Variable Intercept x1 X2 Variable a. At the 5% significance level, comment on the significance of the variables for both models. x₁ X2 LPM -0.30 (0.03) 0.27 (0.06) -0.05 (0.02) x₁ = 10, x₂ = 14 x₁ = 10, X₂ = 25 Logistic -2.50 (0.03) 1.03 (0.07) -0.30 (0.01) x₁ = 10, X₂ = 14 x₁ = 10, x₂ = 25 LPM Not significant Significant b. What is the predicted probability implied by the linear probability model for x₁ = 10 with x2 equal to 14 and 25? Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). ý Logistic Not significant Significant What is the predicted probability implied by the logistic model for x₁ = 10 with x2 equ to 14 and 25? Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). у

Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C

Table 4.18 shows estimated effects for a fitted logistic regression model with squamous cell esophageal cancer (1 = yes, 0 = no) as the response variable Y. Smoking status (S) equals 1 for at least one pack per day and 0 other- wise, alcohol consumption (A) equals the average number of alcoholic drinks consumed per day, and race (R) equals 1 for blacks and 0 for whites. A. To describe the race-by-smoking interaction, construct the prediction equation when R = 1 and again when R = 0. Find the fitted YS conditional odds ratio for each case. Similarly, construct the prediction equation when S = 1 and again when S = 0. Find the fitted YR conditional odds ratio for each case. Note that, for each association, the coefficient of the cross-product term is the difference between the log odds ratios at the two fixed levels for the other variable. B. In Table 4.18, explain what the coefficients of R and S represent, for the coding as given above. What hypotheses do the P -values refer to for…

A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam Scores (y). The results of the regression were: y=ax+b a=6.179 b=28.96 r²=0.937024 r=0.968 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.