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- For which of the following pairs of variables would it be appropriate to use a chi-square to test if a significant association exists between the two variables (assuming we have met the expected counts requirement). Group of answer choices a) percentage body fat time spent each day on vigorous activity (minutes) b) Maximum oxygen uptake (mL/min/kg) Runners: Normally Active, Recreational Runners, Elite Runners c) Exercise: No regular exercise, sporadic exercise, regular exercise Student living arrangement: Dormitory, On campus apartment, off campus apartment, at home e) Staff : permanent , casual Work satisfaction: Measured using a group of survey questions, whose answers are then scored and combined to give a final score for satisfaction that falls between 0 and 100, with 100 indicating very high satisfactionThe data shows 10 randomly selected people being asked how old is their car and how many miles are on it. Use the age of the car for the independent variable and the miles on the car for the dependent variable. Use an alpha = 0.05. Person 1: 4 years, 83, 420 miles. Person 2: 4 years, 54 917 miles. Person 3: 13 years, 128, 609 miles. Person 4: 2 years, 15,033 miles. Person 5: 16 years, 218,407 miles. Person 6: 5 years, 98,012 miles. Person 7: 6 years, 112,000 miles. Person 8: 7 years, 113, 908 miles. Person 9: 3 years, 55,015 miles. Person 10: 10 years, 102, 209 miles. 1. draw a scatter plot of the data 2.Showing all work calculate r. 3. Showing all work determine whether to reject or not reject the null hypothesis based on the t-calculation. 4. Determine the equation of best fit. 5. When x = 5 what is y? 6. Determine r^2. 7. Determine S est. 8. Find the 95% prediction interval when x = 5The National Safety Council of the U.S. released the following data on the incidence rates for fatal or lost-worktime injuries per 100 employees for several industries in three recent years. Compute r for each pair of years and determine which years are most highly correlated. Calculate r using 1. the formula and 2. function. Industry Year 1 Year 2 Year 3 Textile 0.46 0.48 0.69 Chemical 0.52 0.62 0.63 Communication 0.9 0.72 0.81 Machinery 1.5 1.74 2.1 Services 2.89 2.03 2.46 Nonferrous metals 1.8 1.92 2 Food 3.29 3.18 3.17 Government 5.73 4.43 4 By formula By Function By formula By Function r1 r2 r3 Please provide a step by step of calculation in excelto give me an understaning on how to calculate in future Thank you in advance
- Question 4 a The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. Assuch, he is interested in investigating the association between the age of the respondents and theirknowledge level. Table 2 below shows the knowledge level of respondents, by age group.Table 2Age Group Knowledge Level TotalPoor Satisfactory Good18 - 25 33 16 13 6226 - 34 30 18 12 6035 - 44 29 14 12 5545 - 54 36 16 18 7055 - 75 17 14 22 53Total 145 78 77 300 Conduct a test, at the 5% level of significance, to determine whether the data provided sufficientevidence 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) the p-value for this test, given that the chi-square test statistic, x2, is 11.029. (iv) state the conclusion for the test. Give reason for your answer.QUESTION 4(a) The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. Assuch, he is interested in investigating the association between the age of the respondents and theirknowledge level. Table 2 below shows the knowledge level of respondents, by age group.Table 2Age Group Knowledge Level TotalPoor Satisfactory Good18 - 25 33 16 13 6226 - 34 30 18 12 6035 - 44 29 14 12 5545 - 54 36 16 18 7055 - 75 17 14 22 53Total 145 78 77 300Conduct a test, at the 5% level of significance, to determine whether the data provided sufficientevidence 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) the p-value for this test, given that the chi-square test statistic, 2, is 11.029.(iv) state the conclusion for the test. Give reason for your answer.A researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.
- A covariance of 0.01 between data set A and data set B indicates: A strong tendency for B to increase when A increases A weak relationship between A and B A strong tendency for B to decrease when A increases Not enough information to sayIf the value of Cronbach’s alpha is 0.07, it means ___________; a. Research instrument is not reliable b. Research instrument is internally consistent c. Data is reliable d. Data is internally consistentAssume that as a portfolio manager the beta of your portfolio is 1.15 and that your performance is exactly on target with the SML data under condition 1. If the true SML data is given by condition 2, how much does your performance differ from the true SML? (1) RFR = 0.0625 Rm(proxy) = 0.12 (2) RK = 0.078 Rm(true) = 0.10
- 1) The following data show the results of a study based on the number of hours college students spend playing video games and their GPAs: Number of Hours Playing Video Games(per week)= 42 GPA= 0.2Number of Hours Playing Video Games(per week)= 38 GPA= 0.9Number of Hours Playing Video Games(per week) = 32 GPA= 1.0Number of Hours Playing Video Games(per week) = 26 GPA = 1.1Number of Hours Playing Video Games(per week) = 23 GPA= 1.2Number of Hours Playing Video Games(per week) = 19 GPA= 2.5Number of Hours Playing Video Games(per week) = 15 GPA = 3.0 a) Create a scatter plot and be sure to LABEL BOTH axis and give the chart an overall name. Have the graph display the “r-value” and the correct equation.b) What kind of correlation is this?c) Is this more of a linear or exponential model? Why?d) Predict the standard GPA if a student spends one hour a week playing videogames.Obtain the Z scores on each subject’s age. DATA Subject Gender Marital Status Age Education Household Income Personal Income 1 F 1 30 0 70000.00 40000.00 2 F 0 40 0 32500.00 32500.00 3 M 1 45 0 42000.00 .0 4 M 1 23 0 50000.00 50000.00 5 M 0 50 0 4500.00 4500.00 6 F 0 65 1 40000.00 22000.00 7 F 1 33 1 12000.00 12000.00 8 F 0 20 2 56000.00 52000.00 9 F missing 30 3 17500.00 17500.00 10 M 1 Missing 4 44000.00 39000.00 11 M 2 58 1 missing missing 12 M 2 32 2 10000.00 10000.00 13 M 1 35 3 missing missing 14 F 2 23 4 100000.00 50000.00 15 F 2 34 1 64000.00 64000.00 16 M 1 26 2 Missing missing 17 M 1 36 3 missing missing 18 F 0 41 4 7500.00 5500.00 19 F 0 43 1 missing missing…Which of the following would cause FOBT to increase A. An increase in the difference between the means b. An increase in the magnitude of the independent variables affect c. An increase in the difference between the means and an increase in the within groups variability d. An increase in the difference between the means and an increase in the magnitude of the independent variables of effect e. An increase in the within-groups variability
