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no in Excel
It is required to use the data given in the table to estimate the parameters of the simple linear regression equation by any of the estimation methods:
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- A computer engineer needs to know how the efficiency of a new computerprogram depends on the size of incoming data. Efficiency will be measuredby the number of processed requests per hour. Applying the program todata sets of different sizes with the following results. The response variableis the number of processed requests (Y) and to predict it from the size of adata set (X). Estimate the quadratic regression model and use it to find theprocessed requests when the data size is 14 GB.Data size (GB) X 6 7 7 8 10 10 15Processed requests Y 50 43 44 37 25 26 15The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x,) and newspaper advertising (x,). The estimated regression equation was ý = 82.3 + 2.29x, + 1.90x2. The computer solution, based on a sample of eight weeks, provided SST = 25.1 and SSR = 23.415. (a) Compute and interpret R? and R 2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is 653 x . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (b) When television advertising was the only independent variable, R2 = 0.653 and R,2 = 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis (is preferred since both R2 and R.2 show an increased v v…Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.
- Experimenters wants to assess the association between X and Y, the scatter plot of X and Y showed a quadratic pattern. After applying the appropriate regression model, experimenters want to produce a prediciton interval for X = 20. Using StatCrunch with 95% confiendence, the result interval is 223 to 267. Provide the most appropriate interpretation of this interval.The table shows the number of goals allowed and the total points earned (2 polnts for a win, and 1 point for an overtme or shootout loss) by 14 lce hockey teams over the course of a season The equation of the regression line is (a) Find the coefficient of determination,, and interpret the result (b) Find the standard error of the estimate, and interpret the resut Goals Allowed, x Points, y -0.560x 218.067 Use he data to answer the folowing questions 217 213 221 229 260 262 277 205 216 20s 217 208 257 246 66 70 105 105 0 83 47106 103 97 9182 91 88 Inco (a) r-O (Round to three decimal places as noeded.)The trip rate (y) and the corresponding household sizes (x) from a sample are shown in Table Q2. Apply the regression method to find the trip rate for a household size of 10. Table Q2
- Show that the following relationship on the simple linear regression class notebook is true: (Refer the image)The table lists the average monthly cost to workers for family health insurance for various years. Year, x Average Monthly Cost to Workers for Family Health Insurance $298 a) Use a graphing calculator to fit a regression line to the data. b) Predict the average monthly cost to workers for family health insurance in 2020, and compare the value with $493.3, which is obtained using the points (1,340) and (4,386). c) Find the correlation coefficient for the regression line, and determine whether the line fits the data closely. 2009, 0 2010, 1 2011, 2 340 348 2012, 3 367 2013, 4 2014, 5 386 406 a) The linear equation of the regression line that best models the data is y =x+. (Round to the nearest hundredth as needed.) b) The average monthly cost to workers for family health insurance in 2020 is predicted to be $ (Round to the nearest cent as needed.) Compare the above obtained value with $493.3 This value is $ $493.3 c) The correlation coefficient is (Round to the nearest thousandth as…The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x₁) and newspaper advertising (x₂). The estimated regression equation was ŷ = 83.5+ 2.21x₁ + 1.80x₂. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.495. (a) Compute and interpret R² and R2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is variable that can be explained by the estimated multiple regression equation is (b) When television advertising was the only independent variable, R² = 0.653 and R2 = 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis ---Select--- preferred since both R² and R2 show ---Select--- ✓percentage of the variability of y explained when both independent variables are used. . Adjusting for the number of…
- Tristan has completed his STAT 1342 course. He intends to build a simple linear regression model using control variable (X) as number of hours per week for his preparations and (Y) as the weekly performance measured in a 100-point scale and based on his self-assessment. There were totally n = 28 weekly collected records. The model built by Tristan was: Ý = 10 + 7· X with the standard error of estimated slope equal to SE = SE [6] = 2.8 1. At the significance level, a = 0.01, is there sufficient evidence that X positively impacts Y? • Evaluate Test Statistic • Specify critical value (or values) for this procedure • State the Rejection Rule • Formulate your decision 2. Estimate the population slope (= B) with confidence level, C = 0.95 • Specify critical value (or values) for this procedure • Evaluate UCL and LCL Solution 10Define both x and y in all problems. x is the cause, and y is the effect. This is the most important step when doing linear regression, otherwise, all the remanding parts will be wrong.
