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- Researchers were interested in assessing whether stress levels are different at the beginning of the semester compared to finals week. To test this, stress was measured in 5 students at the start of the semester and then again at the end of the semester during finals week. Participant Stress 1 Stress 2 Difference Score (Di) (Di - Mdiff)2 1 22 22 0 2 32 34 -2 3 24 25 -1 4 28 30 -2 5 26 29 -3 What is the observed test statistic (i.e., tobs)? Round to 2 decimal places.Frequent food questionnaires (FFQ) are a simple way to obtain information on the foods individuals consume by asking them questions about typical amounts of food consumed in a day, a week, or a month. A more accurate picture is obtained by obtaining a detailed food diary (DR) for several days that are randomly chosen over a certain time period. The data obtained from a frequent food questionnaire can be compared with the food diary to assess the validity of the questionnaire. The data below are for seven individuals who participated in such a study on alcohol consumption. DR FFQ 8.26 1.68 0.83 0 20.13 15.10 11.16 7.49 7.18 12.84 1.76 0 22.66 25.06 I got a correlation of r= 0.89. Is that correct?Let's use SPSS to run a one-sample t-test! Imagine that you are interested in whether the number of hours students in a statistics course work each week differs from the average number of hours reported by the general student body at ASU. Thankfully, you have a data set that consists of information from students in a statistics course, including how many hours they work each week ("workhours"). You also happen to know that the average number of hours worked each week by the general student population at ASU is 25. Use the data provided to conduct a one sample t-test in SPSS comparing the sample data to the population mean.. The dependent variable for your test should be "workhours". Based on your output, the average number of hours worked each week by a sample is ________ . Enter your answer rounded to two decimal places (i.e., 10.01, not 10.1, not 10.0, not 10.010).
- The manager of a company that assembles and exports a particular type of pumps wants to know if there is a link between the number of hours spent by assembly workers in training and their productivity on the job. A random sample of 7 assembly workers was selected and their performances evaluated. The summary of the obtained data is listed in Table 2. Table 2: Shows the time spend by workers during training and their productivity on jobTraining hours (x) 20 36 20 38 40 33 32Output (y) 40 70 44 56 60 48 62 (i) Construct a scatter plot of the sample data and comment on the relationship between hours of training and output. (ii) Estimate a simple regression line, using the method of least squares, to identify a linear relationship between the hours of training received by assembly workers and their output (i.e. number of units assembled per day). (iii) Interpret, in context, the gradient/slope of the regression line. (iv) Estimated the output at 20 hours training time. (v) Interpret the…A school had a lot of problems with student absences and wanted to try a intervention program to see if it encouraged students to come to school more often. As a trial, 26 students were split into two equal size groups. Group 1 would get the new intervention and Group 2 got no intervention. The mean- number of absences was calculated after one month for each group, as shown in the table below. What inference can be made about the results? Group 1 Group 2 3 5 3 1 3 2 3 4 1 3 2 1 2 3 3 4 2 5 1 3 1 6 4 2 1 2 Mean: 2.2 Mean: 3.2 Frequency200 Simulated Group Mean Differences Since the simulation shows FEW CASES OR Many Cases. where a mean difference of ___ or less occurred when the groups were re-randomized, it can be inferred that the mean difference observed in the study was VERY POSSIBLY OR VERY UNLIKELY due to the random assignment of participants into groups, so the results…A professor of business statistics recently adopted a new textbook. At the completion of thecourse, a sample of randomly selected students was selected. The students were asked to assessthe book. The responses are as follows:Excellent (1), Good (2), Adequate (3), Poor (4).Do the data allow us to conlclude that more than 60% of all business students would rate the bookas excellent? amount (n) response 60 excellent 21 good 4 adequate 4 poor 89 total
- How do you find the mode of a particular column in stat crunch?8- Aresearcher randomly sampled 30 graduates of an MBA program and recorded data concerning their starting salaries. Of primary interest to the researcher was the effect of gender on starting salaries. The result of the pooled- variance t-test of the mean salaries of the females (Population 1) and males (Population 2) in the sample is given below. The researcher was attempting to show statistically that the female MBA graduates have a significantly lower mean starting salary than the male MBA graduates. The proper conclusion for this test is: Hypothesized Difference Level of Significance 0.05 Population 1 Sample Sample Size Sample Mean Sample Standard Deviation 18 99210 13577 Population 2 Sample Sample Size Sample Mean Sample Standard Deviation 12 105820 11741 Difference in Sample Means 6610 t Test Statistic -1.37631 Lower-Tail Test Lower Critical Value -1.70113 p-Value 0.089816 a) O At the a= 0.10 level, there is insufficient evidence to indicate any difference in the mean starting…Suppose that, for one semester, you can collect the following data on a random sample of college juniors and seniors for each class taken: a standardised final exam score, percentage of lectures attended, a dummy variable indicating whether the class is within the student’s major, cumulative grade point average prior to the start of the semester, and SAT score. If you pool all of the data and use OLS, what are you assuming about unobserved student characteristics that affect performance and attendance rate and What roles do SAT score and prior GPA play in this regard?
- 2. Suppose you want to test the factors that potentially affect the germination of bean. | (a) What would you use as a response variable in this experiment? How would you measure the response? (b) List the potential factors and their potential levels. (c) List all of the potential sources of variability that could impact the response.The proportion of drivers who use seat belts depends on things like age (young people are more likely to go unbelted) and gender (women are more likely to use belts). It also depends on local law. In New York City, police can stop a driver who is not belted. In Boston at the time of the study, police could cite a driver for not wearing a seat belt only if the driver had been stopped for some other violation. Here are data from observing random samples of female Hispanic drivers in these two cities. (a) Verify that the 95% CI for the difference in the proportions of female Hispanic drivers in the two cities who wear seat belts pNY −pBT is (0.149,0.353). Show your computation.(b) Determine if the following statements are true or false, and explain your reasoning if you identify the statement as false. i. There was strong evidence that pNY > pBT.ii. 95% of random samples of 220 female Hispanic drivers in New York City and 117 female Hispanic drivers in Boston will yield differences…Two surfers and statistics students collected data on the number of days on which surfers surfed in the last month for 30 longboard (L) users and 30 shortboard (S) users. Treat these data as though they were from two independent random samples. Test the hypothesis that the mean days surfed for all longboarders is larger than the mean days surfed for all shortboarders (because longboards can go out in many different surfing conditions). Use a level of significance of 0.05. Longboard: 4,10,9,4,9,8,8,6,7,9,11,11,9,15,11,16,13,11,12,18,18,13,12,15,20,22,7,24,22,24 Shortboard: 6,4,4,6,9,9,6,8,4,8,8,5,9,9,4,16,12,9,13,13,10,13,11,12,14,14,9,21,19,10 Determine the hypotheses for this test. Choose the correct answer below. C. Ho: HL Hs Hai HL # Hs Ha: HL = Hs O D. Ho: HL = Hs Ha: HL Hs F. Ho: HL # Hs Ha: HL = Hs Find the test statistic for this test. t%=D (Round to two decimal places as needed.) Find the p-value for this test. p-value = (Round to three decimal places as needed.) What is the…
