The table below contains ratings for food, décor, service, cost per person, and

Question

The table below contains ratings for food, décor, service, cost per person, and popularity index for various types of restaurants in a large city. You want to study differences in the cost of a meal for the different types of cuisines and also want to be able to predict the cost of a meal based on the ratings.

Find the test statistic.

FSTAT=______

(Round to two decimal places as needed.)

Find the p-value.

p-value=________

(Round to three decimal places as needed.)

Cuisine Food Décor Service Cost Popularity American 32 25 27 72 85 American 27 28 27 68 94 American 27 23 26 72 83 American 33 28 30 77 92 American 27 25 25 69 82 American 27 26 27 81 100 American 30 23 28 58 77 American 26 29 25 73 53 American 26 24 24 81 62 American 26 23 27 78 72 Japanese 33 22 24 86 90 Japanese 28 19 25 127 54 Japanese 27 15 21 87 59 Japanese 32 27 28 61 70 Japanese 26 27 23 83 57 Japanese 26 23 23 90 57 Japanese 31 23 26 83 57 Japanese 25 23 22 58 33 Japanese 25 18 22 69 33 Japanese 24 26 26 84 45 Indian 28 24 23 58 56 Indian 24 21 22 48 58 Indian 23 19 21 66 32 Indian 28 19 26 50 29 Indian 23 28 23 71 38 Indian 22 17 19 68 23 Indian 25 19 22 43 37 Indian 21 22 18 36 27 Indian 21 22 20 65 61 Indian 21 16 20 36 27 Italian 31 24 23 58 99 Italian 24 30 22 48 94 Italian 23 19 21 46 77 Italian 34 19 29 50 78 Italian 23 27 23 71 79 Italian 22 17 19 69 79 Italian 35 19 25 43 57 Italian 21 24 18 36 68 Italian 21 22 20 90 53 Italian 21 16 28 36 56 Use technology to find the multiple regression equation. Assume that x, corresponds to the food rating, x2 corresponds to the decor rating. x3 corresponds to the service rating, and x4 corresponds to the popularity rating of the restaurant y=0+0x1 + 0x2 +0x3 + Ox4 (Round to two decimal places as needed.)

Explanation / Answer

from above below is regression output:

yhat =25.86+0.54x1+0.66*x2+0.46x3+0.01*x4

Fstat =0.60

p value =0.665

Regression Statistics Multiple R 0.2533 R Square 0.0641 Adjusted R Square -0.0428 Standard Error 19.3731 Observations 40.0000 ANOVA df SS MS F Significance F Regression 4 900.2719 225.0680 0.5997 0.6653 Residual 35 13136.1031 375.3172 Total 39 14036.3750 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 25.8582 27.7798 0.9308 0.3583 -30.5377 82.2542 Food 0.5436 1.1101 0.4897 0.6274 -1.7101 2.7973 Décor 0.6565 0.9015 0.7282 0.4713 -1.1737 2.4867 Service 0.4588 1.4358 0.3195 0.7512 -2.4561 3.3736 Popularity 0.0057 0.1734 0.0326 0.9742 -0.3464 0.3577

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