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- 2) a, b, and c. Solve them step by step.Can you also take a screenshot or list all the graphical procedures when doing the attached question by using MinitabJohnson Filtration, Inc., provides maintenance service for water-filtration systems throughout southern Florida. Suppose that in addition to information on the number of months since the machine was serviced and whether a mechanical or an electrical repair was necessary, the managers obtained a list showing which repairperson performed the service. The revised data follow. Time bo + b₁ Months + b₂ Type + b3 Person Round your answers to three decimal places. bo b₁ b₂ b3 Repair Time in Hours 2.8 3.0 4.7 1.9 2.9 4.8 4.2 4.9 4.3 4.4 0000 Months Since Last Service 2 6 8 3 a. Develop the estimated regression equation to predict the repair time given the number of months since the last maintenance service, the type of repair, and the repairperson who performed the service. Assume that ₂ = 1 if the type of repair is electrical and 3 = 1 if Dave Newton performed the service. Enter negative value as negative number. 2 7 9 8 4 6 Type of Repair Electrical Mechanical Electrical Mechanical…
- The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature x1, the number of days in the month x2, the average product purity x3, and the tons of product produced x4. The past year's historical data are available and are presented in the following table. 240 25 24 91 100 236 31 21 90 95 290 45 24 88 110 274 60 25 87 88 25 26 25 301 65 91 94 316 72 94 99 300 80 87 97 84 75 296 25 86 96 267 24 88 110 276 60 25 91 105 288 50 38 25 23 90 100 261 89 98 If y= ao+a1X1 +a2x2+Q3X3+Q4X4 represents the regression model. What is the value of a2? Use 2 decimal places.Major League Baseball now records information about every pitch thrown in every game of every season. Statistician Jim Albert compiled data about every pitch thrown by 20 starting pitchers during the 2009 MLB season. The data set included the type of pitch thrown (curveball, changeup, slider, etc.) as well as the speed of the ball as it left the pitcher's hand. A histogram of speeds for all 30,740 four-seam fastballs thrown by these pitchers during the 2009 season is shown below, from which we can see that the speeds of these fastballs follow a Normal model with meanu = 92.12 mph and a standard deviation of o = 2.43 mph. 85 90 100 speed (mph) Compute the z-score of pitch with speed 95.8 mph. (Round your answer to two decimal places.) 1.5 Approximately what fraction of these four-seam fastballs would you expect to have speeds between 90.2 mph and 90.8 mph? (Express your answer as a decimal, not a percent, and round to three decimal places.) Approximately what fraction of these four-seam…Major League Baseball now records information about every pitch thrown in every game of every season. Statistician Jim Albert compiled data about every pitch thrown by 20 starting pitchers during the 2009 MLB season. The data set included the type of pitch thrown (curveball, changeup, slider, etc.) as well as the speed of the ball as it left the pitcher’s hand. A histogram of speeds for all 30,740 four-seam fastballs thrown by these pitchers during the 2009 season is shown below, from which we can see that the speeds of these fastballs follow a Normal model with mean μ = 92.12 mph and a standard deviation of σ = 2.43 mph. Compute the z-score of pitch with speed 89.4 mph. (Round your answer to two decimal places.)Approximately what fraction of these four-seam fastballs would you expect to have speeds between 88.2 mph and 95 mph? (Express your answer as a decimal, not a percent, and round to three decimal places.)Approximately what fraction of these four-seam fastballs would you expect…
- Set A: n = 5; x = 10Set B: n = 50; x = 10(a) Suppose the number 32 is included as an additional data value in Set A. Compute x for the new data set. To compute x for the new data set, add 32 to x of the original data set and divide by 6. (Round your answer to two decimal places.) b.) Suppose the number 32 is included as an additional data value in Set B. Compute x for the new data set. (Round your answer to two decimal places.)A1 1 2 3 7 5 5 7 B 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 A Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 X B Discharged_Patients A 54 63 110 105 131 137 80 63 75 92 105 112 120 95 72 128 126 106 129 136 94 74 107 135 124 113 140 83 62 106 fx Day с Records_not_Processed 18 18 52 29 70 57 26 29 14 27 49 38 47 26 28 49 45 39 27 38 44 25 29 62 44 60 46 38 25 39 D E F G H I JA psychologist believed that as children get older, they engage in more “inactive activities” such as playing computer games, watching TV and surfing the internet. She collected data from 10 children. She recorded the age of each child and the amount of activity (in hours) the child engaged in per week. Age Activity 7 4.3 9 3.2 10 1 13 1.5 12 1.2 15 0.8 9 3 12 4 15 1.5 14 1.9 Using excel, obtain a scatterplot of the data. Discuss the relationship between age and activity based on the scatterplot. Using excel, obtain the simple linear regression linear regression line predicting activity from age. Interpret the intercept and slope of the regression line. By hand, predict the amount of activity for age = 14. By hand, calculate the residual for age = 14 Using excel output, test the null hypothesis that the slope coefficient is zero using the p-value approach. Write one sentence interpreting the meaning of this result. Make sure to report the test statistic…