Reference no: EM132152225
Question 1 - Answer all parts of this question.
a) A cost accountant has derived the following data on the weekly output of standard size boxes from a factory.
![154_table.png](https://secure.expertsmind.com/CMSImages/154_table.png)
i) Calculate the regression coefficients β^1 and β^2 for the equation Y^i - β^1+ β^2Xi before estimating the regression model, plot the data.
ii) Intercept the regression coefficients β^1 and β^2.
b) Repeat this question by using log of each of the above variables.
Question 2 - Answer all parts of this question
The following data were given to support the theory that high protein diets reduce the fertility of people:
![484_table1.png](https://secure.expertsmind.com/CMSImages/484_table1.png)
a) Estimate the least square regression line Y = β1 + β2X for the data above.
b) Calculate the coefficient of correlation.
c) Are data o these type adequate to establish a 'cause and effect' relationship between these two variables? Can any conclusions be drawn from the result of your calculations?
Question 3 - Answer all parts of this question
To investigate the relationship between the level of advertising in local papers and the level of sales of a particular consumer product, the marketing manager of a national firm used different levels of advertising in 10 randomly selected geographic areas. The results are given in the table below:
![1238_table2.png](https://secure.expertsmind.com/CMSImages/1238_table2.png)
a) Draw a scatter diagram for these data.
b) Estimate the least squares regression line Y = β1 + β2X for the data above.
c) Calculate the R2 and interpret the result.
d) Use your OLS estimates to predict the level of sales in an area in which £1000 is spent on advertising.