domly. Perform linear regression using lm() to predict the variable medv. Tune the model with feature selection, feel free
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.A group of Maternal and Child Health public health practitioners are interested in the relationship between bacterial vaginosis (BV) and a number of negative health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between BV and depression, controlling for maternal age. The following is a computerized output displaying the results of their analysis.Parameter Intercept Maternal Age DepressionEstimate StandardError tValue Pr>|t|0.2186206635 -.0046496845 0.19124124150.06635040 0.00221338 0.031518843.29 0.0010 -2.10 0.0360 6.07 <.0001 A) What are the dependent and independent variables in this investigation?B) Based on the information above, was the research team justified in controlling for maternal age in this population? Why or why not?C) Write out the model in symbols. Round to 3 decimal places.D) Is there a significant association between BV and depression?A sixth-grade teacher believes that there is a relationship between his students’ IQscores (y) and the numbers of hours (x) they spend watching television each week. Thefollowing table shows a random sample of 7 sixth-grade students.y 125 116 97 114 85 107 105x 5 10 30 16 41 28 21 Does the data provide sufficient evidence to indicate that the simple linear regressionmodel is appropriate to describe the relationship between x and y? Perform a model utilitytest at α = 0.05. (Give H0, Ha, rejection region, observed test statistic, P-value, decisionand conclusion.)Find the Pearson sample correlation coefficient between x and y. Then interpretthe result.
- The marketing manager of a supermarket chain would like to determine the effect of shelf spaceon the sales of pet food. A random sample of 10 stores was selected, and the results are presentedbelow. Store shelf space in cm weekly sales in thousand pesos 1 45 18 2 45 21 3 75 15 4 80 18 5 95 23 6 100 26 7 135 22 8 140 27 9 185 25 10 190 28 d. Using the estimated simple linear regression equation Y=15.6414+0.0611X, estimate the weekly sales when theshelf space is 230cm? 250cm? e. Compute the coefficient of determination and interpret its value.A mail-order business selling personal computer supplies, software and hardware maintains a centralized warehouse. Management is currently examining the process of distribution from the warehouse and wants to study the factors that affect the warehouse distribution costs. Data collected over 24 random months contain the warehouse’s distribution cost (in thousands of Rands), the sales (in thousands of Rands) and the number of orders received. A multiple linear regression model was fitted to the data by using Stat1.2. Use the output to answer the questions that follow by typing only the letter of the correct option in the answer boxes. Variablesy: Warehouse Distribution Costx1: Salesx2: Number of Orders Model Fitting StatisticsR2 = 0.8504Adj R2: ? Regression Coefficients Beta Parameter Standard b Parameter Standard Estimates…A U.S. state's Bureau of Economic Geology published a study on the economic impact of using carbon dioxide enhanced oil recovery (EOR) technology to extract additional oil from fields that have reached the end of their conventional economic life. The following table gives the approximate number of jobs for the citizens that would be created at various levels of recovery. Percent Recovery (%) 20 40 80 100 Jobs Created (Millions) 6 9 12 18 Find the regression line. j(r) = Use the regression line to estimate the number of jobs that would be created at a recovery level of 60%. _____ million jobs
- Use the table below: X1 15 20 25 30 35 40 45 48 50 60 X2 100 110 115 120 140 142 144 146 150 160 Y 1 2 3 2 3 3 4 5 5 6 (i) Fit a regression equation to the multiple regression model by least squares method. (ii) Predict Y when X1=3.5 and X2=5.5 (iii) Compute TSS, ESS and RSS. (iv) Test for the significance of overall regression at 5% level of significance.Draw the scatter plot and compute the predicted equation of the line using the least square Regression line method.Show all the steps, do not just write the answer. X 0 1 3 4 7 Y 7 5 4 3 2The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored 60 on their achievement test. What would their SY16C grade be? Mathematics test (x) SY16C grades (y) 1 39 65 2 43 78 3 21 52 4 64 82 5 57 92 6 47 89 7 28 73 8 75 98 9 34 56
- The following table displays the mathematics test scores for a random sample ofcollege students, along with their final SY16C grades.a. Fit the regression line y=a+bx to the data and interpret the results.b. Use the regression equation to determine the SY16C grade for a college student whoscored 60 on their achievement test. What would their SY16C gradebe? Mathematics test(x) SY16C grades(y)1 39 652 43 783 21 524 64 825 57 926 47 897 28 738 75…It is believed that the annual repair cost for the sporty automobile Jeep is related to its age. A sample of 11 automobiles revealed the results in the table at the right. Car age (xi) 2 3 1 7 5 8 1 2 6 9 4 Repair cost (yi) in £ 72 99 65 138 67 140 83 101 170 121 114 Define the terms regression and correlation analysis . From the simple linear model ,y= a + bx ,determine parameters a and bA highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized. ŷ = b0+b1x+b2x^2 where: y = traffic flow in vehicles per hourx = vehicle speed in miles per hour The following data were collected during rush hour for six highways leading out of the city. Traffic Flow (y) Vehicle Speed (x) 1256 35 1329 40 1227 30 1336 50 1350 55 1125 25 a. Use the data to compute the coefficients of this estimated regression equation (to 4 decimals). Enter negative value as negative number. (Create the x^2 variable first using Data/Transform Data/Square.) b0 = ? b1 = ? b2 = ? b. Using alpha = 0.01, test for a significant relationship. F = ? (to 4 decimals) P-value = ? (to 4 decimals) c. Estimate the traffic flow in vehicles per hour at a speed of 39 miles per hour (to 2 decimals). vehicles per hour
