The data show the chest size and weight of several bears. Find the regression​ equation, letting chest size be the independent​ (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 372 ​pounds? Use a significance level of 0.05.

y = 16.3216X - 330.3904

322 pounds;

Result is significant

Step-by-step explanation:

Given the data:

Chest size, x : 41,54,44,55,39,51

Weight, Y : 328,528,418,580,296,503

Using technology, the prediction model obtained by fitting the data is :

y = 16.3216X - 330.3904

Where, x = chest size ; y = weight

The best predicted weight of a bear with chest size of 40 is

Put x = 40 in the equation :

y = 16.3216(40) - 330.3904

Y = 322.4736

Y = 322 pounds

At α = 0.05

The regression Coefficient, R value obtained is 0.986 ; using this to obtain the Pvalue ;

df = n - 1

Pvalue(0.986, 5) = 0.00198

Since, Pvalue < α ; result is significant at α = 0.05

to find the total number of combinations, multiply the quantity of each item by each other:

2 pairs of shoes x 3 pairs of shorts = 6 different combinations.