Profit and Working Capital. Sixteen industries of thisState have been ranked as follows according to profits earned in1970-71, and working capital for the year:IndustryRank (Profit) 1 2Rank (work-ing capital) 13 16 14 15 10 12 4 11 5 9 8 3 1 6 7 2Calculate the correlation coefficient,A BCD EFGHIJK L5 6 7M NO P8 9 10 11 12 13 14 15 163 4

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Answered: Profit and Working Capital. Sixteen…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Create scatterplots using the data in the spreadsheet linked above and display the equation for the regression line. What is the equation for the regression line that predicts mortgage amount using household income as the explanatory variable? Ý : Ex: 1.234 x + (Ex: 1.234) What is the interpretation of the slope? Pick What is the interpretation of the intercept? Pick Pick Household income when mortgage amount is 0 Mortgage amount when household income is 0 No practical interpretation 2
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Find the correlation coefficient of determination and then interpret both Table #10.1.6: Data of House Value versus Rental Value Rental Value Rental Value Rental Rental Value 67500 81000 6656 77000 4576 75000 7280 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9152 7488 9568 140000 135000 7488 165000 13312 165000 8528 155000 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 匯 190000 200000 225000 8320 12272 8528 200000 200000 10608 194000 11232 8320 10400 11648 10192 12272 10400 200000 240000 214000 208000 240000 10192 240000 12064 12480 244500 11232 12896 12480 289000 11648 270000 262000 325000 12480 310000 303000 300000 12480
TIP ($) 250 225 200 175 150 125 100 75 50 25 0 0 A SONNY'S SCATTERPLOT B 100 200 300 400 Ⓒ2020 Radha Bose Florida State University Department of Statistics C D E SALE AMOUNT ($) *F H 500 600 700 800 900 1000 1100 1200 1. Which sale received the best tip, that is, which sale had the tip that was highest above the tip predicted for it? 2. Which data point has the smallest residual? 3. The residual for data point B is closest to
Outside Sr # Tempera (Number Sales X(outsid Y(sales) X*2 Y*2 Y=-5 e ture of Air tempera (Degrees Conditio ture) F) ning units sold) 68 3 68 3 4624 204 1.636 72 72 5 5184 25 360 4.883 78 7 3 78 7. 6084 49 546 9.754 81 12 4 81 12 6561 144 972 12.19 84 15 84 15 7056 225 1260 14.62 86 16 6 86 16 7396 256 1376 16.25 89 22 89 22 7921 484 1958 18.68 91 18 91 18 8281 324 1638 20.31 93 19 9 93 19 8649 361 1767 21.93 94 26 10 94 26 8836 676 2444 22.74 836 143 7059 2553 12525 143 sum Y= Plot a scatter diagram for the data provided on the table above and the linear regression line calculated in topic (b). Consider that: Y: number of air conditioning units sold X: outside temperature (degrees F) rds English (U.S.) Text Predictions: On acer
The table below gives the estimated world population (in billions) for various years. 1980 1990 1997 2000 2005 2011 Years Population 4400 5100 5852 6080 6450 7000 Is the correlation significant? yes cannot be determined yes only to some extent O no
A group of farmer wants to know the correlation between the certain amount of fertilizer and the crops yield. With the same land area and different amount of fertilizer yields the following crops. Fertilizer 23 18 15 12 13 14 15 23 20 20 19 22 12 10 16 crops 78 66 54 48 65 71 77 57 69 74 56 60 54 59 63 Does it appear there is relationship between the fertilizer and crops? Compute the coefficient of correlation. Determine at 0.05 level of significance whether the correlation is greater than zero.
IQuestion 1] a. The following table shows demand (x) and supply (v) for a sample of a certain commodity. 12 7 11 19 5 21 3 4 17 14 3 21 28 6 43 1 12 30 y i. Plot the points on a scatter graph and state the relationship between the two variables. ii. Calculate the value of the product moment correlation coefficient for the data and comment briefly. b. Company Y wants to determine the cost-volume relation between its factory overhead cost and number of units produced. The volume and the corresponding total cost information of the factory for past eight months are given below: Month 2 3 4 5 6 7 8. Units 1,520 1,250 1,750 1,600 2,350 2,100 3,000 2,750 FOH S36,375 $38,000 $41,750 S42,360 $55,080 SS48,100 $59,000 $56,800 Factory Overhead costs of Company Y i. Use the high-low method to split its factory overhead (FOH) costs into fixed and variable components and create a cost volume formula. ii. Briefly explain why this method is unreliable as a means of cost estimation and suggest one other…
Calculate Karl Pearson's coefficient of correlation between capital employed andprofit obtained from the following data. Comment on the nature of correlation. 5,6 N Capital Employed10 20 30 40 50 60 70 80 90 100(Rs. In Crore)Profit2 4 8 5 10 15 14 20 2 50
1. What is the correlation coefficient for the two variables listed below? It is probably easiest to use the =correl() function in excel or find the correlation coefficient in Gretl or Jamovi. (Round your answer to the nearest 0.1) 19 1 4 12 54 51 53 64 82 85 86 14 65 54 96 98 91 88 96 66
X1 X2 Y X1 1.0000 0.7139 0.6147 X2 0.7139 1.0000 0.3098 Y 0.6147 0.3098 1.0000 This is my correlation matrix table. Using this, which variable explains the greatest proportion of variation in Y? What is the proportion of variation in Y that can be explained by X1? What is the proportion of variation in Y that can be explained by X2? Also what is multicollinearity?

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