A research center is interested in investigating the height and age of children who are between 5 to 9 years old. In order to do this, a sample of 15 children is selected and the data are given below. Age (in years) Height (inches) 7 47.3 8 48.8 5 41.3 8 50.4 8 51 7 47.1 7 46.9 7 48 9 51.2 8 51.2 5 40.3 8 48.9 6 45.2 5 41.9 8 49.6 How much of the variation in the sample values of height does the model estimate

0.940

Step-by-step explanation:

Given the data:

Age in years(X) Height(Y)

7 47.3

8 48.8

5 41.3

8 50.4

8 51

7 47.1

7 46.9

7 48

9 51.2

8 51.2

5 40.3

8 48.9

6 45.2

5 41.9

8 49.6

The proportion of Variation explained by the line of best fit in a regression model can be determined by calculating the Coefficient of determination (R²) of the model.

Using the online R² calculator, the variation in the sample values of height which is estimated by the model is 0.9696² = 0.94012416.

Hence about 0.94 or 94% variation in sample values of height is estimated by the model while (1 - 0.94 = 0.06 or 6%) is explained by other factors.

answer: the price of one pound cabbage = $ 0.8

the point (10,8) represents that the cost of 10 pounds cabbage is $ 8

step-by-step explanation:

since, here is a proportional relation between the number of pounds of cabbage (x) and the price in dollars (y).

therefore, we can write,

⇒ y = k x

where k is the constant of proportionality.

now, point (5,4) is in the line.

thus, it will satisfies the above equation of line.

⇒ 4 = 5 k

⇒ k = 0.8

thus, the equation of the line is,

y = 0.8 x

a) for x = 1,

y = 0.8

therefore, the cost of one pound of cabbage is 0.8 dollars.

b) in the below graph (10,8) represents that the cost of 10 pounds of cabbage is 8 dollars.