Randomly selected 10 student cars have ages with a mean of 7.2 years and a standard deviation of 3.4 years, while randomly selected 31 faculty cars have ages with a mean of 5.9 years and a standard deviation of 3.5 years.

1. Use a 0.01 significance level to test the claim that student cars are older than faculty cars.

(a) The test statistic is

(b) The critical value is 2.326

(c) Is there sufficient evidence to support the claim that student cars are older than faculty cars? A. No B. Yes

2. Construct a 99% confidence interval estimate of the difference μs−μf, where μs is the mean age of student cars and μf is the mean age of faculty cars. <(μs−μf)<

The x2 statistic from my study was close to zero, so I rejected the null hypothesis.

The mean cost of domestic airfares in the United States rose to an all-time high of $385 per ticket. Airfares were based on the total ticket value, which consisted of the price charged by the airlines plus any additional taxes and fees. Assume domestic airfares are normally distributed with a standard deviation of $105. Use Table 1 in Appendix B.

a. What is the probability that a domestic airfare is $560 or more (to 4 decimals)?

b. What is the probability that a domestic airfare is $250 or less (to 4 decimals)?

c. What if the probability that a domestic airfare is between $300 and $470 (to 4 decimals)?

d. What is the cost for the 2% highest domestic airfares? (rounded to nearest dollar) $ or Select your answer 1. More 2. Less

A food safety guideline is that the mercury in fish should be below 1 part per million​ (ppm). Listed below are the amounts of mercury​ (ppm) found in tuna sushi sampled at different stores in a major city. Construct a 90​% confidence interval estimate of the mean amount of mercury in the population. Does it appear that there is too much mercury in tuna​ sushi? 0.54  0.82  0.09  0.96  1.28  0.54  0.96

What is the confidence interval estimate of the population mean?

Use this information to draw an appropriate conclusion about whether there could be too much mercury in tuna sushi

What social media tools do marketers commonly use? A survey by Social Media Examiner of B2B marketers, marketers that primarily target businesses, and B2C marketers, marketers that primarily target consumers, reported that 344 (88%) of B2B marketers and 373 (61%) of B2C marketers commonly use LinkedIn as a social media tool. The study also revealed that 239 (61%) of B2B marketers and 324 (53%) of B2C marketers commonly use Google ++ plus as a social media tool. (Data extracted from 2014 Social Media Marketing Industry Report, bit.ly/1e896pD .)

Suppose the survey was based on 390 B2B marketers and 610 B2C marketers.

• a. At the 0.05 level of significance, is there evidence of a difference between B2B marketers and B2C marketers in the proportion that commonly use LinkedIn as a social media tool?

• b. Find the p-value in (a) and interpret its value.

• c. At the 0.05 level of significance, is there evidence of a difference between B2B marketers and B2C marketers in the proportion that commonly use Google ++ plus as a social media tool?

SHOW EXCEL FUNCTIONS NEEDED FOR ANSWERS

--In the GSS, the original race variable was coded as: whites=1, blacks=2, others=3. Which of the following possibilities is the best way to recode this variable into a dichotomy with “white” as the reference category?

a.) whites=1, non-whites=2

b.) non-whites=1, whites=2

c.) whites=0, non-whites=1

d.) whites=-1, non-whites=+1

-- Another word for the reference group is:

a.) the omitted variable

b.) the omitted slope

c.) the omitted category

d.) the omitted constant

-- Here is a regression equation using GSS2008 data, people aged 21 to 29, where men were coded as 0, and women were coded as 1:

# OF TIMES GO TO BAR PER MONTH = 4.00 – 1.73 (SEX)

If women had been coded as 0, and men had been coded as 1, the regression equation would have been:

a.) # OF TIMES GO TO BAR PER MONTH = 4.00 – 1.73 (SEX)

b.) # OF TIMES GO TO BAR PER MONTH = 2.27 + 1.73 (SEX)

c.) # OF TIMES GO TO BAR PER MONTH = 5.73 – 1.73 (SEX)

d.) # OF TIMES GO TO BAR PER MONTH = 4.00 – 2.27 (SEX)

--If we wanted to use the GSS variable HEALTH (self-assessment of health: Excellent, Good, Fair, or Poor) as an independent variable in a regression model using a dummy approach, how many independent variables would we have to create (not including the reference category)?

a.) None, this variable is perfectly fine as is to use in a regression equation.

b.) 2

c.) 3

d.) 4

--A researcher creates a set of four reference-group variables to include in a regression. What can you assume about the variable from which she built these variables?

a.) It likely had three categories

b.) It likely had four categories

c.) It likely had five categories

d.) It likely had six categories

--- With which of the following variables would you most likely not use the reference-grouping technique?

a.) a nominal-level variable

b.) an ordinal-level variable

c.) a ratio-level variable

d.) all are equally likely

You are the operations manager for an airline and you are considering a higher fare level for passengers in aisle seats. How many randomly selected air passengers must you​ survey? Assume that you want to be 99​% confident that the sample percentage is within 4.5 percentage points of the true population percentage. Complete parts​ (a) and​ (b) below.

a. Assume that nothing is known about the percentage of passengers who prefer aisle seats.

n = ?

​(Round up to the nearest​ integer.)

b. Assume that a prior survey suggests that about 29% of air passengers prefer an aisle seat.

n = ?

​(Round up to the nearest​ integer.)

A sample of 20 Automobiles was taken and the miles per gallon (MPG), horsepower (HP), and total weight were recorded. Develop a linear regression model to predict MPG…

1)Using HP as the independent variable. What is the regression equation?

2) Is your model a good predicting equation? How do you know?

3) Using Total Weight as the independent variable, what is the regression equation?

4)Is this a good predicting model? How do you know?

5) Using MPG and Total weight as independent variables, what is the regression equation?

6) Is the model in part e a good predicting equation? How do you know?   

7)  Predict MPG using the model in part e with HP = 100 and weight = 3 thousand pounds.

A researcher wishes to estimate the proportion of adults who have​ high-speed Internet access. What size sample should be obtained if she wishes the estimate to be within 0.03 with 95​% confidence if ​

(a) she uses a previous estimate of 0.36? (round up to the nearest integer) ​(b) she does not use any prior​ estimates? (round up to the nearest integer)

Scores: 57, 49, 53, 60, 58, 59, 48,

1. What is the mean of these scores?   (round your answer to 2 decimal places)
2. What is the median?
3. What is the estimated standard deviation of the population based on this sample?   (round your answer to 2 decimal places)

4.

A simple random sample of 800 elements generates a sample proportion j5 =

.70.

a.

Provide a 90% confidence interval for the population proportion.

b.

Provide a 95% confidence interval for the population proportion.

We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here (data336.dat) is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.

(a) Plot wages versus LOS. Consider the relationship and whether or not linear regression might be appropriate. (Do this on paper. Your instructor may ask you to turn in this graph.)

(b) Find the least-squares line. Summarize the significance test for the slope. What do you conclude?

(c) State carefully what the slope tells you about the relationship between wages and length of service.

This answer has not been graded yet.

(d) Give a 95% confidence interval for the slope.
(  ,  )

worker  wages   los     size
1       44.898  39      Large
2       85.8585 122     Small
3       37.6708 100     Small
4       44.1095 168     Small
5       47.756  25      Large
6       40.8481 22      Small
7       50.5179 27      Large
8       63.4659 70      Large
9       37.2126 86      Large
10      66.0707 95      Small
11      53.5897 56      Large
12      42.5586 18      Small
13      50.3493 129     Small
14      60.3041 75      Large
15      46.2348 93      Large
16      56.1494 23      Large
17      45.4136 15      Large
18      40.9541 44      Small
19      55.3183 26      Large
20      50.7934 58      Large
21      41.2603 79      Large
22      37.3516 19      Small
23      42.1137 30      Large
24      60.4141 88      Small
25      51.9331 119     Large
26      49.6191 20      Small
27      53.1292 116     Small
28      60.8961 62      Large
29      51.3743 31      Large
30      52.4964 42      Large
31      47.748  102     Small
32      47.1194 90      Large
33      60.6775 99      Large
34      70.5214 21      Small
35      39.4673 164     Large
36      50.4703 83      Large
37      66.2801 100     Large
38      62.3078 185     Small
39      43.79   18      Large
40      54.1258 56      Small
41      39.0053 174     Small
42      52.4289 59      Small
43      57.6612 89      Large
44      51.6591 17      Small
45      50.383  73      Large
46      38.2104 40      Small
47      52.421  78      Large
48      45.5227 55      Large
49      62.5477 53      Small
50      43.9493 58      Large
51      76.2546 87      Large
52      56.4322 110     Large
53      37.8525 64      Large
54      37.132  47      Small
55      50.4954 84      Small
56      49.1702 54      Large
57      41.8979 16      Small
58      45.3906 40      Large
59      57.8986 41      Small
60      40.3537 34      Large

The Consumer Reports Restaurant Customer Satisfaction Survey is based upon 148,599 visits to full-service restaurant chains.† One of the variables in the study is meal price, the average amount paid per person for dinner and drinks, minus the tip. Suppose a reporter for a local newspaper thought that it would be of interest to her readers to conduct a similar study for restaurants located in her city. The reporter selected a sample of 8 seafood restaurants, 8 Italian restaurants, and 8 steakhouses. The following data show the meal prices ($) obtained for the 24 restaurants sampled.

Use α = 0.05 to test whether there is a significant difference among the mean meal price for the three types of restaurants.

State the null and alternative hypotheses.

H₀: At least two of the population means are equal.
H_a: At least two of the population means are different.H₀: μ_Italian ≠ μ_Seafood ≠ μ_Steakhouse
H_a: μ_Italian = μ_Seafood = μ_Steakhouse    H₀: μ_Italian = μ_Seafood = μ_Steakhouse
H_a: μ_Italian ≠ μ_Seafood ≠ μ_SteakhouseH₀: μ_Italian = μ_Seafood = μ_Steakhouse
H_a: Not all the population means are equal.H₀: Not all the population means are equal.
H_a: μ_Italian = μ_Seafood = μ_Steakhouse

Find the value of the test statistic. (Round your answer to two decimal places.)

Find the p-value. (Round your answer to four decimal places.)

p-value =

What is your conclusion?

Reject H₀. There is sufficient evidence to conclude that the mean meal prices are not all the same for the three types of restaurants.Reject H₀. There is not sufficient evidence to conclude that the mean meal prices are not all the same for the three types of restaurants.    Do not reject H₀. There is not sufficient evidence to conclude that the mean meal prices are not all the same for the three types of restaurants.Do not reject H₀. There is sufficient evidence to conclude that the mean meal prices are not all the same for the three types of restaurants.

The Bureau of Economic Analysisin the U.S. Department of Commerce reported that the mean annual income for a resident of North Carolina is $18,688 (USA Today, August 24, 1995). A researcher for the state of South Carolina wants to see if the mean annual income for a resident of South Carolina is different. A sample of 400 residents of South Carolina shows a sample mean annual income of $16,860 and the population standard deviation is assumed to known, =$14,624. Use a 0.05 level of significance, the researcher wants to test the following hypothesis.H0:= 18,688Ha:18,688a.What are three rejection rules (You have used confidence interval approach in Question 2)? b.Do three rejection rules lead to the same conclusion? What is your conclusion?

Barking deer.

Microhabitat factors associated with forage and bed sites of barking deer in Hainan Island, China were examined from 2001 to 2002. In this region woods make up 4.8% of the land, cultivated grass plot makes up 14.7%, and deciduous forests makes up 39.6%. Of the 426 sites where the deer forage, 4 were categorized as woods, 16 as cultivated grassplot, and 61 as deciduous forests. The table below summarizes these data.

1. Write the hypotheses for testing if barking deer prefer to forage in certain habitats over others.

2. What type of test can we use to answer this research question?
3. Check if the assumptions and conditions required for this test are satisfied.
4. Do these data provide convincing evidence that barking deer prefer to forage in certain habitats over others? Conduct an appro- priate hypothesis test to answer this research question.