Exam 27: Multiple Regression

What is the regression equation?

What is the regression equation?

From this model,what is the predicted calorie content of a serving of breakfast cereal which contains 10 g of protein,3 g of fat,6 g of fibre,14 g of carbohydrates,and 2 g of sugar?

How much of the variation in bear measurements is explained by the model?

A visitor to Yellowstone National Park in Wyoming,Idaho,U.S.A.,sat down one day and observed Old Faithful,which faithfully erupts throughout the day,day in and day out.He surmised that the height of a given eruption was caused by the pressure buildup during the interval between eruptions and by the momentum buildup during the duration of the eruption.He wrote down the data to test his hypothesis,but he didn't know what to do with his data. Height Interval Duration 150 86 240 154 86 237 140 62 122 140 104 267 160 62 113 140 95 258 150 79 232 150 62 105 160 94 276 155 79 248 125 86 243 136 85 241 140 86 214 155 58 114 130 89 272 125 79 227 125 83 237 139 82 238 125 84 203 140 82 270 140 82 270 140 78 218 135 87 270 140 70 241 100 56 102 105 81 271

Interpret the R-squared value of 95.8%.

Interpret the R-squared value of 84.5%.

Use the following computer data,which refers to bear measurements,to answer the question. Dependent variable is Weight S = 32.49 R-Sq = 96.9% R-Sq (adj)= 94.6% Predictor Coef SE Coef T P Constant -285.21 78.45 -3.64 0.022 Age -1.3838 0.9022 -1.53 0.200 Head Width -11.24 20.88 -0.54 0.619 Neck 28.594 5.870 4.87 0.007 Analysis of Variance Source DF SS MS F P Regression 3 132425 44142 41.81 0.002 Residual Error 4 4223 1056 Total 7 136648 -Which measurement is the worst predictor of calorie content,after allowing for the linear effects of the other variables in the model?

A health specialist gathered the data in the table to see if pulse rates can be explained by exercise,smoking,and age.For exercise,he assigns 1 for yes,2 for no.For smoking,he assigns 1 for yes,2 for no. Pulse Exercise Smoke Age 97 2 2 19 88 1 2 28 69 1 2 19 67 1 2 20 83 1 2 18 77 1 2 17 66 2 2 18 78 2 2 19 73 1 1 17 67 1 1 18 55 1 2 19 82 1 1 24 70 1 2 30 55 1 2 24 76 1 2 19

Every extra metre of the length adds 5.2 kg to the average weight.

What does the coefficient of neck mean?

Every extra centimetre of the chest adds 2.2 kg to the average weight,for a given length and sex.

Use the following computer data,which refers to bear measurements,to answer the question. Dependent variable is Weight S = 32.49 R-Sq = 96.9% R-Sq (adj)= 94.6% Predictor Coef SE Coef T P Constant -285.21 78.45 -3.64 0.022 Age -1.3838 0.9022 -1.53 0.200 Head Width -11.24 20.88 -0.54 0.619 Neck 28.594 5.870 4.87 0.007 Analysis of Variance Source DF SS MS F P Regression 3 132425 44142 41.81 0.002 Residual Error 4 4223 1056 Total 7 136648 -Which measurement is the best predictor of weight,after allowing for the linear effects of the other variables in the model?

From this model,what is the predicted salary of a secretary with 2.5 years (30 months)experience,10th grade education (10 years of education),an 80 on the standardized test,45 wpm typing speed,and the ability to take 30 wpm dictation?

Use the following computer data,which refers to bear measurements,to answer the question. Dependent variable is Weight S = 32.49 R-Sq = 96.9% R-Sq (adj)= 94.6% Predictor Coef SE Coef T P Constant -285.21 78.45 -3.64 0.022 Age -1.3838 0.9022 -1.53 0.200 Head Width -11.24 20.88 -0.54 0.619 Neck 28.594 5.870 4.87 0.007 Analysis of Variance Source DF SS MS F P Regression 3 132425 44142 41.81 0.002 Residual Error 4 4223 1056 Total 7 136648 -Which measurement is the best predictor of salary,after allowing for the linear effects of the other variables in the model?

Every extra kilogram of weight means an increase of 5.2 metres in length.

An anti-smoking group used data in the table to relate the carbon monoxide output of various brands of cigarettes to their tar and nicotine content. CO Tar Nicotine 15 1.2 16 15 1.2 16 17 1.0 16 6 0.8 9 1 0.1 1 8 0.8 8 10 0.8 10 17 1.0 16 15 1.2 15 11 0.7 9 18 1.4 18 16 1.0 15 10 0.8 9 7 0.5 5 18 1.1 16

Use the following computer data,which refers to bear measurements,to answer the question. Dependent variable is Weight S = 32.49 R-Sq = 96.9% R-Sq (adj)= 94.6% Predictor Coef SE Coef T P Constant -285.21 78.45 -3.64 0.022 Age -1.3838 0.9022 -1.53 0.200 Head Width -11.24 20.88 -0.54 0.619 Neck 28.594 5.870 4.87 0.007 Analysis of Variance Source DF SS MS F P Regression 3 132425 44142 41.81 0.002 Residual Error 4 4223 1056 Total 7 136648 -Which measurement is the best predictor of calorie content,after allowing for the linear effects of the other variables in the model?

This model fits 96% of the data points exactly.

Use the following computer data,which refers to bear measurements,to answer the question. Dependent variable is Weight S = 32.49 R-Sq = 96.9% R-Sq (adj)= 94.6% Predictor Coef SE Coef T P Constant -285.21 78.45 -3.64 0.022 Age -1.3838 0.9022 -1.53 0.200 Head Width -11.24 20.88 -0.54 0.619 Neck 28.594 5.870 4.87 0.007 Analysis of Variance Source DF SS MS F P Regression 3 132425 44142 41.81 0.002 Residual Error 4 4223 1056 Total 7 136648 -Which measurement is the worst predictor of weight,after allowing for the linear effects of the other variables in the model?