1. An advertising company wants to look at the relationship between the dollars
ID: 3218611 • Letter: 1
Question
1. An advertising company wants to look at the relationship between the dollars spent on advertising (AD) and sales (SALES). What is the apparent nature of the relationship between advertising and sales? Advertising 2. Which variable should be the response? Which should be the predictor? Write out the theoretical regression model 3. The relationship can be classified as 4. A simple linear regression generates bo 5886.44 and b 8.27. What is the predicted sales if the company spends $1700? 5. If R2 703, then the correlation between the two variables is 6. The company want to increase the R2 value so that they can have more accurate prediction. One way they can do this is by:Explanation / Answer
Sol2:
variables of interest in an experiment (those that are measured or observed) are called response or dependent variables. Other variables in the experiment that affect the response and can be set or measured by the experimenter are called predictor, explanatory, or independent variables.
Response=Y=sales
predictor=X=advertising
Theoritical reg equation
sales=bo+b1(advertising)
b0-y intercept
b1=slope of regression line
Solution3:
the relationnship is linear and positive
Solution4:
obtained regressionj eq is
sales=5886.44+8.27(advertising)
here advertising=1700
so sales=5886.44+8.27(1700)
predicted sales =$19945.44
Solution5:
r 2=0.703
r=sqrt(0.703)
r=0.838
correlation coeff between two variables is 0.838
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