1.0- ! 0.8- 8 8 Chance.of.Admit 0.6- 8 : 8 0.4- 290 310 320 330 340 GRE. Score 300 Confidence Level for Slope and Interc
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1.0- ! 0.8- 8 8 Chance.of.Admit 0.6- 8 : 8 0.4- 290 310 320 330 340 GRE. Score 300 Confidence Level for Slope and Interc
8. Is the linearity condition met? Yes, the residual plot is normal. Yes, there is no megaphone pattern found in the scatterplot Yes, the scatterplot shows a linear pattern in the data Yes, there is no megaphone pattern in the residual plot. 9. Select "Proceed to Regression Analysis". Refer to the table. If we perform at test for the slope of the regression line, what is the test statistic and p-value for this procedure? t = -20.68, p-value = -2.67 t = 26.84, p-value = 0.00 t = 26.84, p-value = 0.01 t = -20.68, p-value = 0.00 10. Calculate a 95% confidence interval for the slope on the line. Assuming that a = 0.05, can we use this interval as evidence that there is a linear relationship between GRE score and chance of admission? No. We don't know the alternative hypothesis, so we cannot make a conclusion on the relationship between GRE score and chance of admission. Yes. Because our alternative hypothesis is one-sided and O is not found in the confidence interval, we reject the null hypothesis and conclude that there is a linear relationship between GRE score and chance of admission. No. Confidence intervals cannot be used to make conclusions for hypothesis tests. Yes. Because our alternative hypothesis is two-sided and O is not found in the confidence interval, we reject the null hypothesis and conclude that there is a linear relationship between GRE score and chance of admission.