Chapter 1. Tutorial Regression

Problem Statement

{0.30, 0.35, 0.40, 0.45, 0.50}
rand(0,4)
0.4[2]
{0.70, 0.65, 0.60, 0.55, 0.50}
{2,3,4,5,6,7}
rand(0,5)
6[4]
{10,10,10,10,10,10}
10[4]
{20,30,40,50,60,70}
60[4]
{50,15,20,25,35,25}
35[4]
{5,5,8,5,12,14}
12[4]
{3,2,5,4,7,6}
rand(0,5)
2[1]
{5,4,5,5,5,5}
4[1]
{10,5,10,10,10,10}
5[1]
{15,10,25,20,35,30}
10[1]
{30,20,50,40,70,60}
20[1]
{2,3,4,5,6,7}
rand(0,5)
3[1]
{130,140,150,160, 170,180}
140[1]
{80,85,90,95,100,105}
rand(0,5)
80[0]
{6,5,4,3,2,1}
6[0]
{5,4,5,5,5,5}
5[0]
{16,17,18,19,20,21}
16[0]
{80,85,90,95,100,105}
80[0]

A dataset consists of the composition of 77 breakfast cereals. For each cereal, the following variables were measured:

  • Calories/serving
  • Fat/serving (g)
  • Fiber/serving (g)

Separate regression lines were obtained as follows:

(a) Calories = 110 + 10 (grams of fat)

(b) Calories = 110 – 5 (grams of fiber)

Step 1

questions

Question 1

For every additional gram of fat, the number of calories .

Correct.
Incorrect.

Step 2

Question 5

Suppose that two cereals differ by 6 grams of fat per serving. The caloric content per serving would differ by

A.
B.
C.
D.

Correct.
Incorrect.

Step 3

Question 7

The predicted number of calories for a cereal with 3 grams of fat is ______ calories.

Correct.
Incorrect.