If the number of miles for a delivery is 5 & the number of minutes is 30, what is the estimated overhead cost associated with that delivery rounded to two decimals?
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- P Question 12 The equation for the 1.5 mile run/jog test is: VO,max (mi/kg/min) = 3.5 + [483 + (time in min.)] Jackson runs the 1.5 miles in 9 minutes. What information is obtained from this equation? O Jackson's VO2 max is 57.2ml/kg/min O Jackson's average VO2 running at a 6 minute mile pace is 57.2ml/kg/min O Jackson burns 30 calories per minute at thsi pace O Jackson's absolute VO2 is 57.2ml/kg/min5. Among important factors that affecting the price of land lot are size, number of mature trees and distance to the lake. Using data for 60 recently sold land lots are shown below: B 1 SUMMARY OUTPUT 2 3. Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 0.4924 0.2425 0.2019 40.24 8 Observations 60 9. 10 ANOVA Significance F 5.97 11 df S MS 9676.6 0.0013 12 Regression 13 Residual 3 29,030 90,694 56 1619.5 14 Total 59 119,724 15 16 Coefficients Standard Error t Stat P-value 0.0331 0.2156 17 Intercept 51.39 23.52 2.19 18 Lot size 0.700 0.559 1.25 19 Trees 0.679 0.229 2.96 0.0045 20 Distance -0.378 0.195 -1.94 0.0577 a) Write the regression equation b) What is the standard error of estimate? Interpret its value. c) What is the coefficient of determination? Interpret its value. d) What is the adjusted coefficient of determination? Interpret its value. e) Test the validity of the model. f) Interpret each of the coefficients. g) Test at 5% level of…OA linear regression model is Units 3,414-0.839xWeek. For week 45, what is the forecast for the number of units? Round your answer to the nearest whole number. OO units
- 1. R-squaredSuppose regression of y on an intercept and x with 50 observations yields total sum of squares 100 andexplained sum of squares 36.(a) What is ?^2?(b) What is the correlation coefficient between y and x?(c) What is the standard error of the residual?:= 1:36 MicrolnternationalProject 5G 49 Done International Aspect of Project Homework Below is an except pasted from a semester project for this course (broken into two pieces). Your task is to respond to this prompt and to cite at least one source. For this assignment, the source may be scholarly or from a periodical. Your source should be documented as a reference using APA style. Be sure to respond to the prompt using concepts from our course. You may use models to illustrate your points. 1. American solar farms receive billions of dollars in taxpayer subsidies each year. These subsidies allow them to substitute grain production for energy production. How do U.S. solar farm subsidies hurt or benefit Mexican farmers? 2. What does this imply for U.S. food production independence? What could be done to address this problem, and would the solution be effective? Notice, having a positive effect, a negative effect or no net-effect is a possibility on Mexican farmers. Whatever your answer,…According to the following given information how to determine: Production Times (months) 1 9 10 11 12 13 14 15 product of 970 1,180 1,239 1,293 1,350 1,398 1,410 1,480 1,492 1,500 1,520 1,592 1,605 1,660 1,685 (Z unit) A) Break Even-point or points? B) How is to construct the relationship between entire variables through the simple drawing for all above figures and highlighting of Break Even point the drawing? C) Justify your final answer for each line of production.
- In the graph below, the which variable is NOT held constant? [Select] The red, dashed line is the [Select] 8 14 22 Line A X Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.Define the term, the variation of PW?Uniform gradient pls
- Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. Regression Statistics Multiple R 0.7339 R Square 0.5386 Adjusted R Square 0.5185 Standard Error 2137.5200 Observations 49 ANOVA SS df Regression 2 245,370,679.3850 122,685,339.6925 26.8517 MS F Significance F 1.9E-08 Total Residual 46 210,173,612.6150 48 455,544,292.0000 4,568,991.5786 Coefficients Standard Error Intercept Education (Years) 14290.37278 2350.8671 2,528.5819 338.1140 Experience (Years) 829.3167 392.5627 t Stat P-value 5.6515 0.000000961 9200.6014 6.9529 0.000000011 2.1126 0.040093183 Lower 95 % Upper 95% 19,380.1442 1670.2789 3031.4553 39.129 1619.5044 Step 2 of 2: How much would you expect your salary to increase if you had one more year of education?Consider the following regression estimates (FN2) Linear regression belavg abvavg female married _cons b. 1 wage O C. 5 O d. 4 Robust Coef. Std. Err. 3047845 3150202 2820787 -1.063254 .0693348 -2.751963 .9686236 .2612646 6.699098 .2889831 Number of obs F(4, 1255) Prob > F R-squared Root MSE t P>|t| -3.49 0.001 0.22 0.826 -9.76 0.000 3.71 0.000 23.18 0.000 |||||||||| = = .45606 6.132155 = -1.661197 -.5486894 -3.305361 = = [95% Conf. Interval] 1,260 56.35 0.0000 0.1121 4.3987 assume that MLR 1-6 hold. In the regression above, how many coefficients (including the constant) are statistically significant at the 1% level? a. 3 -.4653108 .687359 -2.198565 1.481187 7.266042Please do 8-38