Question Completion Status: QUESTION 13 2 points Suppose we used ANOVA methods to test there are differences in the mean

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Question Completion Status Question 13 2 Points Suppose We Used Anova Methods To Test There Are Differences In The Mean 1 (31.18 KiB) Viewed 21 times

Question Completion Status Question 13 2 Points Suppose We Used Anova Methods To Test There Are Differences In The Mean 2 (30.37 KiB) Viewed 21 times

Question Completion Status Question 13 2 Points Suppose We Used Anova Methods To Test There Are Differences In The Mean 3 (29.89 KiB) Viewed 21 times

Question Completion Status: QUESTION 13 2 points Suppose we used ANOVA methods to test there are differences in the means of four populations. Then there would have been up to six po pairs of means to compare If we choose to testo pows, how can we make sure our over probability of a false rejection is belowa 0052 O Assume there will be no falso rections since x tesis is not too many Perform only the three toss that will have the largest statistic Use an appropriate multiple comparisons procedure QUESTION 14 2 points SA The following ANOVA table was obtained from a completely randomized designed experiment Source DF 5S MS F GODS 3 90 30 923 Error 15 325 Total 19 162 What is the ul hypothesis for this experiment OT2 2014 OUT= 2415 12 Sendimit ANO

QUESTION 15 Which of the following affects alpha? The p-value of the test The sample size The number of Type I errors OA All of the above OB. None of the above QUESTION 16 Which of the following statements is true? The correlation coefficient will be 10 only if all the data lie on a perfectly horizontal straight line The correlation coefficient equals the proportion of times two variables lie on a straight line The correlation coefficient is a unitiess number and must always to between 10 and 10 The correlation coefficient measures the fraction of outfiors that appear in a scattorplot

QUESTION 17 2 poi The residual plots (residuals versus predicted values, and also residuals versus time, if applicable) for regression models are important because they help to O a identity lack of fit of the model evaluate normality of the residuals display nonconstant variance display correlated errors 2 point QUESTION 18 Regression model diagnostics might include checking for which of the following? A Error fit B. model assumptions (independent normal errors with constant variance) C influential observations