Q3: Multiple regression using Minitab. interpret the results in bullets step by step Regression Analysis: y versus x1, x2 Regression Equation
Q: A multiple regression model has the form Y = -17 + ( 18 * X1 ) + ( 17 * X2 ) As X2 decreases by 1…
A: A multiple regression model has the form Y = -17 + ( 18 * X1 ) + ( 17 * X2 ) As X2 decreases by 1…
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A: Hi, thanks for the question. Since there are multiple subparts posted in the question, we will…
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A: Lemon Import, X Crash Fatality rate, Y 233 16 270 15.9 358 15.6 492 15.3 536 15
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- t Predictions: On A startup team is interested in creating a productivity app. In estimating the cost of creating the app, they collected sample data and developed the following regression equation: where number of developers b 2number of hours spent creating the app Is cost of software and testing ($'000) y-total cost of creating app ($'000) a. What is the value of b2 in the equation? y = -8.006-19.271x1 +0.8462 +1.786x3 b. Does it make sense to interpret bo in this equation? Yes No Accessibility: Investigate Search O W 5 IMultiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0 =female and 1=male). The following is a partial result of computer output that was used on a sample of 20 individuals. Present the estimated regression equation and compute the coefficient of determination. Explain it. Use the t test to determine the significance of each independent variable. Let α = 0.05. (For each test, give the null and alternative hypotheses, test statistic, and conclusion.) Use the F test to determine whether or not the regression model is significant. Let α = 0.05. (For the test, give the null and alternative hypotheses, test statistic, and conclusion.) Does the estimated regression equation provide a good fit for the observed data? Explain it. Suppose a new person with X1=40, X2=4, X3=0. Use the estimated regression equation in part (a)…How does the interpretation of the regression coefficients differ in multiple regression and simple linear regression?
- The equation used to predict annual cauliflower yield (in pounds per acre) is y=24,596+4.423x1−4.772x2, where x1 is the number of acres planted an x2 is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables.Find the equation of the regression line Y= ?+(-?)X Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed The best for predicted crash fatality rate for a year in which there are 425 metric tons of lemon imports is ? Fatalities per 100,000 population.(round two one decimal place as needed)Consider a regression model. The coefficient of determination (R2) gives the proportion of the variability in the dependent variable that is explained by the regression equation. True False
- The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150For a linear regression b1 is the estimated y-intercept, and b0is the estimated slope of the regression line. True or FalsePlease answer it using any spreadsheet. Or you can answer it manually but please do show your full solution. Thanks!!!
- The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.7 + 0.3x, + 5.2x2, where x, is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. X1 = 70, x, = 8.9 The predicted volume is cubic feet. (Round to one decimal place as needed.)X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) NextBiochemical oxygen demand (BOD) measures organic pollutants in water by measuring the amount of oxygen consumed by microorganisms that break down these compounds. BOD is hard to measure accurately. Total organic carbon (TOC) is easy to measure, so it is common to measure TOC and use regression to predict BOD. A typical regression equation for water entering a municipal treatment plant is BOD = -55.47 + 1.505 TOC Both BOD and TOC are measured in milligrams per liter of water. (a) What does the slope of this line say about the relationship between BOD and TOC? TOC rises (falls) by 1.505 mg/l for every 55.47 mg/l increase (decrease) in BOD BOD rises (falls) by 55.47 mg/l for every 1 mg/l increase (decrease) in TOC TOC rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in BOD BOD rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in TOC