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Tutors Answer Your Questions about Probability-and-statistics (FREE)
Question 140488: Two-Sample T-Test
We want to know whether the means of two populations on some outcome differ. For example, we want to compare two categories of males and females two populations’ age difference in purchasing concert tickets. The two-sample t-test is a hypothesis test for answering questions about the mean where the data are collected from two random samples of independent observations, each from an underlying normal distribution:
The steps of conducting a two-sample t-test are quite similar to those of the one-sample test. And for the sake of consistency, we will focus on another example dealing with ages of ticket purchase.
Returning to the two-sample t-test, the steps to conduct the test are similar to those of the one- sample test.
Establish hypotheses
The first step to examining this question is to establish the specific hypotheses we wish to examine. Specifically, we want to establish a null hypothesis and an alternative hypothesis to be evaluated with data.
In this case:
• Null hypothesis is that the difference between the two groups is 0. Another way of stating the null hypothesis is that the difference between the mean of the treatment group of ages for ticket purchasers and the mean of the men and women who purchase tickets is zero.
Calculate test statistic
Calculation of the test statistic requires three components:
1. The average of both sample (observed averages)
Statistically, we represent these as
2. The standard deviation (SD) of both averages
Statistically, we represent these as
3. The number of observations in both populations, represented as
From hospital records, we obtain the following values for these components:
men women
Average age 29.87 31.67
SD 8.45 8.10
n 15 15
With these pieces of information, we calculate the following statistic, t:
Use this value to determine p-value
Having calculated the t-statistic, compare the t-value with a standard table of t-values to determine whether the t-statistic reaches the threshold of statistical significance.
With a t-score -1.80 not significant, the p-value is 0.7218, a score that forms our basis to reject the null hypothesis and conclude that the age data for both male and female who purchase tickets are not 34.
Click here to see answer by stanbon(26259)   |
Question 140653: 12.50
In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64
large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two tailed
test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your
conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify
that F = t2 for the slope. (f) In your own words, describe the fit of this regression.
R2 0.519
Std. Error 6.977
n 64
ANOVA table
Source SS df MS F p-value
Regression 3,260.0981 1 3,260.0981 66.97 1.90E-11
Residual 3,018.3339 62 48.6828
Total 6,278.4320 63
Regression output confidence interval
variables coefficients std. error t (df = 62) p-value 95% lower 95% upper
Intercept 6.5763 1.9254 3.416 .0011 2.7275 10.4252
X1 0.0452 0.0055 8.183 1.90E-11 0.0342 0.0563
14.16
(a) Plot the data on U.S. general aviation shipments. (b) Describe the pattern and discuss possible
causes. (c) Would a fitted trend be helpful? Explain. (d) Make a similar graph for 1992–2003 only.
Would a fitted trend be helpful in making a prediction for 2004? (e) Fit a trend model of your
choice to the 1992–2003 data. (f) Make a forecast for 2004, using either the fitted trend model or
a judgment forecast. Why is it best to ignore earlier years in this data set?
U.S. Manufactured General Aviation Shipments, 1966–2003
Year Planes Year Planes Year Planes Year Planes
1966 15,587 1976 15,451 1986 1,495 1996 1,053
1967 13,484 1977 16,904 1987 1,085 1997 1,482
1968 13,556 1978 17,811 1988 1,143 1998 2,115
1969 12,407 1979 17,048 1989 1,535 1999 2,421
1970 7,277 1980 11,877 1990 1,134 2000 2,714
1971 7,346 1981 9,457 1991 1,021 2001 2,538
1972 9,774 1982 4,266 1992 856 2002 2,169
1973 13,646 1983 2,691 1993 870 2003 2,090
1974 14,166 1984 2,431 1994 881
1975 14,056 1985 2,029 1995 1,028
Click here to see answer by stanbon(26259) |
Question 140651: For the following question, each part of the question is worth 8 points.
A researcher wants to determine whether the number of minutes adults spend online per day is related to gender. A random sample of 315 adults was selected and the results are shown below. Test the claim that the number of minutes spent online per day is related to gender. Use α=0.05.
Minutes Spent Online Per Day
Gender 0 – 30 30 – 60 60 – 90 90 or over
Male 25 35 75 45
Female 30 45 45 15
a) Write the null and alternative hypotheses to test the claim that the number of minutes spent online per day is related to gender.
b) Show how you would calculate the expected number of males to spend 60-90 minutes online. Do not carry out the calculations. However, show how you would calculate the expected value.
c) How many degrees of freedom should you use to determine the critical value? Explain how you arrived at that number of degrees of freedom.
d) Suppose that the value of the χ2 test statistic is 18.14 and suppose that the critical value is 7.815. What conclusion would draw about the null hypothesis? Explain what numbers you are comparing to decide whether to reject or fail to reject the null hypothesis.
e) State your conclusion in terms of the original claim and indicate why you are justified in making this conclusion.
Click here to see answer by stanbon(26259) |
Question 140714: In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald’s employees. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t2 for the slope. (f) In your own words, describe the fit of this regression.
R2 0.202
Std. Error 6.816
n 35
ANOVA table
Source SS df MS F p-value
Regression 387.6959 1 387.6959 8.35 .0068
Residual 1,533.0614 33 46.4564
Total 1,920.7573 34
Regression output confidence interval
variables coefficients std. error t (df = 33) p-value 95% lower 95% upper
Intercept 30.7963 6.4078 4.806 .0000 17.7595 43.8331
Slope 0.0343 0.0119 2.889 .0068 0.0101 0.0584
Click here to see answer by stanbon(26259) |
Question 140734: Easy Eye, Inc. manufactures adult sunglasses of all types. The company’s management is not sure whether to target the next promotional campaign primarily toward men or women and has asked the research team to determine whether the market for sunglasses is split in half. A study is conducted at various cooperating stores selling sunglasses scattered throughout the market area. In a random sample of 300 adult purchasers of sunglasses, 141 were men.
If "Pi" is the proportion of adult sunglass purchasers who are men, what is the appropriate null hypothesis for Easy Eye, Inc. to test?
a. H0: Pi = 0.5
b. H0: Pi "not equal to" 0.5
c. H0: Pi >= 0.5
d. H0: Pi <= 0.5
What is the value of the test statistic?
a. –0.06
b. –0.50
c. –1.04
d. –2.54
Based on the data and at "a" = 0.05, what can Easy Eye’s management conclude?
a. An equal proportion of men and women are buying sunglasses in the market area.
b. A greater proportion of women buy sunglasses than do men in the market area.
c. A greater proportion of men buy sunglasses than do women in the market area.
d. There is not an equal proportion of men and women buying sunglasses in the market area.
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Question 140732: The appropriate null hypothesis for an upper-tail test to determine if mean body weight of all the men who have joined a health club exceeds 185 pounds would be
a. HO: u = 185 lb.
b. HO: u > 185 lb.
c. HO: u <= 185 lb
d. HO: u "not equal to" 185 lb
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Question 140779: 9.62 The Web-based company Oh Baby! Gifts has a goal of processing 95 percent of its orders on the
same day they are received. If 485 out of the next 500 orders are processed on the same day, would
this prove that they are exceeding their goal, using α = .025? (See story.news.yahoo.com accessed
June 25, 2004.)
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Question 140836: Please help. I submitted this question earlier in the week and have not heard anything back. I am unablt to put the columns side by side.
Provide following information... This is the time for you to pull out allof your statistical tricks(descriptive statistics, inferential statistics(parametric and nonparametric.)Of course all must your calculations must have a purpose, not calculating just for the sake of calculating.
Please paste your results into the post if you can. If you attach a spreadsheet, please provide a detailed explanation about whats in the spreadsheet if you do indeed post a spreadsheet.
Please explain the process of analyzing the information, not just a list of answers.
Price($) cc
6.24
4.79
5.96
4.7
4.11
3.85
2.52
5.46
6
3.71
6.7
4.99
4.1
5.96
6.31
6.42
7.79
5.05
5.26
5.84
7.22
6.12
7.37
6.47
6.72
7.59
6.36
6.52
6.34
7.1
4.78
4.63
5.41
6.39
5.52
6.38
5.68
5.82
5.83
7.8
2.82
3.2
3.83
4.02
3.88
4.79
4
3.95
3.27
4.02
3.26
3.19
2.9
2.36
3.93
4.25
4.03
4.02
2.86
4.03
4.02
6.49
3.24
3.6
2.99
2.75
3.9
5.42
5.63
Calories
159
160
160
162
157
151
155
135
162
142
146
148
170
160
172
170
184
201
155
170
158
159
150
177
146
151
163
186
168
142
148
150
140
150
160
160
148
148
148
160
145
142
147
148
149
155
159
148
143
137
153
143
144
133
143
143
134
110
110
105
96
95
58
82
60
72
70
71
96
%Alcohol Content
5.2
5
4.9
4.9
5.5
4.9
4.7
5.1
5.4
4.8
4.4
4.3
5.1
5
5.8
5.9
6
5.6
4.7
5.3
4.9
5.4
5.1
5.6
3.7
4.9
5.3
5.9
5.9
4.7
5
5
5
5
4.8
5
4.6
4.9
4.3
4.1
4.5
4.4
5
4.9
5.5
5.6
5
5.5
4.9
4.6
4.6
5
4.7
4.6
5
4.6
4.3
4.2
4.2
4.2
4.5
3.6
0
0
0
0
0
0
0
Type
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
Country of Origin
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
0
0
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Question 140829: How does correlation analysis differ from regression analysis?
What does a correlation coefficient reveal?
State the quick rule for a significant correlation and explain its limitations.
What sums are needed to calculate a correlation coefficient?
What are the two ways of testing a correlation for significance?
Click here to see answer by stanbon(26259) |
Question 140886: A manufacturer produces a batch of memory chips (RAM) and measures the mean-time-between-failures (MTBF). The manufacturer then changes a manufacturing process and produces another batch and again measures the MTBF. Did the change to the process improve the MTBF?
Click here to see answer by stanbon(26259) |
Question 140891: A linear regression between Y and X produced the following equation for the least squares line:
= 2.15 – 3.2x
Which of the following statements concerning this relationship is true?
a. For every one-unit increase in X, Y increases 3.2 units.
b. For every one-unit increase in Y, X decreases 3.2 units.
c. For every one-unit increase in X, Y decreases 3.2 units.
d. For every one-unit increase in Y, X increases 3.2 units.
Click here to see answer by stanbon(26259) |
Question 140890: The least squares method finds the equation of the line that __________ the __________ of the squared deviations between the points and the line.
a. maximizes, sum
b. minimizes, product
c. minimizes, sum
d. maximizes, product
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Question 140889: The technique that is used to determine if more than two population means are equal by analyzing the variation in the data is known as
a. chi-square.
b. analysis of variance.
c. correlation analysis.
d. least squares regression.
Click here to see answer by stanbon(26259) |
Question 140937: Suppose that a random sample of fifteen recently sold houses in a certain city has a mean sales price of $285,000, with a standard deviation of $5000. Under the assumption that house prices are normally distributed, find a 90% confidence interval for the mean sales price of all houses in this community.
Carry your intermediate computations to at least three decimal places. Round your answers to the nearest whole number
What is the lower limit of the confidence interval?
What is the upper limit of the confidence interval?
I think i knew how to do this once, but am not sure what formula to use now. Any help would be greatly appreciated!
Thank you in advance.
Click here to see answer by stanbon(26259) |
Question 140971: Please help with this problem, it has been revised.
A researcher used stepwise regression to create regression models to predict Birth Rate (births per 1,000) using five predictors: Life Exp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
Regression Analysis—Stepwise Selection (best model of each size)
153 observations
Birth Rate is the dependent variable
p-values for the coefficients
Nvar Life Exp InfMort Density GDPCap Literate s Adj R2 R2
1 .0000 =(infmort) 6.318=(s) .722=(adjr2) .724=(r2)
2 .0000= (infmort).0000=(literate) 5.334=(s) .802=(adjr2) .805=(r2)
3 .0000 =(infmort).0242=(gdpcap) .0000=(literate) 5.261=(s) .807=(adjr2) .811=(r2)
4 .5764=(lifeexp) .0000=(Infmort) .0311=(gdpcap) .0000=(literate) 5.273=(s) .806=(adjr2) .812= (r2)
5 .5937=(lifeexp) .0000=(infmort) .6289=(density) .0440=(gdpcap) .0000=(literate) 5.287=(s) .805=(adjr2) .812=(r2)
Click here to see answer by stanbon(26259) |
Question 140965: Faced withe rising fax costs a firm issued guideline that transmissions of 10 pages or more should be sent by 2 day mail instead. Exceptions are allowed, but they want the average to be 10 or below. The firm examined 35 randomly chosen fax transmissions during the next year, yielding a sample mean of 14.44 with a standard deviation of 4.45 pages. At a .01 level of significance, is the true mean greater than 10? Use excel to find the right tail p value.
Click here to see answer by stanbon(26259) |
Question 140962: Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
Sally’s Beauty Salon just opened for business. Sally assigns the stylists customers on a rotation basis so that everyone is kept busy all day. One month after she opened the salon, Sally’s customer count for each stylist was (a) 20 customers; (b) 30 customers; (c) 15 customers; and (d) 25 customers. Has Sally been fair in how she allocates customers to each of the stylists? ____
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Question 140976: A digital camcorder repair service has set a goal not to exceed an average of 5 working days from the time the unit is brought in to the time repairs are completed. A random sample of 12 repair records showed the following repair (in days) 9,2,5,1,5,4,7,5,11,3,7,2. At a=.05 is the goal being met?
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Question 140961: Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
Mel’s Diner has been surveying their customers for the past couple of years about their dining experience in the restaurant. The survey uses a scale of one to five, five being best to indicate customer satisfaction. Mel’s customer satisfaction averaged 2.5 last year, but this year it is 2.9. Is this difference statistically significant? ____
Click here to see answer by stanbon(26259) |
Question 140960: Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
A study to determine if job absenteeism is distributed evenly over the week. ____
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Question 140994: (a) How does correlation analysis differ from regression analysis?
(b) What does a correlation
coefficient reveal?
(c) State the quick rule for a significant correlation and explain its limitations.
(d) What sums are needed to calculate a correlation coefficient?
(e) What are the two ways of testing a correlation coefficient for significance?
Click here to see answer by stanbon(26259) |
Question 140993: Horace Mann, principal of Jones Public School, has decided to construct a time series model to obtain a 2- and a 3-period moving average to forecast student enrollments for next term. Which statement is true concerning the accuracy of each forecast that Horace will obtain?
a. The 2-period forecast will be more accurate than the 3-period forecast.
b. The 3-period forecast will be more accurate than the 2-period forecast.
c. Both forecasts will be equally accurate.
d. Either forecast could be more accurate than the other.
Click here to see answer by stanbon(26259) |
Question 140959: Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
Jim Smith owns three real estate offices in Anytown. He has decided to open one more office, but he cannot decide between Hometown or Uptown as the town where he wants to locate. He will be comparing the mean number of homes sold per real estate agent, and the mean commission percentage earned by agents in the two towns to make his decision. ____
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Question 140780: The following time series data represent the yearly amounts spent on advertising (in millions of dollars) by a large toy company:
32.3, 28.5, 31.2, 31.1, 32.9, 28.6, 37.9
This series of data begins in year 1996 (i.e., time period t= 1 corresponds to 1996 ). Using regression analysis, a linear trend line of the form Tt = 29.08 +0.68t was fit to the data. Using this information, generate a forecast for the total yearly amount of money that will be spent on advertising in 2008.
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Question 140958: Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
A catering company is buying equipment in order to set up their own store. They have a choice of two ovens that they can purchase for the store. The used oven is $100 less than the new oven, but its heating calibration is off by 20 degrees. Which one is a better buy for them? ____
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Question 140775: Parametric and Nonparametric Data Identification Assignment
Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
From a written survey where the respondents were asked to rate an individual on a scale of 1 to 5, one group rated an individual a 3.7, another group rated the individual a 4.3. Is the difference statistically significant? ____
Please
Click here to see answer by stanbon(26259) |
Question 140721: A researcher used stepwise regression to create regression models to predict BirthRate (births per
1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate),
Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
Regression Analysis—Stepwise Selection (best model of each size)
153 observations
BirthRate is the dependent variable
p-values for the coefficients
Nvar-----LifeExp-----InfMort-----Density-----GDPCap-----Literate-----s-----Adj R2-----R2
1-------------------- .0000--------------------------------------------- 6.318--- .722----- .724
2-------------------- .0000---------------------------------- .0000---- 5.334--- .802----- .805
3-------------------- .0000---------------------- .0242----- .0000---- 5.261--- .807----- .811
4--------- .5764----- .0000--------------------- .0311----- .0000---- 5.273--- .806----- .812
5--------- .5937----- .0000------- .6289------- .0440----- .0000---- 5.287--- .805----- .812
Click here to see answer by stanbon(26259) |
Question 140897: 13.30
A researcher used stepwise regression to create regression models to predict Birth Rate (births per 1,000) using five predictors: Life Exp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
Regression Analysis—Stepwise Selection (best model of each size)
153 observations
Birth Rate is the dependent variable
p-values for the coefficients
Nvar Life Exp InfMort Density GDPCap Literate s Adj R2 R2
1 .0000 =(infmort) 6.318=(s) .722=(adjr2) .724=(r2)
2 .0000= (infmort).0000=(literate) 5.334=(s) .802=(adjr2) .805=(r2)
3 .0000 =(infmort).0242=(gdpcap) .0000=(literate) 5.261=(s) .807=(adjr2) .811=(r2)
4 .5764=(lifeexp) .0000=(Infmort) .0311=(gdpcap) .0000=(literate) 5.273=(s) .806=(adjr2) .812= (r2)
5 .5937=(lifeexp) .0000=(infmort) .6289=(density) .0440=(gdpcap) .0000=(literate) 5.287=(s) .805=(adjr2) .812=(r2)
Click here to see answer by stanbon(26259) |
Question 140720: A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
Regression Analysis—Stepwise Selection (best model of each size)
153 observations
BirthRate is the dependent variable
p-values for the coefficients
Nvar LifeExp InfMort Density GDPCap Literate s Adj R2 R2
1 .0000 6.318 .722 .724
2 .0000 .0000 5.334 .802 .805
3 .0000 .0242 .0000 5.261 .807 .811
4 .5764 .0000 .0311 .0000 5.273 .806 .812
5 .5937 .0000 .6289 .0440 .0000 5.287 .805 .812
Click here to see answer by stanbon(26259) |
Question 140622: A researcher used stepwise regression to create regression models to predict BirthRate (births per
1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate),
Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
Regression Analysis—Stepwise Selection (best model of each size)
153 observations
BirthRate is the dependent variable
p-values for the coefficients
Nvar-----LifeExp-----InfMort-----Density-----GDPCap-----Literate-----s-----Adj R2-----R2
1--------------------- .0000--------------------------------------------- 6.318--- .722----- .724
2--------------------- .0000---------------------------------- .0000---- 5.334--- .802----- .805
3--------------------- .0000------------------- .0242----- .0000---- 5.261--- .807----- .811
4-------- .5764----- .0000------------------- .0311----- .0000---- 5.273--- .806----- .812
5-------- .5937----- .0000------- .6289------ .0440----- .0000---- 5.287--- .805----- .812
Click here to see answer by stanbon(26259) |
Question 140456: Parametric and Nonparametric Data Identification Assignment
Label each of the following situations “P” if it is an example of parametric data or “NP” if it is an example of nonparametric data.
A manufacturer produces a batch of memory chips (RAM) and measures the mean-time-between-failures (MTBF). The manufacturer then changes a manufacturing process and produces another batch and again measures the MTBF. Did the change to the process improve the MTBF? ____
Click here to see answer by stanbon(26259) |
Question 140361: A linear regression between Y and X produced the following equation for the least squares line:
= 2.15 – 3.2x
Which of the following statements concerning this relationship is true?
a. For every one-unit increase in X, Y increases 3.2 units.
b. For every one-unit increase in Y, X decreases 3.2 units.
c. For every one-unit increase in X, Y decreases 3.2 units. (I CHOSE C)
d. For every one-unit increase in Y, X increases 3.2 units.
11. Horace Mann, principal of Jones Public School, has decided to construct a time series model to obtain a 2- and a 3-period moving average to forecast student enrollments for next term. Which statement is true concerning the accuracy of each forecast that Horace will obtain?
a. The 2-period forecast will be more accurate than the 3-period forecast.
b. The 3-period forecast will be more accurate than the 2-period forecast.
c. Both forecasts will be equally accurate.
d. Either forecast could be more accurate than the other. (I CHOSE D)
Click here to see answer by stanbon(26259) |
Question 140624: Explain regression analysis. Explain how the linear equation Y=MX + B applies to regression analysis. What is the difference between regression and correlation. Provide an example of regression analysis, please.
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Question 140333: Please help!
In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald’s employees. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t2 for the slope. (f) In your own words, describe the fit of this regression.
Regression output confidence interval
variables coefficients std. error t (df = 33) p-value 95% lower 95% upper
Intercept 30.7963 6.4078 4.806 .0000 17.7595 43.8331
Slope 0.0343 0.0119 2.889 .0068 0.0101 0.0584
ANOVA table
Source SS df MS F p-value
Regression 387.6959 1 387.6959 8.35 .0068
Residual 1,533.0614 33 46.4564
Total 1,920.7573 34
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Question 140478: An expert witness in a case of alleged racial discrimination in a state University school of nursing introduced a regression of the deyerminates of salary of esch professionfor esch yesr during a eight-year period (n=423) with the following results, with dependent variable year (year in whichthe salary was observed) and predictors year hire(yesr when the individual was hired), Race ( 1 if individual is black, 0 otherwise), and rank ( 1 if individual is an assistant professor, 0 otherwise). Interpret these results.
Variable Coefficient t p
Interpret -3,816,521 -29.4 .000
Year 1,948 29.8 .000
Year Hire -826 -5.5 .000
Race -2,093 -4.3 .000
Rank -6,438 -22.3 .000
RR2 = 0.811 R2adi=0.809 .000
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Question 141132This question is from textbook Applied Statistics in Business and Economics
: In this exercises, include MegaStat, Excel, or MINITAB exhibits to support your calculations.
State the hypotheses, show how the degrees of freedom are calculated, find the critical value of chisquare
from Appendix E or from Excel’s function =CHIINV(alpha, deg_freedom), and interpret the p-value.
Tell whether the conclusion is sensitive to the level of significance chosen, identify cells that contribute
the most to the chi-square test statistic, and check for small expected frequencies. If necessary, you can
calculate the p-value by using Excel’s function =CHIDIST(test statistic,deg_freedom). Note: Exercises marked
* are harder or require optional material.
15.22 A student team examined parked cars in four different suburban shopping malls. One hundred vehicles
were examined in each location. Research question: At α = .05, does vehicle type vary by
mall location? (Data are from a project by MBA students Steve Bennett, Alicia Morais, Steve
Olson, and Greg Corda.)
Vehicle Type Somerset Oakland Great Lakes Jamestown Row Total
Car 44 49 36 64 193
Minivan 21 15 18 13 67
Full-sized Van 2 3 3 2 10
SUV 19 27 26 12 84
Truck 14 6 17 9 46
Col Total 100 100 100 100 400
This question is from textbook Applied Statistics in Business and Economics
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Question 141131This question is from textbook Applied Statistics in Business and Economics
: In this exercises, include MegaStat, Excel, or MINITAB exhibits to support your calculations.
State the hypotheses, show how the degrees of freedom are calculated, find the critical value of chisquare
from Appendix E or from Excel’s function =CHIINV(alpha, deg_freedom), and interpret the p-value.
Tell whether the conclusion is sensitive to the level of significance chosen, identify cells that contribute
the most to the chi-square test statistic, and check for small expected frequencies. If necessary, you can
calculate the p-value by using Excel’s function =CHIDIST(test statistic,deg_freedom). Note: Exercises marked
* are harder or require optional material.
Employees of Axolotl Corporation were sampled at random from pay records and asked to complete
an anonymous job satisfaction survey, yielding the tabulation shown. Research question: At
α = .05, is job satisfaction independent of pay category? Employees
688 Applied Statistics in Business and Economics
Pay Type Satisfied Neutral Dissatisfied Total
Salaried 20 13 2 35
Hourly 135 127 58 320
Total 155 140 60 355
This question is from textbook Applied Statistics in Business and Economics
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