression model is used to predict the response variable and a predictor variable of 1550, P-value of 0.0000 and a T-Statistic of 53.523 what the response variable would be and how?

4. Simple Linear Regression: Predicting the Total Number of Wins using Average Relative Skill A simple linear regression model is used to predict the response variable (the variable we wish to measure) using a predictor variable. For example, in the above scatterplot our response variable is the total number of wins, while our predictor variable is average relative skill. This equation is represented with HY) = Bo + le where Bo represents the total wins and Bl represents the average relative skill. For our F-Test we will call upon the following: 3. PPP H0: B1 = 0. Our null hypothesis says that BI '3 value is equal to 0. Tfthis is true then we will not have a statistically signicant relationship and our graph will show a atline, or no positive or negative correlation. Ha: Bl at 0. The alternative hypothesis says that 31's value is not 0 and thus has statistically signicance. When graphed this will show as a positive or negative correlation Our level of signicance will be at 1% or .01. Please see Table l for values below. As our P-value does not reach our level of signicance at .01 we will reject our null hypothesis. There is indeed a statistical signicance between X and Y and average relative skill can be used to predict the total number of wins in the regular season. Table 1: Hypothesis Test for the Overall FTest Statistic Valu e Test Statistic 53.523 Pval ue 0.0000 I What is the predicted tote\"r number of wins in a regaiar season for a team that has an average relative skill af1550? Round your answer down to the nearest integer. - What is the predicted number of wins in a regular season Jfor a team that has an average reiative skiii' of1450? Round your answer down to the nearest integer