A local grocery store wants to predict its daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/MegaStat output given above summarizes the results of the regression model. What is the value of the simple coefficient of determination?

Step-by-step explanation:

Hello!

The manager of the store made a linear regression analysis to study if the amount of newspaper advertising (independent variable, X) significantly affects the sales (dependent variable, Y)

The coefficient of determination R² is a statistic that measures the percentage of the variability of Y that is explained by X in the context of the regression model. It also determines the ability of the model to replicate the results of the analysis.

The Excel output is attached below, the calculated determination coefficient is:

R²= 0.726

Interpretation

72.6% of the variability of the estimated average daily sales of the grocery store is explained by the amount of newspaper advertisement placed under the estimated model.

I hope this helps!

yes, gavin is right.

step-by-step explanation:

gavin is correct. 

this problem is about converting 9% per year to how many percent per quarter. the rate is still the same. it only differed in the time period. so, through dimensional analysis,

9% per year  × (1 year / 4 quarters) = 2.25% per quarter

if he was asked to convert 9% per year to how many percent per quarter  compounded quarterly, then you will not simply divide by four. this is because compounding is not linear.

hope this , have a good day. c;

step-by-step explanation: