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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
CINSFG5121289189a. 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.