Improving driving performance while fatigued. Refer to the Human Factors (May, 2014) study of driving performance while fatigued, Exercise 9.31 (p. 521). Recall that the researchers had 40 college students drive a long distance in a simulator. While driving, each student performed a task. One group of student-drivers performed a verbal task continuously (continuous verbal condition); another group performed the task only at the end of the drive (late verbal condition); a third group did not perform the task at all (no verbal condition); and, the fourth group listened to a program on the car radio (radio show condition). The dependent variable of interest was the percentage of billboards recalled by the student-driver. The data are listed in the table on the next page.
- a. Write a model for
mean recall percentage, E(y), as afunction of task group (continuous verbal, late verbal, no verbal, and radio show). Use radio show as the base level for the qualitative independent variable, task group. - b. Measures of
central tendency for the recall percentage measurements of each task group are displayed in the accompanying Minitab printout. Use this information to estimate the β parameters of the model, part a.
- c. Fit the model, part a, to the data in the file. Use the output to verify your 13 estimates in part b.
- d. d. Refer to the output, part c. Conduct a test (at α= .01) to determine if the mean recall percentage differs for student- drivers in the four groups. Your answer should agree with that of Exercise 9.31.
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EBK STATISTICS FOR BUSINESS AND ECONOMI
- xt:Bong-Cha is deciding what to do during the 30-minute break between her college classes. One rule she could follow is, "Choose the activity with the highest value" (A). Another rule she could follow is, "Choose the activity with the lowest opportunity cost" (B). Do you think Bong-Cha's choice if she follows rule (A) will be the same as the choice she would make if she followed rule (B)? [another way to think about it, "Is rule (A) identical to rule (B) in a sense that they would both induce the same choice?"].arrow_forward“Business Ethics is the application of ethical and moral principles or in a business environment. It deals with what is right and what wrong while doing business”. But to the contrary, evidences show that some business organizations are involved in different unethical practices to increase their profit at the risk of many people’s money, health and lives. As a business ethics student you are required to address the following questions: Describe five unethical practices adopted by business organizations in Oman. You may find it form newspapers, magazines etc. or from your own experiences and observation if any. And Analyze each of these unethical practices and explain how these unethical practices affect the people and society as a whole. And Suggest the ways to overcome each of these unethical practices.arrow_forwardExercise 3.13 —*** Challenging Question ✶✶✶. Two women, Anna and Bess, claim to be the legal owners of a diamond ring that - each claims - has great sentimental value. Neither of them can produce evidence of ownership and nobody else is staking a claim on the ring. Judge Sabio wants the ring to go to the legal owner, but he does not know which of the two women is in fact the legal owner. He decides to proceed as follows. First he announces a fine of $F > 0 and then asks Anna and Bess to play the following game. Move 1: Anna moves first. Either she gives up her claim to the ring (in which case Bess gets the ring, the game ends and nobody pays the fine) or she asserts her claim, in which case the game proceeds to Move 2. Move 2: Bess either accepts Anna's claim (in which case Anna gets the ring, the game ends and nobody pays the fine) or challenges her claim. In the latter case, Bess must put in a bid, call it B, and Anna must pay the fine of $F to Sabio. The game goes on to Move 3. Move…arrow_forward
- Recently the European Community (EC) decided to lower its subsidies to makers of pasta. In deciding by what amount to reduce total subsidies, experiments were carried out for determining the possible reduction in exports, mainly to the United States, that would result from the subsidy reduction. Over a small range of values, economists wanted to test whether there is a positive correlation between level of subsidy and level of exports. A computer simulation of the economic variables involved in the pasta exports market was carried out. The results follow. Assuming that the simulation is an accurate description of reality and that the values obtained may be viewed as a random sample of the populations of possible outcomes, state whether you believe that a positive rank correlation exists between subsidy level and exports level over the short range of values studied Qarrow_forwardInvestigators enrolled 2,100 women in a study and followed them monthly to determine the incidence rate of heart disease. After one month of the first period of observation, none had a new diagnosis of heart disease, but 100 had died. In the second observation period which lasted for three months, 1 had a new diagnosis of heart disease within 1 month, and another 99 died within 2 months. In the third observation period which lasted for four months, another 7 had new diagnoses of heart disease and 793 died within 2 months. Calculate the incidence rate of heart disease among this cohort. Express in 2 decimal places as number of new cases per 1,000 person-time.arrow_forwardJachuck et al. (1982) report on a drug designed to reduce hypertension (high blood pressure). Such hypotensive drugs are frequently effective but are also linked to side effects like irritability and a decline in energy. Seventy-five patients with mild hypertension were put on hypotensive drugs and their progress was monitored by doctors and spouses. When asked to rate the treated patients as improved, worse, or unchanged, the doctors rated all 75 patients as "improved." Meanwhile, the spouses rated 74 of the 75 patients as "worse." Why might spouses and doctors differ in their opinion about the effect of going on blood pressure medication?arrow_forward
- Allegiant Airlines is considering an overbooking policy for one of its flights. The airplane has 50 seats, but Allegiant is considering accepting more reservations than seats because sometimes passengers do not show up for their flights, resulting in empty seats. The PassengerAppearance worksheet in the file Overbooking contains data on 1,000 passengers showing whether or not they showed up for their respective flights. In addition, Allegiant has conducted a field experiment to gauge the demand for reservations for the current flight. During this experiment, they did not limit the number of reservations for the flight to observe the uncensored demand. The following table summarizes the result of the field experiment. No. of Reservations Demanded Probability 48 0.05 49 0.05 50 0.15 51 0.30 52 0.25 53 0.10 54 0.10 Suppose Allegiant receives a marginal profit of $108 for each passenger who books a reservation (regardless of whether they show up). In addition, suppose…arrow_forwardProblem Set #3 J) The amount of income spent on housing is an important component of the cost of living. The total costs of housing for homeowners might include mortgages payments, property taxes, and utility costs (water, heat, electricity). An economist selected a sample of Inland Empire, California, homeowners and calculated housing costs as a percent of monthly income, 5 years ago and now. The information is reported below. Is it reasonable to conclude the percent is less now than 5 years ago? Apply the 6-step hypothesis testing procedure to test using a = 5% (0.05). (LMW) Five Years Now Ago Aziz 18 11 Baker 19 38 Cortez 28 36 Duran 42 26 Edgewort 35 11 Foster 44 42 Gomez 46 Hochhack 20 27 Isoko 48 27 Jarvis 48 25 Kenda 36 33 Li 17 33 Morales 24 22 Nasser 32 11 Oliphant 43 39 Pierce 45 43 Quest 29 23 Rawlins 28 18 Sorrento 40 36 Thomas 23 13arrow_forwardAn economist collects data regarding the number of jobs an individual has held by age 21. Tim states he had 4 jobs, Sam had 3, Jill had 3, Sally had 2, and Watney had 10.An economist should use the to draw conclusions. A typical individual had jobs by the age 21.arrow_forward
- 6. Imagine that I wanted to test the proposition that people think older politicians are more trustworthy. I recruited an internet sample of 90 people. Each person was asked to read a short article about a hypothetical political candidate. Random assignment determined whether the subjects were told that candidate was 65 or whether they were told that candidate was 35. After reading the article, all subjects used a 10-point scale to rate the candidate on competence, trustworthiness, and likability. I take the mean values of trustworthiness in each group, perform a difference of means test, and find a test statistic of 1.04. Should I reject the null at the 99% confidence level? Why or why not? What does that mean?arrow_forwardWe 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…arrow_forwardWe 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…arrow_forward
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