a) explain the type of data you have here and the hypothesis test you would use to determine the difference between the two types b) determine whether you can conclude that the mean score differs between the two types of course. You need to first set up an alternate and null hypothesis
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Permutations and Combinations
If there are 5 dishes, they can be relished in any order at a time. In permutation, it should be in a particular order. In combination, the order does not matter. Take 3 letters a, b, and c. The possible ways of pairing any two letters are ab, bc, ac, ba, cb and ca. It is in a particular order. So, this can be called the permutation of a, b, and c. But if the order does not matter then ab is the same as ba. Similarly, bc is the same as cb and ac is the same as ca. Here the list has ab, bc, and ac alone. This can be called the combination of a, b, and c.
Counting Theory
The fundamental counting principle is a rule that is used to count the total number of possible outcomes in a given situation.
Do parts a nd b
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- Urban Travel Times Population of cities and driving times are related, as shown in the accompanying table, which shows the 1960 population N, in thousands, for several cities, together with the average time T, in minutes, sent by residents driving to work. City Population N Driving time T Los Angeles 6489 16.8 Pittsburgh 1804 12.6 Washington 1808 14.3 Hutchinson 38 6.1 Nashville 347 10.8 Tallahassee 48 7.3 An analysis of these data, along with data from 17 other cities in the United States and Canada, led to a power model of average driving time as a function of population. a Construct a power model of driving time in minutes as a function of population measured in thousands b Is average driving time in Pittsburgh more or less than would be expected from its population? c If you wish to move to a smaller city to reduce your average driving time to work by 25, how much smaller should the city be?6. In the book Business Research Methods (5th ed.), Donald R. Cooper and C. William Emory discuss studying the relationship between on-the-job accidents and smoking. Cooper and Emory describe the study as follows: Suppose a manager implementing a smoke-free workplace policy is interested in whether smoking affects worker accidents. Since the company has complete reports of on-the-job accidents, she draws a sample of names of workers who were involved in accidents during the last year. A similar sample from among workers who had no reported accidents in the last year is drawn. She interviews members of both groups to determine if they are smokers or not. The sample results are given in the following table.In the book Business Research Methods (5th ed.), Donald R. Cooper and C. William Emory discuss studying the relationship between on-the-job accidents and smoking. Cooper and Emory describe the study as follows: Suppose a manager implementing a smoke-free workplace policy is interested in whether smoking affects worker accidents. Since the company has complete reports of on-the-job accidents, she draws a sample of names of workers who were involved in accidents during the last year. A similar sample from among workers who had no reported accidents in the last year is drawn. She interviews members of both groups to determine if they are smokers or not. The sample results are given in the following table. On-the-Job Accident Smoker Yes No Row Total Heavy 12 5 17 Moderate 9 10 19 Nonsmoker 13 17 30 Column total 34 32 66 Expected counts are below observed counts Accident No Accident Total Heavy 12 5 17 8.76 8.24…
- 13.4 #8 A research article on the effect of multitasking on grade performance describes an experiment in which 62 undergraduate business students were randomly assigned to one of two experimental groups. Students in one group were asked to listen to a lecture but were told that they were permitted to use cell phones to send text messages during the lecture. Students in the second group listened to the same lecture but were not permitted to send text messages. Afterwards, students in both groups took a quiz on material covered in the lecture. Data from this experiment are summarized in the accompanying table. ExperimentalGroup GroupSize Mean QuizScore StandardDeviation ofQuiz Scores Texting 31 42.56 9.24 No Texting 31 58.61 10.76 Use the given information to construct a 90% confidence interval for the difference in mean quiz score for the two treatments (texting allowed and texting not allowed). (Use ?no texting − ?texting. Use SALT. Round your answers to three…(a) The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. As such, he is interested in investigating the association between the age of the respondents and their knowledge level. Table 2 below shows the knowledge level of respondents, by age group. Table 2 Age Group Knowledge Level Total Poor Satisfactory Good 18 - 25 33 16 13 62 26 - 34 30 18 12 60 35 - 44 29 14 12 55 45 - 54 36 16 18 70 55 - 75 17 14 22 53 Total 145 78 77 300 Conduct a test, at the 5% level of significance, to determine whether the data provided sufficient evidence to conclude that an association exists between age group and knowledge level. (i) State the hypotheses to be tested: H0: H1: Calculate: (ii) state the degrees of freedom for this test (iii)…a) The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. As such, he is interested in investigating the association between the age of the respondents and their knowledge level. Table 2 below shows the knowledge level of respondents, by age group. Table 2 Age Group Knowledge Level Total Poor Satisfactory Good 18 - 25 33 16 13 62 26 - 34 30 18 12 60 35 - 44 29 14 12 55 45 - 54 36 16 18 70 55 - 75 17 14 22 53 Total 145 78 77 300 Conduct a test, at the 5% level of significance, to determine whether the data provided sufficient evidence to conclude that an association exists between age group and knowledge level. (i) State the hypotheses to be tested: H0: H1: Calculate: (ii) state the degrees of freedom for this test (iii)…
- In a study examining the permanence of academic learning, Bahrick and Hall (1991) tested knowledge of high school algebra for two groups of participants 50 years after they graduated from high school. One group had received additional college math courses and the other group had received no advanced math courses in college. The following table shows data similar to Bahrick and Halls results. No College Math Additional Math n = 4 n = 8 M = 42 M = 50 s2 = 33.333 s2 = 20 1) Do the data indicate a significant difference between the two groups? Use a two- tailed test with α = .05. Report and interpret r2.3) The following two sets of Excel output use are from the same data set as described above, but the first set of output is for the set of 35 CEO’s that earn the lowest total compensation and the second set of output is for a set of 40 CEO’s that earn the highest total compensation. a) What is heteroscedasticity? b) Why is heteroscedasticity a problem? c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain.SCENARIO 7 Suppose a group is interested in determining whether teenagers obtain their drivers licenses at approximately the same average age across the country. Suppose that the following data are randomly collected from five teenagers in each region of the country. The numbers represent the age at which teenagers obtained their drivers licenses. Use a level of significance of 0.10. Northeast South West Central 16.3 16.9 16.4 16.2 16.1 16.5 16.5 16.6 16.4 16.4 23.0 16.5 16.5 16.2 20.2 16.4 Question 45 Listen Which test are you running? Question 45 options: ANOVA Chi-Square Goodness of Fit One mean t-test One-mean z-test Question 46 Listen What is the null hypothesis? Question 46 options: Ho:The mean ages for teenagers obtaining their drivers licenses…
- The following table was presented in a article summarizing a study to compare a new drug to a standard drug and to a placebo. characteristic new drug stand. drug placebo p age,yrs 45.2(4.8) 44.9(5.1) 42.8(4.3) 0.5746 % female 50% 55% 57% 0.1635 annual income,$000s 59.5%(14.3) 63.8(16.9) 58.2%(13.1) 0.4635 % w/ins 87% 65% 82% 0.0352 disease stage 0.0261 stage 1 35% 18% 33% stage 2 42% 37% 47% stage 3 23% 51% 20% Are there any statistiscally significant differences…TABLE 1 The director of cooperative education at a state college wants to examine the effect of cooperative education job experience on marketability in the work place. She takes a random sample of 4 students. For these 4, she finds out how many times each had a cooperative education job and how many job offers they received upon graduation. These data are presented in the table below. Student CoopJobs JobOffer 1 1 4 2 2 6 3 1 3 4 0 1 Referring to Table 1, set up a scatter plot with Coop Jobs as the horizontal axis and Job offer as the vertical axis12.25 Infusionsoft conducted a study to explore the attitudes, behaviors, and challenges that small businesses face related to sales and marketing. Small business owners were categorized by the amount they spend per month on marketing activities as well as the attitudinal segment to which they belong. Results were organized into the following table. AttitUdinAl sEGmEnt sPEnd PER montH on mARkEtinG ActiVitiEs Less than $200 $200–$1,000 $1000+ Total Freedom Seekers 89 64 40 193 Passionate Creators 64 82 63 209 Struggling Survivors 87 66 48 201 Legacy Builders 122 63 49 234 Total 362 275 200 837 Source: Data extracted from 2015 Infusionsoft Small Business Market Research Sales & Marketing Report, bit.ly/1x8t9r2. At the 0.05 level of significance, is there evidence of a significant relationship between amount spent per month on marketing activities and attitudinal segment?