The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $33 million. Is the result close to the actual number of viewers, 3.03.0 million? Use a significance level of 0.05.

y = 5.064 - 0.010x

Here, in this question x = 33

y = 4.734 million views

In this question data is missing and I filled it out and calculated the questions accordingly. Please refer to the attachment for the data calculated.

Step-by-step explanation:

First of all, this question is incomplete. It lacks the data needed to calculate the required things.

So, I  figured out the question and I will try my best to solve the question at hand.

I have calculated the some data sheet in excel. Please refer to the attachment for that data.

let a be the salaries

b be the viewers

= ∑  -

= 7522.8571

= ∑  -

= 47.1943

= ∑  -

= -76.8286

Now the slope of the required regression equation is:

Slope =  / = -76.8286/7522.8571 = -0.010

And the intercept of the required regression equation:

intercept = x (∑b - slope x ∑a) = 5.064

So, the regression equation will be:

y = intercept + slope x

y = 5.064 - 0.010x

Here, in this question x = 33

y = 5.064 - 0.010 (33)

y = 4.734 million views

25% is the answer