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The management of a large firm would like to know something about employee morale and the other variables to which it may be related.  To study these relationships, each employee in a simple random sample of 27 employees is interviewed and tested to obtain information concerning morale level and the average number of satisfying extra work social contacts experienced during a week.  Whether or not the duties the employee usually performs are appropriate to the job title is also determined.  The dependent variable Y is measure of morale, the quantitative independent variable, X1 is average number of social contacts, and the following dummy variable coding is used to quantify the qualitative variable: X2 = 1 if yes, X2 = 0 if no. The model including dummy variable and the interaction term was being estimated and a part of computer outputs is below:   beta std error t p-value 95% CI for B             Lower bound Upper bound Constant 260 134.308…

The management of a large firm would like to know something about employee morale and the other variables to which it may be related. To study these relationships, each employee in a simple random sample of 27 employees is interviewed and tested to obtain information concerning morale level and the average number of satisfying extra work social contacts experienced during a week. Whether or not the duties the employee usually performs are appropriate to the job title is also determined. The dependent variable Y is measure of morale, the quantitative independent variable, X1 is average number of social contacts, and the following dummy variable coding is used to quantify the qualitative variable: X₂ = 1 if yes, X₂ = 0 if no. The model including dummy variable and the interaction term was being estimated and a part of computer outputs is below:

States (and provinces) that have control over taxation sometimes reduce taxes in an attempt to spur economic growth. Suppose that you are hired by a state to estimate the effect of corporate tax rates on, say, the growth in per capita gross state product (GSP).(i) What kind of data would you need to collect to undertake a statistical analysis?(ii) Is it feasible to do a controlled experiment? What would be required?(iii) Is a correlation analysis between GSP growth and tax rates likely to be convincing? Explain.

Hotel Prices. Hotel room pricing changes over time (Lodging Magazine), but is there a difference between Europe hotel prices and U.S. hotel prices? The file IntHotels contains changes in the hotel prices for 47 major European cities and 53 major U.S. cities. a On the basis of the sample results, can we conclude that the mean change in hotel rates in Europe and the United States are different? Develop appropriate null and alternative hypotheses. b Use a.01. What is your conclusion?

five-star restaurant has the business objective of improving customer waiting time during the noon-to-1 p.m. lunch period. The manager decides to compare the waiting time between the restaurant's two locations. A random sample of 15 customers was selected from Location 1, and another random sample of 15 customers was selected from location 2 on the same day. The waiting times collected from both samples are stored in the following table.   Location 1 Location 2 4.21 9.66 5.55 5.90 3.02 8.02 5.13 5.79 4.77 8.73 2.34 8.01 3.54 8.35 3.20 10.49 4.50 6.68 6.10 5.64 0.38 4.08 5.12 6.17 6.46 9.91 6.19 5.47 3.79 3.82   At a 0.05 level of significance, is there evidence of a difference in the means waiting time between the two locations? Determine the p-value in (a) and interpret its meaning. What assumption about the population distribution of each location is necessary for (a)? Is the…

We are studying the factors that contribute to unemployment at an individual level. UE, unemployment, is our dependent variable and it is a binary variable that takes the value 1 if an individual is unemployed and 0 if they are employed. We have a random sample and we estimate the following model: UE^= 0.508−0.051educ−0.023urban+0.005age(0.122)  (0.012)          (0.005)            (0.002)n=6214,  R2=0.474 where educ = an individual’s years of education urban = a dummy equal to 1 if the individual lives in an urban area and 0 otherwise age = an individual’s age in years What is the correct interpretation of the estimated coefficient on education?

7. A television station wishes to study the relationship between viewership of its 11 p.m. news program and viewer age (18 years or less, 19 to 35, 36 to 54, 55 or older). A sample of 250 television viewers in each age group is randomly selected, and the number who watch the station’s 11 p.m. news is found for each sample. The results are given in the table below.

Tourism patterns are difficult to forecast; they normally vary from country to country and sometimes even between places quite close to each other. In Hong Kong, a survey asked 1,600 people their favorite Asian destination for a short holiday. The results were as follows: 43% go to China, 23% go to Thailand, 20% go to the Philippines, 5% go to Cambodia, and the rest choose other countries. The same survey has been carried out in Macau, China only 1 hour from Hong Kong by jet boat, and the results were as follows: 48%, China; 20%, Thailand; 22%, the Philippines; 3%, Cambodia; and the remaining, other destinations. Would you conclude that the patterns are the same in the two cities?

Coku-cola and Pepusi are two duopoly cola brands in the coke market. A market research had been conducted to show the preference of the customers. In the research, one of the element of coke, sweetness, was evaluated, scaling 0 to 1, as an indicator from lighter to sweeter. Based on the research, customers who preferred lighter coke would tend to choose Coku-cola, whereas customers who preferred sweeter coke would choose Pepusi. Investigators also found that the willing-to-pay price of the customers toward their preference was based on the scale of sweetness. The intangible cost to force a sweet-preferred customer to choose a light coke is $1, vice versa. For example, a customer who prefer 0.6 sweetness would buy a perfectly light coke by adding cost $0.6 or buy a perfectly sweet coke by adding $0.4. The sweetness of both brands were tested by a sweetness tester. The result came out that the sweetness of Coku-cola is 0 while the sweetness of Pepusi is 1. Assume the preference of…

Identify the appropriate test to use for the following scenarios: The population of American adults watch 238 minutes of TV per day on average. I believe that providing adults with bicycles will decrease the daily TV-watching. I provide bicycles to 500 American adults and then measure their daily TV watching. The sample watched 204 minutes of TV per day on average. Did the bicycles decrease TV watching? Group of answer choices A)One-Sample T-Test B) Independent Groups T-Test C)Correlated Groups T-Test D) Linear Regression

A tea company appoints four salesmen A, B, C and D and observes their sales in three months, April, May and June:   Months       Salesmen                   A   B   C D               April 36   36   21 35 May 28   29   31 32 June 26   28   29 29                             Prepare a two – way analysis of variance table Name the blocking variable and the treatment in this experiment. Test at the 5% level of significance the null hypothesis that there is significant difference in sales made by the four salesmen                     Test at the 5% level of significance the null hypothesis that there is significant difference in the sales made during different months.

You are volunteering for a local nonprofit organization whose mission is to improve child literacy. This organization has asked for your help gathering information on the reading activities that local children engage in. 1. For each of the following scenarios, state the null and alternative hypotheses. Scenario A: You read in a report that preschool-aged children have on average 5.2 books at home. You are concerned that children in your community have fewer books. Scenario B: The nonprofit recently engaged in a campaign to encourage elementary school children to read more. A previous study found that children in your community read in their free time for 48 minutes per day on average. You would like to find out whether the time spent reading among elementary school students increased after the campaign. Scenario C: Your local public library reported last year that the average number of children visiting the library each day was 77. You would like to test whether that has changed.

The manager of a men’s clothing catalog measured the market’s response to a $6 decrease in the usual price of his company’s oxford shirts by conducting a sales experiment.  An A-B split was used to divide the company’s 120,000-customer mailing list into two groups.  Customers in the control group were sent catalogs listing oxford shirts at their usual price of $40.  Customers in the test group were sent catalogs listing the price of oxford shirts at $32.80.  During the period of the test, customers in the control group purchased 700 oxford shirts, and customers in the test group purchased 889 oxford shirts. What is the independent variable in this sales experiment?  What is the dependent variable in this sales experiment? What is the percent change in price in this experiment?   What is price elasticity indicated by the results of this experiment.

We are interested in analysing the effect of the lockout laws introduced in some areas of the Sydney CBD and nearby surrounds on the number of alcohol-related violent incidents.  Suppose we have two samples of data on the number of violent incidents in a number of local areas of the Sydney CBD and nearby surrounds. Pubs, hotels and clubs located in a subset of these areas became subject to the lockout laws when they were introduced in 2014. The first sample is from 2010 before the introduction of the lockout laws, and the second is from 2015 after the introduction of the law. The hypothesis we wish to test is that the introduction of the lockout laws reduces violent incidents in the areas in which the lockout laws were put in place.  We use a difference-in-difference model on the pooled data from 2010 and 2015. We find the following results: viol_inc hat = 33.21 (5.29) + 12.43lockout (7.01) – 4.19Yr2015 (2.98) – 3.32 (lockout x Yr2015) (1.85) N = 181, R^2 = 0.128 Where: viol_incis the…

Following are the results of a study that used a case–control design. This study evaluated factors associated with admission to college. A total of 650 students were admitted to college (cases), and they were compared to 650 students who were not admitted to college (controls). The purpose of this study was to identify factors that are associated with the likelihood of being accepted into college. (8 questions) Results of a Hypothetical Study of Factors Related to Admission to College Factor                                           Odds Ratio Female gender                                             1.4 Alcohol consumption                                  0.5 Sedentary life                                              1.0 Smoking                                                      0.4 Illicit drug use                                             0.2 Regular sports practice                                2.1   True or False regarding this case–control study.   Being female was…

The blood bank at a hospital has 1,200 units of blood, out of which 37% units are of blood group B+. A clinical researcher randomly selects 300 units of blood and finds that 33% of those are of blood group B+. To test his result, he randomly selects 200 units of blood and finds that 40% of those are of blood group B+. Which of the following is the reason there is a difference between the two percentages selected by the researcher?

We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings.  We use the following model to estimate the effect of a training program on annual earnings in 2018: ln⁡(earn2018)=β0+β1train+β2ln⁡(earn2016)+β3educ+β4exper+u where earn2018 = individual total annual earnings in 2018 in dollars train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise earn2016 = individual total annual earnings in 2016 in dollars educ = the individual's years of education    exper = the individual's years of experience   We find: ln⁡(earn2018)^= 11.672 + 0.041train + 0.821ln⁡(earn2016) + 0.037educ + 0.012exper                          (5.864)   (0.019)         (0.258)                       (0.013)         (0.007) n=1278, R2= 0.048 Which of the following is the correct interpretation of the…

We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings.  We use the following model to estimate the effect of a training program on annual earnings in 2018: ln⁡(earn2018)=β0+β1train+β2ln⁡(earn2016)+β3educ+β4exper+u where earn2018 = individual total annual earnings in 2018 in dollars train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise earn2016 = individual total annual earnings in 2016 in dollars educ = the individual's years of education    exper = the individual's years of experience     Now, I want to test whether the effect of an additional year of education increases earnings by twice as much as an additional year of experience. My null hypothesis is H0:β3=2β4. To get the standard error I need to conduct this hypothesis test, I rearrange or re-parameterise…

A CBS News poll involved a nationwide random sample of 651 adults, asked those adults about their party affiliation (Democrat, Republican or none) and their opinion of how the US economy was changing ("getting better," "getting worse" or "about the same"). The results are shown in the table below. If we randomly select one of the adults who participated in this study, compute: (round to four decimal places)a.P(affiliated with neither party) = b.P(better) = c.P(better|affiliated with neither party) = d.P(affiliated with neither party|better) = e.P(affiliated with neither party and better) =

Sherwin-Williams Company is attempting to develop a demand model for its line of exterior house paints. The company’s chief economist feels that the most important variable affecting paint sales (Q) (measured in gallons) is the Selling price (P) (measured in Ghana cedis per gallon). The chief economist decides to collect data on the variables in a sample of 10 company sales regions that are roughly equal in population. Data on paint sales, and selling prices were obtained from the company’s marketing department. The data are shown in the table below:     Sherwin-Williams Company Data Sales Region Sales (Q) Selling Price (P) (GHS/Gallon) 1 160 15       2 220 13.5 3 140 16.5 4 190 14.5 5 130 17 6 160 16 7 200 13 8 150 18 9 210 12 10 190 15.5                                       Specify the linear demand model for Sherwin-William’s paint.                          Estimate the demand…

Mary Arnold wants to use the results of a random sample market survey to seek strong evidence that her brand of breakfast cereal has more than 20% of the total market. Formulate the null and alternative hypotheses, using P as the population proportion.

You are asked to perform a hypothesis test that population proportion is different from 0.35.  Which of the following is the correct statement of the null and alternative hypotheses for this test?   a H₀: π = 0.35 H₁: π ≠ 0.35 b H₀: π ≠ 0.35 H₁: π = 0.35 c H₀: π ≥ 0.35 H₁: π < 0.35 d H₀: π ≤ 0.35 H₁: π > 0.35

A company that has a 15% market share launches a marketing campaign. At the end of the campaign period, the company conducts a survey in order to assess whether its market share has increased. From a survey issued to 500 customers after the campaign, the company found that 90 of them were committed to their products.  a.  Write the null and alternative hypotheses. b.  What is the value of the test statistic? c.  What is the associated P-value? d.  State your conclusion using α = 0.05.

You are given the following demand for European luxury automobiles: Q= 1,000P-0.93 Pa0.75 Pj1.2 I1.6 Where P = Price of European luxury cars; Pa = Price of American luxury cars; Pj = Price of Japanese luxury cars; and I = Annual income of car buyers. Assume that each of the coefficients is statistically significant (i.e., that they passed the t-test). On the basis of the information given, address the following: What is the degree of substitutability between European and American luxury cars and between European and Japanese luxury cars. What is the coefficient for the income variable. What is he coefficient of the European car price variable.  Be sure to include your work for all calculations.

the unemployment rate for 18- to 34-year-olds was reported to be 10.8% (the Cincinnati Enquirer, november 6, 2012). assume that this report was based on a random sample of four hundred 18- to 34-year-olds. a. a political campaign manager wants to know if the sample results can be used to conclude that the unemployment rate for 18- to 34-years-olds is significantly higher than the unemployment rate for all adults. according to the bureau of labor Statistics, the unemployment rate for all adults was 7.9%. develop a hypothesis test that can be used to see if the conclusion that the unemployment rate is higher for 18- to 34-year-olds can be supported.b. use the sample data collected for the 18- to 34-year-olds to compute the p-value for the hypothesis test in part (a). using a 5 .05, what is your conclusion?c. explain to the campaign manager what can be said about the observed level of significance for the hypothesis testing results using the p-value

Sales of sugar-sweetened beverages at stores in Seattle dropped about 30.5% in the months after the city adopted a tax on such beverages, says a new study that also looked at sales at stores in Portland, which has no such tax.Sales in Portland declined only 10.5%, suggesting sales in Seattle dropped much more than they would have without a tax, according to the peer-reviewed study by University of Illinois at Chicago researchers.The study’s results are the first to measure the impact of Seattle’s tax on beverage sales in the city, and they may bolster claims by supporters that the controversial policy is working as intended.“From a public health perspective, this is good,” said Jay Krieger, a University of Washington professor who heads the nonprofit Healthy Food America. “People are purchasing less sugary drinks, and we know that sugary drinks are associated with heart disease, diabetes,high blood pressure and strokes.”Seattle’s tax of 1.75 cents per fluid ounce, which took effect on…

Sales of sugar-sweetened beverages at stores in Seattle dropped about 30.5% in the months after the city adopted a tax on such beverages, says a new study that also looked at sales at stores in Portland, which has no such tax.Sales in Portland declined only 10.5%, suggesting sales in Seattle dropped much more than they would have without a tax, according to the peer-reviewed study by University of Illinois at Chicago researchers.The study’s results are the first to measure the impact of Seattle’s tax on beverage sales in the city, and they may bolster claims by supporters that the controversial policy is working as intended.“From a public health perspective, this is good,” said Jay Krieger, a University of Washington professor who heads the nonprofit Healthy Food America. “People are purchasing less sugary drinks, and we know that sugary drinks are associated with heart disease, diabetes, high blood pressure and strokes.”Seattle’s tax of 1.75 cents per fluid ounce, which took effect on…

In 2009 a survey found these airline preferences for people in Southeast Asia when choosing to fly to China: 40%, Thai Airlines; 41%, Singapore Airlines; and 19%, Cathay Pacific. In 2011 this survey was repeated, and from a sample of 1,000 responders, 365 chose Thai, 540 chose Singapore, and 95 selected Cathay Pacific. Can you conclude that the consumers still have the same purchase patterns?

Why does a confidence interval contain more information than the resultof a single hypothesis test?

A salesman for a new manufacturer of cellular phones claims not only that they cost the retailer less but also that the percentage of defective cellular phones found among his products, ( p1 ), will be no higher than the percentage of defectives found in a competitor's line, ( p2 ).  To test this statement, the retailer took a random sample of 130 of the salesman's cellular phones and 110 of the competitor's cellular phones.  The retailer found that 10 of the salesman's cellular phones and 5 of the competitor's cellular phones were defective.  Does the retailer have enough evidence to reject the salesman's claim?  Use a significance level of α=0.05 for the test. Step 5 of 6 :  Determine the decision rule for rejecting the null hypothesis H0 . Round the numerical portion of your answer to three decimal places.