Tutors Answer Your Questions about Probability-and-statistics (FREE)
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(75887)  |
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(75887) |
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.
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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(75887) |
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(75887) |
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(75887) |
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? ____
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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(75887) |
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(75887) |
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
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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(75887) |
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(75887) |
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(75887) |
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(75887) |
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(75887) |
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(75887) |
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.
Click here to see answer by stanbon(75887) |
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
Click here to see answer by stanbon(75887) |
Question 141132: 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
Click here to see answer by stanbon(75887) |
Question 141131: 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
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Question 141128: Consider a t distribution with 23 degrees of freedom. Compute
(P(t ≤ - 1.91)= . Round your answer to at least three decimal places.
Consider a t distribution with degrees of freedom. Find the value of c such that P(-c
Click here to see answer by stanbon(75887) |
Question 141211:
Trend lines for yearly data
A clothing manufacturer uses a trend line of the form to generate yearly forecasts of its total sales (in millions of dollars). The trend line was developed using a data set that starts in (i.e., time period corresponds to ).
Generate a forecast for total yearly sales during .
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Question 141200: Suppose that the heights of adult women in the United States are normally distributed with a mean of 63.5 inches and a standard deviation of 2.2inches. Jennifer is taller than 70% of the population of U.S. women. How tall (in inches) is Jennifer? Carry your intermediate computations to at least four decimal places. Round your answer to at least one decimal place.
Click here to see answer by stanbon(75887) |
Question 139352: 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(75887) |
Question 139132: Need help please.
a. What is the F critical value to be used at the 0.05 level of significance with 7 numerator degrees of freedom and 12 denominator degrees of freedom?
b. What is the chi-square critical value with 12 degrees of freedom for a 0.05 probability?
c. What is the exact probability of a value that fits a chi-square distribution with 17 degrees of freedom being higher than 30.995?
d. I have a sample of 13 units and I want to run a hypothesis test comparing the average to a set value. The hypothesis test uses an alpha of 0.05. What critical value would be used to compare the test statistic against?
Click here to see answer by stanbon(75887) |
Question 141262: Please run a chi-square test on the price of beer per bottle and the price of beer type and state the hypothesis. Please.
Price ($)
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
Type of beer
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
Click here to see answer by stanbon(75887) |
Question 141446: Faced with rising fax costs, a firm issued a 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. (a) At the .01 level of significance,
is the true mean greater than 10? (b) Use Excel to find the right-tail p-value
Click here to see answer by stanbon(75887) |
Question 141513: 1. The following information is available.
H0: µ = 50
H1: µ ≠ 50
The sample mean is 49, and the sample size is 36. The population standard deviation is 5. Use a 0.05 significance level.
Answer the questions:
(a) Is this a one- or two-tailed test?
(b) What is the decision rule?
(c) What is the value of the test statistic?
(d) What is your conclusion (in plain English) regarding H0?
Click here to see answer by Edwin McCravy(20054)  |
Question 141677: I do not understand how to make the tree diagram for this problem. I understand , or at least I think I understand, that the definates are the three coins, and the choices are heads or tails, but I keep ending up with the wrong tree. Please show me how to make the tree.
Click here to see answer by stanbon(75887) |
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7606..7650, 7651..7695, 7696..7740, 7741..7785, 7786..7830, 7831..7875, 7876..7920, 7921..7965, 7966..8010, 8011..8055, 8056..8100, 8101..8145, 8146..8190, 8191..8235, 8236..8280, 8281..8325, 8326..8370, 8371..8415, 8416..8460, 8461..8505, 8506..8550, 8551..8595, 8596..8640, 8641..8685, 8686..8730, 8731..8775, 8776..8820, 8821..8865, 8866..8910, 8911..8955, 8956..9000, 9001..9045, 9046..9090, 9091..9135, 9136..9180, 9181..9225, 9226..9270, 9271..9315, 9316..9360, 9361..9405, 9406..9450, 9451..9495, 9496..9540, 9541..9585, 9586..9630, 9631..9675, 9676..9720, 9721..9765, 9766..9810, 9811..9855, 9856..9900, 9901..9945, 9946..9990, 9991..10035, 10036..10080, 10081..10125, 10126..10170, 10171..10215, 10216..10260, 10261..10305, 10306..10350, 10351..10395, 10396..10440, 10441..10485, 10486..10530, 10531..10575, 10576..10620, 10621..10665, 10666..10710, 10711..10755, 10756..10800, 10801..10845, 10846..10890, 10891..10935, 10936..10980, 10981..11025, 11026..11070, 11071..11115, 11116..11160, 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