The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. complete parts (a) through (e) below. no. of absences, x 0 1 2 3 4 5 6 7 8 9 final grade, y 88.5 85.7 82.8 80.3 77.4 73.1 63.6 68.1 65.2 62.4 (a) find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variable.

The equation of the regression line is:

Step-by-step explanation:

Linear regression is a linear approach to modelling the relationship between a dependent variable and one or more independent variables.

Let X be the independent variable and Y be the dependent variable. We will define a linear relationship between these two variables as follows:

We have the the following data:

To find the line of best fit for the points, follow these steps:

Step 1: Find and as it was done in the table.

Step 2: Find the sum of every column:

Step 3: Use the following equations to find intercept a and slope b:

Step 4: Assemble the equation of a line

The graph of the regression line is:

38.5

step-by-step explanation:

lets say, first number = r

second number = 3r+7

total = 49

(r)+(3r+7)= 49

4r+7 = 49

4r = 42

r = 42/4

r= 10.5

3r+7 = 3(10.5)+7 = 38.5

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first, we define the variables:

x: number of years after 1950

f (x): amount of vinyl sold.

then, with the variables defined, we have:

68594 vinyl records were sold in 1958 > f (8) = 68594

91299 vinyl records were sold in 1961 > f (11) = 91299

38720 vinyl records were sold in 1952 > f (2) = 38720

161743 vinyl records were sold in 1967 > f (17) = 161743

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step-by-step explanation: