Kathy Chen​, owner of Flower Hour​, operates a local chain of floral shops. Each shop has its own delivery van. Instead of charging a flat delivery​ fee, Chen wants to set the delivery fee based on the distance driven to deliver the flowers. Chen wants to separate the fixed and variable portions of her van operating costs so that she has a better idea how delivery distance affects these costs. She has the following data from the past seven​ months:

Use Microsoft Excel to run a regression​ analysis, then do the​ following:

A suburban hotel derives its revenue from its hotel and restaurant operations. The owners are interested in the relationship between the number of rooms occupied on a nightly basis and the revenue per day in the restaurant. Below is a sample of 25 days (Monday through Thursday) from last year showing the restaurant income and number of rooms occupied. Day Income Occupied Day Income Occupied 1 $ 1,452 20 14 $ 1,425 31 2 1,361 20 15 1,445 51 3 1,426 21 16 1,439 62 4 1,470 80 17 1,348 45 5 1,456 70 18 1,450 41 6 1,430 29 19 1,431 62 7 1,354 70 20 1,446 47 8 1,442 21 21 1,485 43 9 1,394 15 22 1,405 38 10 1,459 36 23 1,461 36 11 1,399 41 24 1,490 30 12 1,458 35 25 1,426 65 13 1,537 51 PictureClick here for the Excel Data File Use a statistical software package to answer the following questions.

b. Determine the coefficient of correlation between the two variables. (Round your answer to 3 decimal places.) Pearson correlation State the decision rule for 0.01 significance level: H0: ρ ≤ 0; H1: ρ > 0 (Round your answer to 3 decimal places.) Reject H0 if t > Compute the value of the test statistic. (Round your answer to 2 decimal places.) Value of the test statistic

c. Is it reasonable to conclude that there is a positive relationship between revenue and occupied rooms? Use the 0.01 significance level. H0, There is a between revenue and occupied rooms.

d. What percent of the variation in revenue in the restaurant is accounted for by the number of rooms occupied? (Round your answer to 1 decimal place.) % of the variation in revenue is explained by variation in occupied rooms.

Chipotle Mexican Grill continues to suffer from perception issues after a string of outbreaks, including E.coli, worried customers about the safety of eating at the fast-casual chain. Chipotle’s strategy for getting customers back into its restaurants was to give away free tacos, burritos, and chips. And while its customer survey scores are improving, Chipotle is still operating at a loss. What concepts, constructs, and operational definitions should any future research deal with?

Management of a soft-drink bottling company wants to develop a method for allocating delivery costs to customers. Although one cost clearly relates to travel times within a particular route, another variable cost reflects the time required to unload the cases of soft drink at the delivery point. A sample of 20 deliveries within a territory was selected. The delivery time and the number of cases delivered were recorded. Develop a regression model to predict delivery time based on the number of cases delivered. Use the least-square method to calculate the regression coefficients, b0 and b1. Showing all formulas and equations a) Write your regression equation. b) Determine the coefficient of determination, r2, and explain it meaning in this problem. c) Perform a residual analysis. Is there any evidence of patterns in the residuals? Explain.

For this problem, carry at least four digits after the decimal in your calculations. Answers may vary slightly due to rounding.

A random sample of 5913 physicians in Colorado showed that 3062 provided at least some charity care (i.e., treated poor people at no cost).

(a) Let p represent the proportion of all Colorado physicians who provide some charity care. Find a point estimate for p. (Round your answer to four decimal places.)


(b) Find a 99% confidence interval for p. (Round your answers to three decimal places.)

Give a brief explanation of the meaning of your answer in the context of this problem.

1% of the confidence intervals created using this method would include the true proportion of Colorado physicians providing at least some charity care.99% of the confidence intervals created using this method would include the true proportion of Colorado physicians providing at least some charity care.    1% of all confidence intervals would include the true proportion of Colorado physicians providing at least some charity care.99% of all confidence intervals would include the true proportion of Colorado physicians providing at least some charity care.

(c) Is the normal approximation to the binomial justified in this problem? Explain.

No; np < 5 and nq > 5.Yes; np > 5 and nq > 5.    No; np > 5 and nq < 5.Yes; np < 5 and nq < 5.

The breaking strengths of cables produced by a certain manufacturer have a standard deviation of 91 pounds. A random sample of 90 newly manufactured cables has a mean breaking strength of 1700 pounds. Based on this sample, find a 95% confidence interval for the true mean breaking strength of all cables produced by this manufacturer. Then complete the table below. Carry your intermediate computations to at least three decimal places. Round your answers to one decimal place. (If necessary, consult a list of formulas.)

The auditor for a large corporation routinely monitors cash disbursements. As part of this process, the auditor examines check request forms to determine whether they have been properly approved. Improper approval can occur in several ways. For instance, the check may have no approval, the check request might be missing, the approval might be written by an unauthorized person, or the dollar limit of the authorizing person might be exceeded.

(a) Last year the corporation experienced a 5 percent improper check request approval rate. Since this was considered unacceptable, efforts were made to reduce the rate of improper approvals. Letting p be the proportion of all checks that are now improperly approved, set up the null and alternative hypotheses needed to attempt to demonstrate that the current rate of improper approvals is lower than last year's rate of 5 percent. (Round your answers to 2 decimal places.)

H₀: p > ______ versus H_a: p < ______.

(b) Suppose that the auditor selects a random sample of 617 checks that have been approved in the last month. The auditor finds that 19 of these 617 checks have been improperly approved. Calculate the test statistic. (Round your answers to 2 decimal places. Negative value should be indicated by a minus sign.)

(c) Find the p-value for the test of part b. Use the p-value to carry out the test by setting a equal to .10, .05, .01, and .001. Interpret your results. (Round your answer to 4 decimal places.)

p-value                 

Reject H₀ at α = (Click to select).1, and .05/ .1, .05 and .01/ .10, .05, .01, and .001/ none.

What is a hypothesis? Provide an example of a "null hypothesis" and an "alternative hypothesis"

A recent poll stated that if the presidential election were held today, the results would be as follows:

Candidate A: 33%

Candidate B: 33%

Undecided: 34%

Margin of error is 20%

Based on our class discussions to date, what conclusion would you draw from this data?

Researchers at Consumer Reports recently found that fish are often mislabeled in grocery stores and restaurants. They are interested to know, however, if the proportion of mislabeling varies by type of fish. They collected data on 400 packages of tuna and 300 packages of mahi mahi and found that 110 and 95 were mislabeled, respectively.

a. What are the point estimates for the proportion of tuna and mahi mahi that are mislabeled?

b. Provide a 95% confidence interval estimate of the difference between the proportion of tuna and mahi mahi that is mislabeled.

c. Based on your answer to (b), would you say the rate of mislabeling is different for tuna and mahi mahi? Explain your answer.

d. Now, let’s say we want to test whether the proportion of tuna mislabeled is lower than the proportion of mislabeled mahi mahi. Assuming a 99% confidence level, work through your hypothesis testing procedure below.

Discuss the differences in a regression model between making the random error being multiplicative and making the random error being additive regarding how you approach estimation of the model coefficient(s), how you apply linearization for estimating the model coefficient(s), and how you obtain starting values for estimation of the model coefficient(s).

Researchers studied a random sample of high school students who participated in interscholastic athletics to learn about the risk of lower-extremity injuries (anywhere between hip and toe) for interscholastic athletes. Of 998 participants in girls' soccer, 77 experienced lower-extremity injuries. Of 1660 participants in boys' soccer, 159 experienced lower-extremity injuries.

Write a two-way table of observed counts for gender and whether a participant had a lower-extremity injury or not.

(b) Determine a two-way table of expected counts for these data. (Round the answers to one decimal place where it is needed.)

(c) Show calculations verifying that the value of the chi-square statistic is 2.67. Chi-square = (77-88.6)2/ + (921- )2/909.4 + ( -147.4)2/147.4 + (1501- )2/ = 1.52 + 0.15 + + 0.09 = 2.67

A hospital employs 338 nurses and 35​% of them are male. How many male nurses are​ there? b. An engineering firm employs 168 engineers and 109 of them are male. What percentage of these engineers are​ female? c. A large law firm is made up of 65​% male​ lawyers, or 164 male lawyers. What is the total number of lawyers at the​ firm?

I'm having a pretty difficult time with these types of problems and I'd really appreciate it if someone could show me how to go about doing this one, thank you!

1. Consider the population of {32, 34, 37, 39}

a) Find the mean, variance, and standard deviation

b) Suppose the sample size n=2 is randomly chosen with replacement from this population, List the 16 possible samples of size n=2

c) Fill out the table

d) How do the average of all of the 16 sample means, sample variance, and sample standard deviation compare to the population mean, population variance, and population standard deviation?

According to Harper’s magazine, the time spend by kids in front of the television set per year can be modeled by a normal distribution with a mean equal to 1500 hours and a standard deviation equal to 250 hours. If 25 kids are randomly selected from this population, what is the probability that the average of their times spent watching television is at least 1650 hours per year?