1. The table below lists the attributes and levels used in a regression for a credit card. The dependent variable is the number of people (in thousands) who use the credit card.

Attribute	Levels
Brand	National Bank Capital One
Interest Rate	12.9% APR 9.9% APR
Payback	1%WHO&Habitat 1% Cash back 5%WHO&Habitat 5% Cash back

Standard

Parameter Estimate Error t Value p value

Intercept 10.0000 1.0334 19.53 <.0001

Capital One 0.7180 0.0382 18.79 <.0001

9.9% APR 1.7057 0.0358 47.68 <.0001

1% Cash Back 1.5101 0.0664 22.73 <.0001

5% Cash Back 2.4052 0.0647 37.16 <.0001

5% Who&Habitat 0.1262 0.0809 1.56 0.1186

The parameter estimates for a regression model are reported below:

1. What are the baselines for Brand, Interest Rate and Payback?

2. Assume that there are four credit cards in the market (see below). Which of these four credit cards has the highest sales? Please do your calculation based on the regression coefficients.

Credit Card	# of users (in thousands)
National Bank, 9.9% APR, 5% Cash back
Capital One, 12.9% APR, 1% Who&Habitat
Capital One, 9.9% APR, 1% Cash back
National Bank, 12.9% APR, 5% Who&Habitat

Space for your calculations:

2. Let Sales=284+22CompetitorPrice-47Price; sales are in units; and price is in dollars.

1. What are expected unit sales when your competitors price is $2 and your own price is $3?

2. How much more do you expect to sell if you reduce your price by 50 cents?

3. Suppose your competitor lowers the price by $1. If you want to keep the same level of sales, how should you change your price?

3. With a budget of $1000, an average CPC of $2.50, how many clicks can the advertiser receive before their budget is exhausted?

4. With an unlimited budget, an average CPC of $1.00, a CTR of 1.8%, and 60,000 impressions, how much will the advertiser spend?

5. I randomly stopped 250 shoppers at the Oviedo mall and asked each shopper his/her age. I want to test if the average age of male shoppers is different from the average age of female shoppers. Which analytical technique is my best choice?

1. T-test
2. Cross-tabs
3. Chi-square test
4. Correlation

6. You are a brand manager who is interested in finding out if the recent advertising campaign has helped the sales of your brand. You have collected relevant data and are planning on conducting a hypothesis test. What would be your null hypothesis?

1. The advertising campaign has no effect on sales.
2. The advertising campaign has an effect on sales.