survey was conducted and asked, " Do you consider your health to be poor?" This was coded as 1 for "yes" and 0 for "no". The effect of age (in years) and sex (1=male, 0=female) on the outcome was examined using logistic regression. The fitted logistic model is:   logit(p-hat) = -0.544 + Beta * sex + 0.0331*age

What is the mathematical representation for the multiple logistic regression model in photo?

The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis.   Rat Number Initial Weight (gms) Weight Gain (gms) 1 50 128 2 64 159 3 76 158 4 64 119 5 74 133 6 60 112 7 69 96 8 68 126 9 56 132 10 48 118 11 57 107 12 59 106 13 46 82 14 45 103 15 65 104 I used excel's regression took pak and got the following:  SUMMARY OUTPUT                                 Regression Statistics               Multiple R 0.489416452               R Square 0.239528464               Adjusted R Square 0.181030653               Standard Error 8.869929833               Observations 15…

Your company just became international by offering Its products in both the United States and Canada. Experts in your analytics department belleve that tastes for your product differ In those two countries, and have carefully collected data on prices and quantity demanded in both countries. They then present you with the results of two regressions, one for each country, as follows: Log Price regressed on Log Quantity (United States): Standard Error 10.81051303 Coefficients t stat P-value Intercept Log Quantity Lower 95% 31.48708283 -7.685279168 Upper 95% 74.0239705 52.75573994 4.88040363 -4.597932039 1.67605E-06 6.15253E-06 -5.382266173 1.17e5841es -3.079253177 Log Price regressed on Log Quantity (Canada): Standard Error 10.64507785 Coefficients Intercept Log Quantity 22.8707593 -2.09578827s t stat 2.148482109 -1.818112644 0.069981782 P-value 0.0324256e3 Lower 95% 1.9275se2 upper 95% 43.8139384 0.17209336 1.152727409 -4.363669916 Assume you have adequate statistical significance for…

An investigator modeled the log-odds of getting stomach cancer as a function of number of servings of vegetables per week and the number of servings of red mean per week using logistic regression. The odds that a person gets stomach cancer if they have 4 servings of red meat a week are 1.2 times the odds of cancer for someone who has 3 servings of red meat a week.  Suppose the fitted regression model is given as log-odds = -6 + 0.182 M – 0.105 V, where M = #servings of red meat per week and V = #servings of vegetables per week. What is the odds ratio representing the change in odds for an increase in one serving of vegetables? Give the answer to three decimal places.

1 Acup of soup is left on a countertop to cool. The cable below gives the temperatures, in degrees Fahrenheit, of the soup recorded over a 10-minute period. Time in Minutes () Temperature in F() 180.2 165.8 146.3 135.4 127.7 110.5 2. 8. 10 Write an exponential regression equation for the data, rounding all values to the nearest thousandth.

Table 4.8 shows results of an eight-center clinical trial to compare a drug to placebo for curing an infection. At each center, subjects were randomly assigned to treatments. Analyze these data, available in the Infection data file at the text website. Using logistic regression, describe and make inference about the treatment effect.

Calculate the estimate of σε​ What is the estimated resting heart rate for someone who is a smoker (Smoke=1) and exercises 1 hour a day (Exercise=1)?

For the 23 space shuttle flights before the Challenger mission disaster in 1986, The following table shows the temperature (◦F) at the time of the flight and whether at least one primary O-ring suffered thermal distress. Use logistic regression to model the effect of temperature on the probability of thermal distress. Interpret the effect. Estimate the probability of thermal distress at 31◦F, the temperature at the time of the Challenger flight. At what temperature does the estimated probability equal 0.50? At that temperature, give a linear approximation for the change in the estimated probability per degree increase in temperature. Interpret the effect of temperature on the odds of thermal distress. Test the hypothesis that temperature has no effect, using (i) the Wald test, (ii) the likelihood-ratio test.

Listed below are systolic blood pressure measurements​ (in mm​ Hg) obtained from the same woman. Find the regression​ equation, letting the right arm blood pressure be the predictor​ (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a signicance level of 0.05.  Right Arm  102      101     93     76       77 Left Arm      177      170    147   148      148