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# Away Home Runs Margin Hits Errors Pitchers Walks Time TEX CHW 10 10 20 2 5 5 184 CLE DET 15 1 24 0 11 10 225 BOS KCR 7 5 13 1 8 7 213 BAL LAA 8 6 20

AwayHomeRunsMarginHitsErrorsPitchersWalksTime

TEXCHW101020255184

CLEDET1512401110225

BOSKCR7513187213

BALLAA8620455155

NYYMIN3313298187

TOROAK115044158

SEATBR15122276182

ARIATL1110157153

STLCHC8421184162

LADCOL8211167187

SFGHOU1022011210234

MILNYM8417183174

CINPIT9114087173

FLASDP7115086162

PHIWSN 91200103193

TBRBAL7714168167

OAKCHW122251117190

SEADET5114074173

KCRLAA6216056161

TEXMIN12621264187

CLENYY1842411016212

BOSTOR6415375183

LADCOL11125365171

ARIFLA10222094171

ATLHOU157242106180

STLMIL8817055154

CHCPHI122181811189

NYMPIT9722273162

WSNSDP318178164

CINSFG5121289189**a. **Create a scatterplot with time on the X-axis and runs on the Y-axis. Copy + paste your graph below.

**b. **Describe the scatterplot that you made in part (a) in terms of direction, shape, strength, and outliers.

** i. **Direction:

** ii. **Shape:

** iii. **Strength:

** iv. **Outliers:

**c. **Use the five-step hypothesis testing procedure outlined below to determine if there is a statistically significant **relationship **between time and runs. (Use Pearson's r and Minitab Express). Show all relevant output and clearly identify your answers for credit!

**d. **Use the five-step hypothesis testing procedure outlined below to determine if **time is a statistically significant predictor of runs**. In other words, test for the significance of the slope in the simple linear regression model. Use Minitab Express and include all relevant output for credit. Remember to check all the assumptions and clearly identify your answers from the output!

**e. **Use the five-step hypothesis testing procedure outlined below to determine if **runs is a statistically significant predictor** of time. All assumptions have been met. Include all relevant output below for credit.

**f. **How was the regression model impacted when the X and Y variables were switched? Compare the slope, y-intercept, p-values, and r-squared values for the models you tested in parts d and e.