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A survey collected data on annual credit card charges in seven different categories of expenditures: transportation, groceries, dining out, household expenses, home furnishings, apparel, and entertainment. Using data from a sample of 42 credit cardaccounts, assume that each account was used to identify the annual credit card charges for groceries (population 1) and the annual credit card charges for dining out (population 2). Using the difference data, with population 1 − population 2, the sample mean difference was

d = $870,

and the sample standard deviation was

s_d = $1,121.

(a)

Formulate the null and alternative hypotheses to test for no difference between the population mean credit card charges for groceries and the population mean credit card charges for dining out.

H₀: μ_d ≠ 0

H_a: μ_d = 0

H₀: μ_d < 0

H_a: μ_d = 0

H₀: μ_d ≤ 0

H_a: μ_d > 0

H₀: μ_d ≥ 0

H_a: μ_d < 0

H₀: μ_d = 0

H_a: μ_d ≠ 0

(b)

Calculate the test statistic. (Round your answer to three decimal places.)

What is the p-value? (Round your answer to four decimal places.)

Can you conclude that the population means differ? Use a 0.05 level of significance.

The p ≤ 0.05, therefore we can conclude that there is a difference between the annual population mean expenditures for groceries and for dining out.The p > 0.05, therefore we can conclude that there is a difference between the annual population mean expenditures for groceries and for dining out.    The p > 0.05, therefore we cannot conclude that there is a difference between the annual population mean expenditures for groceries and for dining out.The p ≤ 0.05, therefore we cannot conclude that there is a difference between the annual population mean expenditures for groceries and for dining out.

(c)

What is the point estimate (in dollars) of the difference between the population means?

$

What is the 95% confidence interval estimate (in dollars) of the difference between the population means? (Round your answers to the nearest dollar.)

$  to $

Which category, groceries or dining out, has a higher population mean annual credit card charge?

The 95% confidence interval  ---Select--- contains is completely below is completely above zero. This suggests that the category with higher mean annual expenditure is  ---Select--- groceries dining out .

1.

Suppose a researcher is interested in carrying out a phase II clinical trial in order to assess the effectiveness of four different doses of an investigational new drug. Assume the following table represents the summary statistics revolving around the number of adverse events in the four fasting glucoses among the groups.

A) Calculate the MSW.

B) Calculate the MSB

2.

A researcher is interested in the effectiveness of a new asthma medication at increasing the forced vital capacity (FVC) in children. The medicated spray to be used via inhaler has moved into phase II of clinical trials where five different treatment doses are being tested against the control best standard of care. Suppose the following incomplete ANOVA table summarizes the preliminary analysis for the study.

A) Complete the ANOVA table

B) Calculate an F statistic and a pvalue.

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A sample of 112 mortgages approved during the current year showed that 44 were issued to a single-earner family or individual. The historical percentage is 36 percent. At the .05 level of significance in a right-tailed test, has the percentage of single-earner or individual mortgages risen? (a-1) H0: π ≤ .36 versus H1: π > .36. Choose the right option. a. Reject H0 if zcalc > 1.645 b. Reject H0 if zcalc < 1.645 a b (a-2) Calculate the test statistic. (Round intermediate calculations to 2 decimal places. Round your answer to 4 decimal places.) Test statistic 1.645 (a-3) The null hypothesis should be rejected. True False (b) Is this a close decision? Yes No (c) State any assumptions that are required. a. nπ < 10 and n(1 − π) > 10 b. nπ < 10 and n(1 − π) < 10 c. nπ > 10 and n(1 − π) > 10 d. nπ > 10 and n(1 − π) < 10 a b c d

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 (data96.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.


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

worker  wages   los     size
1       61.372  54      Large
2       42.7536 33      Small
3       45.7298 57      Small
4       59.9747 63      Small
5       66.9318 190     Large
6       47.0695 112     Small
7       49.306  41      Large
8       41.0451 49      Large
9       55.3925 29      Large
10      51.586  51      Small
11      48.8118 34      Large
12      47.6549 49      Small
13      51.9155 58      Small
14      49.4336 71      Large
15      49.0055 59      Large
16      67.1645 54      Large
17      41.0187 146     Large
18      66.6989 64      Small
19      37.3414 57      Large
20      41.1314 44      Large
21      68.2611 54      Large
22      49.2968 146     Small
23      41.31   71      Large
24      51.4378 131     Small
25      39.8553 92      Large
26      46.3618 137     Small
27      49.451  31      Small
28      41.2582 85      Large
29      56.6397 46      Large
30      43.6494 98      Large
31      43.9767 125     Small
32      44.4695 87      Large
33      45.9359 95      Large
34      42.7246 100     Small
35      45.1822 111     Large
36      67.6785 126     Large
37      47.3643 115     Large
38      44.4952 41      Small
39      41.0943 58      Large
40      43.894  133     Small
41      49.3584 49      Small
42      48.877  86      Small
43      55.4153 37      Large
44      52.4565 25      Small
45      79.1435 85      Large
46      47.3674 121     Small
47      37.8021 81      Large
48      38.0888 31      Large
49      40.4484 146     Small
50      45.4833 15      Large
51      53.525  38      Large
52      52.6821 102     Large
53      42.9239 18      Large
54      40.1348 168     Small
55      75.9808 72      Small
56      37.1931 24      Large
57      48.2541 36      Small
58      49.557  44      Large
59      79.727  28      Small
60      53.8476 56      Large

The Tire Rack, America's leading online distributor of tires and wheels, conducts extensive testing to provide customers with products that are right for their vehicle. The following data show survey ratings (1 to 10, with 10 being the highest) for 18 summer tires. Develop an estimated regression equation that can be used to predict the Buy Again rating given based on the Steering and Tread wear rating. How many percent of the variation in the Buy Again variable could be predicted by Steering and Thread wear rating?

Note: put answers into decimal form, if your answer is 90.8765%, enter in 0.908765.

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 (data493.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       44.4711 150     Large
2       45.2146 21      Small
3       74.8957 123     Small
4       72.0558 80      Small
5       39.0496 83      Large
6       47.9774 73      Small
7       51.2293 86      Large
8       69.0781 179     Large
9       39.2668 39      Large
10      53.424  125     Small
11      51.8895 50      Large
12      42.1108 67      Small
13      50.9806 86      Small
14      41.6564 26      Large
15      64.8102 138     Large
16      38.3316 30      Large
17      70.1092 31      Large
18      59.5725 22      Small
19      72.6489 97      Large
20      48.6928 129     Large
21      65.3321 34      Large
22      46.696  56      Small
23      42.9948 100     Large
24      63.7128 106     Small
25      54.0511 170     Large
26      37.2906 56      Small
27      58.9101 44      Small
28      80.6583 206     Large
29      82.063  63      Large
30      68.5583 114     Large
31      48.3471 97      Small
32      43.8155 109     Large
33      58.983  16      Large
34      37.3826 23      Small
35      68.8845 63      Large
36      55.8785 167     Large
37      60.7873 46      Large
38      43.4198 16      Small
39      47.1446 77      Large
40      44.8549 121     Small
41      65.4524 29      Small
42      45.9087 72      Small
43      46.2893 28      Large
44      65.7419 114     Small
45      44.6151 37      Large
46      89.5987 173     Small
47      50.201  25      Large
48      79.3444 55      Large
49      44.7124 62      Small
50      41.2526 63      Large
51      67.4239 138     Large
52      80.865  51      Large
53      50.7154 86      Large
54      40.1463 165     Small
55      56.4553 29      Small
56      49.2739 82      Large
57      58.4318 17      Small
58      58.0383 127     Large
59      52.917  71      Small
60      62.8699 28      Large

If a researcher found a Person correlation of r = 0.32 between aggression and frequency of binge drinking in a sample of n = 52 undergraduate students. Therefore, he can conclude that __________.

• A. there is no significant relationship between these variables with either, p <.05 and p <.01

• B. there is a significant positive relationship between these variables with p <.05 but not with p <.01.

• C. there is a significant positive relationship between these variables with both, p <.05 and p <.01

• D. there is a significant positive relationship between these variables with p <.01 but not with p <.05.

In a fishing lodge brochure, the lodge advertises that 75% of its guests catch northern pike over 20 pounds. Suppose that last summer 65 out of a random sample of 88 guests did, in fact, catch northern pike weighing over 20 pounds. Does this indicate that the population proportion of guests who catch pike over 20 pounds is different from 75% (either higher or lower)? Use α = 0.05. (a) What is the level of significance? State the null and alternate hypotheses. H0: p = 0.75; H1: p ≠ 0.75 H0: p < 0.75; H1: p = 0.75 H0: p = 0.75; H1: p > 0.75 H0: p ≠ 0.75; H1: p = 0.75 H0: p = 0.75; H1: p < 0.75 (b) What sampling distribution will you use? The Student's t, since np > 5 and nq > 5. The Student's t, since np < 5 and nq < 5. The standard normal, since np < 5 and nq < 5. The standard normal, since np > 5 and nq > 5. What is the value of the sample test statistic? (Round your answer to two decimal places.) (c) Find the P-value of the test statistic. (Round your answer to four decimal places.) Sketch the sampling distribution and show the area corresponding to the P-value. WebAssign Plot WebAssign Plot WebAssign Plot WebAssign Plot (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level α? At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant. At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant. (e) Interpret your conclusion in the context of the application. There is sufficient evidence at the 0.05 level to conclude that the true proportion of guests who catch pike over 20 pounds differs from 75%. There is insufficient evidence at the 0.05 level to conclude that the true proportion of guests who catch pike over 20 pounds differs from 75%.

Socially conscious investors screen out stocks of alcohol and tobacco makers, firms with poor environmental records, and companies with poor labor practices. Some examples of "good," socially conscious companies are Johnson and Johnson, Dell Computers, Bank of America, and Home Depot. The question is, are such stocks overpriced? One measure of value is the P/E, or price-to-earnings ratio. High P/E ratios may indicate a stock is overpriced. For the S&P Stock Index of all major stocks, the mean P/E ratio is μ = 19.4. A random sample of 36 "socially conscious" stocks gave a P/E ratio sample mean of x = 17.5, with sample standard deviation s = 5.8. Does this indicate that the mean P/E ratio of all socially conscious stocks is different (either way) from the mean P/E ratio of the S&P Stock Index? Use α = 0.05. (a) What is the level of significance? State the null and alternate hypotheses. H0: μ = 19.4; H1: μ ≠ 19.4 H0: μ = 19.4; H1: μ > 19.4 H0: μ > 19.4; H1: μ = 19.4 H0: μ ≠ 19.4; H1: μ = 19.4 H0: μ = 19.4; H1: μ < 19.4 (b) What sampling distribution will you use? Explain the rationale for your choice of sampling distribution. The standard normal, since the sample size is large and σ is unknown. The Student's t, since the sample size is large and σ is unknown. The standard normal, since the sample size is large and σ is known. The Student's t, since the sample size is large and σ is known. What is the value of the sample test statistic? (Round your answer to three decimal places.) (c) Estimate the P-value. P-value > 0.250 0.100 < P-value < 0.250 0.050 < P-value < 0.100 0.010 < P-value < 0.050 P-value < 0.010 Sketch the sampling distribution and show the area corresponding to the P-value. WebAssign Plot WebAssign Plot WebAssign Plot WebAssign Plot (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level α? At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant. At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant. (e) Interpret your conclusion in the context of the application. There is sufficient evidence at the 0.05 level to conclude that the mean P/E ratio of all socially conscious stocks differs from the mean P/E ratio of the S&P Stock Index. There is insufficient evidence at the 0.05 level to conclude that the mean P/E ratio of all socially conscious stocks differs from the mean P/E ratio of the S&P Stock Index.

You wish to test the following claim ( H a ) at a significance level of α = 0.01 . H o : μ = 64.6 H a : μ < 64.6 You believe the population is normally distributed, but you do not know the standard deviation. You obtain a sample of size n = 55 with mean ¯ x = 56.7 and a standard deviation of s = 15.9 . What is the test statistic for this sample? (Report answer accurate to two decimal places.) test statistic = What is the p-value for this sample? (Report answer accurate to four decimal places.) p-value = The p-value is... less than (or equal to) α greater than α This test statistic leads to a decision to... reject the null accept the null fail to reject the null As such, the final conclusion is that... There is sufficient evidence to warrant rejection of the claim that the population mean is less than 64.6. There is not sufficient evidence to warrant rejection of the claim that the population mean is less than 64.6. The sample data support the claim that the population mean is less than 64.6. There is not sufficient sample evidence to support the claim that the population mean is less than 64.6.

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $34 and the estimated standard deviation is about $9. (a) Consider a random sample of n = 110 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution? The sampling distribution of x is not normal. The sampling distribution of x is approximately normal with mean μx = 34 and standard error σx = $0.08. The sampling distribution of x is approximately normal with mean μx = 34 and standard error σx = $0.86. The sampling distribution of x is approximately normal with mean μx = 34 and standard error σx = $9. Is it necessary to make any assumption about the x distribution? Explain your answer. It is necessary to assume that x has an approximately normal distribution. It is necessary to assume that x has a large distribution. It is not necessary to make any assumption about the x distribution because μ is large. It is not necessary to make any assumption about the x distribution because n is large. (b) What is the probability that x is between $32 and $36? (Round your answer to four decimal places.) (c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $32 and $36? (Round your answer to four decimal places.) (d) In part (b), we used x, the average amount spent, computed for 110 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen? The x distribution is approximately normal while the x distribution is not normal. The sample size is smaller for the x distribution than it is for the x distribution. The standard deviation is larger for the x distribution than it is for the x distribution. The mean is larger for the x distribution than it is for the x distribution. The standard deviation is smaller for the x distribution than it is for the x distribution. In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer? The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer. The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.

In a recent year, the Better Business Bureau settled 75% of complaints they received. (Source: USA Today, March 2, 2009) You have been hired by the Bureau to investigate complaints this year involving computer stores. You plan to select a random sample of complaints to estimate the proportion of complaints the Bureau is able to settle. Assume the population proportion of complaints settled for the computer stores is the 0.75, as mentioned above. Suppose your sample size is 198. What is the probability that the sample proportion will be within 4 percent of the population proportion?

Note: You should carefully round any z-values you calculate to 4 decimal places to match wamap's approach and calculations.

Answer =  

(Enter your answer as a number accurate to 4 decimal places.)

In a recent NY Times Editorial, Ross Douthat looks at the work of Sen and discusses how the "100 million missing women" has now increased to "160 million." He laments that the increase continues to demonstrate COMPLETELY the level of misogyny and the availability of abortions throughout the world. Based on your understanding of Emily Oster's research, what other alternate explanation(s) is/are there for some of these "missing women"?

Given the following relationship:

Shoe Size | Height (inches)

7.5 | 66

8 | 67

8 | 68

10 | 71

10.5 | 70

11 |    73

a) Letting the variable x represent shoe size and y represent height, determine the least squares regression line and correlation coefficent.

b) Based on the correlation coefficient calculated above, can the least squares regression line be confidently used as a predictor of height? Why or Why not?

SHow the work detailed. Thank you