Week 7 Test

Part A of question one asks for the variance (sigma squared), not the equation of regression line. Is the variance 2.79 as I listed on my answer sheet? Maybe my image didn't go through, but I already had the answer to subparts B and C to the question, which you list as #2 and #3. But I need help with parts D, E, and F. I have the following answers for D.  d. Y hat (fitted value = 426.46), with residual of -1.62. e. r squared value = 1.00 g. 99% confidence interval = (-11.63, -1.05) Thanks thanks

Which of the following is not a plot of residuals typically used in multiple regression analysis?Select one:a. None of these b. Residuals versus correlation coefficients..c. Residuals versus X1.d. Residuals versus timee. Residuals versus X2.

Which of the following are correct statements for linear regression? 1. If the scatter plot of the residual and the predicted response of a linear regression model shows a relationship between the two, then the model is good.  2. Linear regression is not sensitive to outliers.  3. LASSO could be used for variable selection.  4. If the Pearson's correlation coefficient between feature X1 and response Y is small, then there is weak evidence of correlation between X1 and Y.  5. If one uses a large penalty in ridge regression, then the bias in the model is high.  6. If the training data size is increased, then the bian and variance of the model increase.  7. One can use a maximum likelihood estimator in the case of linear regression under the assumption that the errors are independent and identically distributed.

A manager wishes to find out whether there is a relationship between the age of his employees and the number of sick days they take each year. The data for the sample follow. If the first letter of your last name starts with A to M, use level of significance 0.05, otherwise, if the first letter of your last name starts with N to Z, use level of significance 0.01.  a. Draw/sketch a SCATTER PLOT with regression line and regression equation. b. State the null and alternative hypotheses. Ho (Null Hypothesis): Ha ( Alternative Hypothesis) c. Level of Significance  d.  Determine the degrees of freedom (df) and t critical value. e.  Correlation coefficient (Pearson r). f.   t statistic g. Compute the slope of regression line. h. Compute the mean of x and y i. Compute the intercept of regression line. j. Write the regression equation k. Write the complete interpretation of the results and conclusion.

Suppose you are conducting an experiment, and you have 8 different treatments you are testing on lab mice.  Assume that the outcome is a continuous random variable, and your main research question is whether or not the distribution of the outcome differs across treatment groups.  You notice that the within group standard deviations differ greatly from one group to the next.  Which of the following analytical approaches would be advisable to take in this situation?   Question 23 options:   Conduct a simple linear regression between the outcome and the treatment group assignment.   Conduct an ANOVA followed by post-hoc Bonferroni adjustment.   Conduct a Kruskal-Wallis test   Calculate within-group Spearman correlations.

Which of the following is not a plot of residuals typically used in multiple regression analysis? Select one: None of these  Residuals versus correlation coefficients Residuals versus X1 Residuals versus time Residuals versus X2.

The value of the sample correlation coefficient R, for these data is approximately 0.712. Answer the following, carrier, intermediate, computations to at least four decimal places, and rounder answers as specified below.a. What is the value of the slope of the least squares regression line for these data? round your answer to at least two decimal places. b. What is the value of the y-intercept of the least squares regression line for these data? Round your answer to at least two decimal places.