Consider the following regression estimates (FNB) Source MS Number of obs 500 F(2, 497) Prob > F 100.85 Model 71007499.5 2 35503749.8 0.0000 Residual 174967111 497 352046.502 Total 245974611 499 492935.092 incone Coef. Std. Err. P>|t| (95% Conf. Interval] fenale -37.5719 53.55403 -0.70 0.483 -142.7921 67.6483 hours 18.79374 1.345669 13.97 0.000 16.14984 21.43765 „cons 302.975 47.65295 6.36 0.000 209.349 396.6011 What is the R-squared of the regression above? Please stote the anawer os a value between O and 1.
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- Refer to the data in images. Test for a significant difference in the variances of theinitial white blood cell count between patients who did andpatients who did not receive a bacterial culture.Please give handwrittenThe regional manager of a franchise business is interested in understanding how income in a region affects sales. Below is a regression output for sales ($’000) regressed on the average household income of an area ($’000) Linear Fit Sales = 14.5774 + 2.9048*Income Summary of Fit RSquare 0.9683 RSquare Adj 0.9630 Root Mean Square Error 3.1083 Mean of Response 43.6250 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 1771.9048 1771.90 183.3946 Error 6 57.9702 9.66 Pro>F C. Total 7 1829.8750 ItI Intercept 14.5774 2.4101 6.05 0.0009* Income 2.9098 0.2145 13.54 < 0.0001* Answer the following questions: (i) What is the average sales across all regions? (ii) Interpret the slope of regression (iii) What is the prediction of the value of sales in a region with an average…
- The average value of the residuals isWhich of the following would probably NOT be a potential “cure” for non-normal residuals? Select one: a. Transforming two explanatory variables into a ratio. b. Removing large negative residuals. c. Removing large positive residuals. d. Using a procedure for estimation and inference which did not assume normality.Calculate the Residual associated with the prediction of your height. Is the predicted height an overestimate or underestimate of your actual height?
- Consider the following Stata regression output (IDFB2) Source SS df MS Number of obs 935 %3D F(3, 931) 114.07 Model 1211.30177 3 403.767257 Prob > F 0.0000 %3D Residual 3295.51748 931 3.53976099 R-squared 0.2688 %3D Adj R-squared 0.2664 Total 4506.81925 934 4.82528828 Root MSE 1.8814 educ Coef. Std. Err. P>|t| [95% Conf. Interval] age .0074829 .0198281 urban 2546161 .1367932 IQ 0750274 .0040968 5.439236 .7981253 _cons What is the value of the t-statistic of the constant?A quadratic regression was fitted to the data. Parts of the computer output appear below. Predictor Coef Stdev t-ratio Constant 7990.0 724.7 11.03 0.000 price -10660 1151 -9.26 0.000 price2 3522.3 436.8 0.000 Analysis of Variance SOURCE DF SS MS P. Regression 16060569 8030284 125.11 0.000 Error 60 3851231 64187 Total 62 19911800 a) Write the appropriate model for the abovedata (3 marks) b) According to this model, how many units will be sold, on average, when the price of the beverage is $1.10? (2 marks)Spray drift is a constant concern for pesticide applicators and agricultural producers. The inverse relationship between droplet size and drift potential is well known. The paper "Effects of 2,4-D Formulation and Quinclorac on Spray Droplet Size and Deposition"+ investigated the effects of herbicide formulation on spray atomization. A figure in a paper suggested the normal distribution with mean 1050 µm and standard deviation 150 µm was a reasonable model for droplet size for water (the "control treatment") sprayed through a 760 ml/min nozzle. USE SALT (a) What is the probability that the size of a single droplet is less than 1380 µm? At least 950 µm? (Round your answers to four decimal places.) less than 1380 μm at least 950 μm (b) What is the probability that the size of a single droplet is between 950 and 1380 µm? (Round your answer to four decimal places.) (c) How would you characterize the smallest 2% of all droplets? (Round your answer to two decimal places.) The smallest 2% of…
- Spray drift is a constant concern for pesticide applicators and agricultural producers. The inverse relationship between droplet size and drift potential is well known. The paper "Effects of 2,4-D Formulation and Quinclorac on Spray Droplet Size and Deposition"+ investigated the effects of herbicide formulation on spray atomization. A figure in a paper suggested the normal distribution with mean 1050 µm and standard deviation 150 μm was a reasonable model for droplet size for water (the "control treatment") sprayed through a 760 ml/min nozzle. USE SALT (a) What is the probability that the size of a single droplet is less than 1440 µm? At least 975 μm? (Round your answers to four decimal places.) less than 1440 μm 9990 X at least 975 μm (b) What is the probability that the size of a single droplet is between 975 and 1440 µm? (Round your answer to four decimal places.) (c) How would you characterize the smallest 2% of all droplets? (Round your answer to two decimal places.) The smallest…A regression analysis was performed, with partial results shown below, along with various plots. In the print-out of results, the square of the correlation coefficient is labeled “Multiple R-squared”. Explain in terms specific to this analysis (i.e., not just general terms) what this R-squared tells us. Response:ln_Income Explanatory: Age Residuals: Min 1Q Median 3Q Max -0.83978. -0.28834 -0.05761 0.25615 1.09741 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 9.680077 0.158362 61.13 < 2e-16 *** samp_reg$Age 0.016778 0.003995 4.20 5.76e-05 *** --- Residual standard error: 0.4012 on 101 degrees of freedom Multiple R-squared: 0.1487, Adjusted R-squared: 0.1403 F-statistic: 17.64 on 1 and 101 DF, p-value: 5.763e-05The following Excel tables are obtained when "Score received on an exam (measured in percentage points)" is regressed on "percentage attendance" for 22 students in a Statistics for Business and Economics course. Regression Statistics Multiple R R Square Standard Error 20.25979924 0.142620229 0.02034053 Observations 22 Coefficients Standard Error T Stat Intercept 39.39027309 37.24347659 1.057642216 Attendance 0.340583573 0.52852452 0.644404489 Estimate the "Score received on an exam" if "percentage attendance" student is 75. Select one: a. 39.6 b. 45.6 c 78.7 d. 64.9