1. Does the data look approximately linear? Or does there appear to be some sort of non-linear trend in our data?

The data look approximately linear.

1. What is the regression model created from our data set?

The mean of years:

x = ni = 1 xi / n

x = 103/11

x = 9.3636

The mean of the Stocks:

= ni = 1 yi / n

= 480/11

= 43.6364

The sum of squares of x:

SSxx = 1073 - 1/11 (103)2

SSxx = 1073 - 10609/11

SSxx = 1073 - 964.4545

SSxx = 108.5455

The sum of squares of stock:

SSyy = 22868 - 1/11 (480)2

SSyy = 22868 - 230400/11

SSyy = 22868 - 20945.4545

SSyy = 1922.5455

The sum of cross products:

SSxy = 4939 - 1/11 (103) (480)

SSxy = 4939 - 49440/11

SSxy = 4939 - 4494.5455

SSxy = 444.4545

The slope is

1 = SSxy/SSxx

1 = 444.4545/108.5455

1 = 4.0946

The y-intercept is

0 = - 1 * x

0 = 43.6364 - 4.0946 x 9.3636

0 = 5.2956

1. What does the slope represent in our regression model?

The slope shows that the company's stock grows by $4094.64 for each year an employee works there.

1. If an employee has been with the company for 13 years, how much company stock would we expect them to have?

We'd anticipate him to have $58525.40

1. In the problem, it was mentioned there are other variables that could impact the amount of company stock awarded to an employee. What are some other variables we may want to collect next time to add to our model?

We might need to gather information about education level, age, performance evaluations, and other factors.

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THE REAL QUESTION IS THIS ONE, BY LOOKING AT THE CHART ABOVE.. PLEASE HELP ME ANSWER THIS QUESTION .. THANK U.

By looking at the graph, are the two variables have a strong correlation? How do you know?