Draft a response to each of the bulleted questions below. Each question must have its own response and have a minimum of 50 words.

1. What is a regression line, how do we come up with one?
2. A customized milling operation uses the equation $200 plus $150 per hour to give price estimates to customers. If it pays a fixed fee to ship these orders, how should it change this equation if the cost of shipping goes up?
3. A package delivery service uses a regression equation to estimate the fuel costs of its trucks based on the number of miles driven. The equation is of the form EstimatedDollars = b₀ + b₁ Miles. If gasoline prices go up, how would you expect the fit of this equation to change?
4. How would you describe a linear relationship, how can we figure out if a linear relationship makes sense?
5. Suppose that large diamonds (more than 1.5 carats) sold at retail tend to be of very mixed quality, whereas small diamonds have consistent quality (more uniform color, clarity, and attractive cut). If this is the case, can we use the SRM to describe the relationship between price and weight among diamonds of widely varying size?
6. In the regression of production time on number of units, how would the following statistics change had the response variable been expressed in hours rather than minutes?
7. a) b0
8. b) b1
9. c) se
10. d) t-statistic for b1
11. Correlation is a measure of the linear relationship between two variables. However, there is a difference between correlation and causation. How are they different?

8. Data on sales have been collected from a chain of convenience stores. Some of the stores are considerably larger (more square feet of display space) than others. In a regression of sales on square feet, can you anticipate any problems?