A brief outline in your own words of the key principle(s) underlying AASB15 Revenue from Contracts with Customers

2.) You want to determine if the average height of men in California is greater than the average height of men in Nebraska. You take a random sample of 30 men in California and 30 men in Nebraska. The data below represents the heights of the men in inches. Write the R code that does the following:

H0: Difference in means in populations is zero.

Ha: Difference in means in the populations is not zero.

NE_heights<-c( 73.5, 68.5, 70, 63, 64, 65, 64, 70, 61, 61.25, 69, 73, 69, 66, 69.5, 68,

64, 64, 72.5, 69, 67, 63, 66.5, 70.5, 64, 67, 71, 74, 68, 65)

CA_heights <- c( 72, 73.5, 74, 75, 66, 78, 70, 73, 74, 68, 71, 68, 67, 66, 73, 72, 82, 71, 64, 72, 65, 66, 69, 83, 67, 74, 76, 65, 74, 79)

a.) Makes two boxplots, an orange one for the CA_heights data, and a red one for the NE_heights data which labels the main title "Men’s heights California vs Nebraska" and names the CA_heights data as "CA heights" and the NE_heights data as "NE heights".

b.) Computes the, sample size, mean and standard deviation of both CA_heights and NE_heights data.

c.) Performs an unpaired "less" than t-test with =.02 to decide whether there is a statistically significant difference between men’s heights in California and Nebraska.

d.) Paste your R code into Run R Script and run the script.

e.) Paste the R output to the bottom R code.

f.) Looking at the p-value in the R output, decide if there is evidence to suggest that there is a statistically significant difference between men’s heights in California and Nebraska.

Write the p-value and your conclusion at the top of your R code.

Suppose you are the Chief Marketing Officer for a retailer that has data on the home addresses of its

1,000,000 most active customers. You hope to determine whether sending out “20% off your entire

purchase” coupons by mail will increase revenues.

You conjecture that customers who have access to this coupon will spend more in the store over the

next year. However, skeptics in your company argue that the coupons will just allow customers to

spend less on items they would have purchased anyway. This is a debate that an experiment can

resolve.

In thinking about how large of an experiment you need to have enough statistical power, you realize

that many of the customers you send the coupons to in the mail will not open the mail and so will not

realize they received the coupon.

1. The CEO argues that to estimate the effects of the coupons on revenue, you should compare

the difference in revenues from a) people you sent the coupons and who used them and b)

people you sent the coupons but who did not use them. Write a response to your CEO:

describe the flaw with this plan in language the CEO will understand, and advocate for your

proposed experiment.

2. To avoid the cost of sending out coupons you do not need to, you ask the data science team

to plan an experiment just large enough (with just enough statistical power) to reliably detect

a treatment effect if the true effect on those who open the mail and realize they have the

coupon is a $2 increase in revenue over the next year. The data science team tells you that

an experiment with 100,000 people in the treatment group (leaving the remaining 900,000 in

the control group) will be well-powered to detect an overall difference between the entire

treatment and control groups of $2 in revenue over the next year. To send out the minimum

number of coupons required while still having enough statistical power to detect a $2 effect of

opening the mail, can you send out fewer, the same number of, or more coupons than

100,000?

Consider following table - Convert it to 3NF

Do confidence interval Estimate the difference between grade of Male and female students using 98% level of confidence and write your conclusion - insert the SPSS output in the space below.

Do ANOVA test

Test to see if there is a difference between grade of different ethnic groups - insert the SPSS output in the space below. What conclusion can you make based on your analysis?

Do confidence interval

Estimate the difference between grade of Male and female students using 98% level of confidence and write your conclusion - insert the SPSS output in the space below.

Do ANOVA test

Test to see if there is a difference between grade of different ethnic groups - insert the SPSS output in the space below. What conclusion can you make based on your analysis?

Suppose in the country A, the velocity of money in the country A is always stable. Answer the following questions:

a. What is the quantity equation? (Please indicate and explain each variable) (2%)

b. Suppose the price level in the period t-1 is P_t-1, and the price level In the period t is P_t in the country A.Please use P_t and P_t-1to represent the inflation rate during the period t-1 and the period tin the country A. (2%)

c. Suppose in the country A, the money supply was $2 million and real GDP was $4 million in 2005.In 2006, the money supply increased by 10 percent, real GDP increased by 5 percent and nominal GDP equaled $8.8 million. How much was the inflation rate between 2005 and 2006 in the country A? (Please use the percentage to represent your answer, and calculate to the second digit below, e.g. 0.456-0.46) (6%)