Question

You are again given the same 5 observations that you were provided with in the Correlation problem.However,you are now asked to derive the regression line,y’= a+bX for the data below.After you have calculated the regression equation,explain to me how you could use it.

                               X(Independent Variable) Y(Dependent variable)

Month Advertising Expenditure (in Millions of $) Sales Revenue (in Millions of $)       

July 1 3

August 2 7

September 3 5

October 4 11

November 5 14

Calculating the Standard Error of the Estimate-Sy.x . You will be using the same summation data that you used to derive the equation of the regression line,Y’=a +bX,in Regression ( Part I )

After you have calculated the Standard Error of the Estimate,Sy.x,tell me what the number you have obtained means.

Calculating a Prediction Interval for a particular value of X

In this problem ,you will be using the results of Part I and Part II,which were Y’ =a+bX and Sy.x ,to compute a prediction value for a particular value of X.I suggest that you use X=1 as the particular value of X.However,you are free to use whatever value of X that you want

Answer 1

ANSWER::

Sales=0.2+2.6*advertisement expenditure

Use- we use this regression equation to predict futue sales based on how much we are going spend on advertisement.

S.E=

0.642910051

The standard error of the regression slope, s (also called the standard error of estimate) represents the average distance that your observed values deviate from the regression line. The smaller the “s” value, the closer your values are to the regression line.

Now below I am providing you all the calculations and futher work that is required

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