In a clinical trial, 19 out of 800 patients taking a prescription drug complained of flulike symptoms. Suppose that it is known that 2.9% of patients taking competing drugs complain of flulike symptoms. Is this sufficient evidence to conclude that less than 2.9% of this drug's users experience flu-like symptoms as a side effect? (Let α=0.05) Ho:        HA:          Z-stat =          Round to 2 decimal places. p-value =          Decision:         Type either Reject Ho or Retain Ho

4. A simple linear regression is fit to a dataset. Unfortunately, the corresponding ANOVA table is not complete because some quantities in the table are missing due to unknown digital errors. Calculate the missing values, denoted by "?", in the ANOVA table based on the other available values. Is this regression model significant (α = 0.05)? Source Regression Residual Total df ? ? 21 SS ? ? ? MS = SS/df ? 1.13 F-Ratio 430.65 p-value ?

The beta of a stock has been estimated as 1.4 using regression analysis on a sample of historical returns. A commonly-used adjustment technique would provide an adjusted beta of A. 1.32. B. 1.13. C. 1.0. D. 1.27.

A study is conducted to determine factors in solving missing persons cases. The outcome is Y; which is equal to 1 if the i-th missing person case is unsolved and 0 if it is solved. Let covariate X1; be an indicator equal to 1 if the i-th case is female and 0 for male. Let X2i be a categorical covariate of age group for the i-th case. Categories are less than 14 years old (base level/group), between 14 and 19 years old, and older than 19 years. Set u = P(Y = 1) and the following model is fit: logit(u) = Bo + BịI(Female) + B2I(14 to 19 yrs old) + B3I(> 19 yrs old) The output from the model is below: Estimate S.E. p-value Bo -4.565 0.128 0.380 0.087 B2 Вз -0.198 0.042 0.163 1.128 0.133 a. Using the logistic regression output, calculate the estimated odds ratio of a case being unsolved (again Y=1 is unsolved and Y=0 is solved) comparing females to males (female is the numerator odds) of the same age. Interpret this odds ratio in context of the problem. iii b. Create a 95% confidence…