The data table contains waiting times of customers at a​ bank, where customers enter a single waiting line that feeds three teller windows. Test the claim that the standard deviation of waiting times is less than 2.3 ​minutes, which is the standard deviation of waiting times at the same bank when separate waiting lines are used at each teller window. Use a significance level of 0.01. Complete parts​ (a) through​ (d) below. customer waiting times (in minutes) 8.1 7.2 6.4 6.6 6.4 7.1 6.7 6.8 8.5 6.1 8.6 6.6 14.9 7.1 6.9 7.3 7.2 6.8 7.7 8.4 8.7 7.8 6.5 11.9 7.3 6.2 6.3 7.8 7.5 6.1 12.4 6.4 6.9 9.9 4.9 7.7 6.1 7.8 6.4 7.4 14.8 7.5 8.9 7.2 7.1 6.1 7.7 6.6 7.8 6.9 6.4 6.2 6.1 7.2 6.8 7.7 6.6 7.3 8.6 7.7

The data table contains waiting times of customers at a​ bank, where customers enter a single waiting line that feeds three teller windows. Test the claim that the standard deviation of waiting times is less than 1.8 ​minutes, which is the standard deviation of waiting times at the same bank when separate waiting lines are used at each teller window. Use a significance level of 0.05. 1. Compute the test statistic. 2.Find the P-value of the test statistic.

The company rents vehicle and has contracts with customers that run from Sep to June.

Customers pay the yearly fee in advance for the rentals. In September 2001, the company received $70,000 cash and recorded it as rental income.

What is Dec 31,2001 year-end adjusting entries for this transaction under IFRS.

A restaurant's marketing department claims that 45% of customers prefer hamburgers, 41% of the customers prefer chicken sandwiches, and 14% of the customers prefer fish sandwiches. To test this claim, a random group of customers at a fast food chain were asked whether they preferred hamburgers, chicken sandwiches, or fish sandwiches, with the results shown below. Sandwich : Hamburgers Chicken Fish No. of customers: 40 16 8 Based on this sample data, is there evidence to reject the restaurant's claim at a significance level of α = .05?

The data table contains waiting times of customers at a​ bank, where customers enter a single waiting line that feeds three teller windows. Test the claim that the standard deviation of waiting times is less than 1.5 ​minutes, which is the standard deviation of waiting times at the same bank when separate waiting lines are used at each teller window. Use a significance level of 0.05. Complete parts​ (a) through​ (d) below.

A. Identify the null and alternative hypotheses for this test.

B. Identify the test statistic for this hypothesis test.

C. Identify the​ P-value for this hypothesis test.

D. Identify the conclusion for this hypothesis test.

Customer wait time (in minute):

8.6

7.3

6.2

6.5

6.4

6.6

6.6

6.4

7.9

7.6

6.4

8.9

11.2

6.1

8.9

7.8

7.6

6.4

7.1

6.5

6.7

6.7

7.2

6.2

7.2

7.1

6.4

7.8

7.6

6.3

4.2

6.4

7.8

7.1

6.5

6.3

7.9

6.8

7.4

7.4

10.7

6.4

6.5

6.3

7.6

7.3

6.1

7.8

7.9

7.4

5.3

8.8

6.6

6.2

7.1

6.3

7.5

7.3

7.4

6.3

An offline retail store called CoolStore have customers that are either students or not. Customers can buy a plastic bag or not. We know for a fact that: Twenty-five percent of all customers are students. Among customers that are students, eighty percent buy a plastic bag. Among customers who buy a plastic bag, fifty percent are students. Forty customers are chosen at random. The probability is one percent that the number of customers buying a plastic bag exceeds what number?

Companies want to acquire profitable customers. Describe how marketers build relationships with customers

Comiskey Fence Co. is evaluating extending credit to a new group of customers. Although these customers will provide $324,000 in additional credit sales, 12 percent are likely to be uncollectible. The company will incur $17,000 in additional collection expenses. Production and marketing expenses represent 72 percent of sales. The company has a receivables turnover of four times. No other asset buildup will be required to service the new customers. The firm has a 16 percent desired return on investment.

a-1. Calculate the incremental income before taxes from this new group of customers.

Incremental income before taxes           $

a-2. Calculate the return on incremental investment. (Round the final answer to 2 decimal place.)

Return on incremental investment              %

a-3. Should Cominsky extend credit to these customers?

• Yes

• No

b-1. Calculate the incremental income before taxes from the new group of customers if 15 percent of the sales prove uncollectable.

Incremental income before taxes           $

b-2. Calculate the return on incremental investment if 15 percent of the new sales prove uncollectible. (Round the final answer to 2 decimal place.)

Return on incremental investment              %

b-3. Should credit be extended if 15 percent of the new sales prove uncollectible?

• Yes

• No

c-1. Calculate the return on incremental investment if the receivables turnover drops to 1.6 and 12 percent of the accounts are uncollectible (as in part a)? (Round the final answer to 2 decimal places.)

Return on incremental investment              %

c-2. Should credit be extended if the receivables turnover drops to 1.6 and 12 percent of the accounts are uncollectible (as in part a)?

• No

• Yes

Problem 7-23

Reconsider Comiskey Fence. Assume the average collection period is 180 days. All other factors are the same (including 12 percent uncollectible).

a. Compute the return on incremental investment. (Use 365 days in a year. Do not round intermediate calculations. Round the final answer to 2 decimal places.)

Return on incremental investment              %

b. Should credit be extended?

• Yes

• No

It sampled 40 customers in San Francisco and 50 customers in San Diego to assess potential demand.

On a scale of 1-7 (7 = very likely to buy), San Diego customers had a mean of 3.5 with a standard deviation of 1.1. SF customers had a mean of 4.1 with a standard deviation of 2.3.

Are these markets statistically different?

1.Compute standard error

2.Compute t-calc  

3.Compare |t-calc| to 1.96 (95% confidence in our results) and 2.58 (99% confidence)

4.If |t-calc| > 1.96, reject the null with 95% confidence

●

Standard error for 2 means (sxs_x ̅ ) = ?12?1+?22?2√((s_1^2)/n_1 +(s_2^2)/n_2 )

T-calc for 2 means = ?1−?2??(x ̅_1-x ̅_2)/s_x ̅

Customers are arriving to a shop according to Poisson process with mean 3.2 customers/hour. What is the probability that the next customer will arrive after 10 minutes but before 33 minutes?