Use the Lagrange multiplier method to identify the stationary point(s) of the function ?(?, ?, ?)=10? + 5? + ? + 2?^2 + 4?? + ?^2 + 2?? - ?^2 - ??, subject to the constraint 5? + 3? + ? = 27. Subsequently determine the nature of the stationary point(s) using the bordered Hessian matrix.
In: Advanced Math
A sample of size 27 will be drawn from a population with mean 4 and standard deviation 3.
(a) Is it appropriate to use the normal distribution to find probabilities for x?
(b) If appropriate find the probability that x will be greater than 2.
(c) If appropriate find the
40th percentile of x.
In: Statistics and Probability
The following are distances (in miles) traveled to the workplace by 17 employees of a certain hospital.
|
9, 27, 31, 18, 1, 28, 13, 32, 3, 18, 29, 16, 2, 37, 14, 22, 11 |
What is The 25th percentile?
What is the 70th percentile?
In: Statistics and Probability
Problem 3.An exam has 30 multiple choice questions. Each question has five answer choices, ofwhich exactly one is correct. In how many different ways can a student who answers all questionsget at least 27 of them correct?
In: Statistics and Probability
FIllmore Company began operations on Sept. 1 by purchasing $6,000 of inventory and $600 of cleaning supplies. During the month, the company generated $7,500 of sales revenue. On Sept. 30, the company had $2,100 of inventory remaining, along with $400 of cleaning supplies. What was FIllmore Company's gross profit for the month of September?Note 3,400 is wrong somehow!
In: Accounting
1) One out of every 92 tax returns that a tax auditor examines requires an audit. If 50 returns are selected at random, what is the probability that less than 3 will need an audit? 0.0151 0.9978 0.0109 0.9828
2) Sixty-seven percent of adults have looked at their credit score in the past six months. If you select 31 customers, what is the probability that at least 20 of them have looked at their score in the past six months? 0.142 0.550 0.692 0.450
3) Ten rugby balls are randomly selected from the production line to see if their shape is correct. Over time, the company has found that 89.4% of all their rugby balls have the correct shape. If exactly 6 of the 10 have the right shape, should the company stop the production line? No, as the probability of six having the correct shape is not unusual Yes, as the probability of six having the correct shape is not unusual No, as the probability of six having the correct shape is unusual Yes, as the probability of six having the correct shape is unusual
In: Math
In: Economics
The following were selected from among the transactions completed by Babcock Company during November of the current year:
| Nov. | 3 | Purchased merchandise on account from Moonlight Co., list price $85,000, trade discount 25%, terms FOB destination, 2/10, n/30. |
| 4 | Sold merchandise for cash, $37,680. The cost of the merchandise sold was $22,600. | |
| 5 | Purchased merchandise on account from Papoose Creek Co., $47,500, terms FOB shipping point, 2/10, n/30, with prepaid freight of $810 added to the invoice. | |
| 6 | Returned $13,500 ($18,000 list price less trade discount of 25%) of merchandise purchased on November 3 from Moonlight Co. | |
| 8 | Sold merchandise on account to Quinn Co., $15,600 with terms n/15. The cost of the merchandise sold was $9,400. | |
| 13 | Paid Moonlight Co. on account for purchase of November 3, less return of November 6. | |
| 14 | Sold merchandise on VISA, $236,000. The cost of the merchandise sold was $140,000. | |
| 15 | Paid Papoose Creek Co. on account for purchase of November 5. | |
| 23 | Received cash on account from sale of November 8 to Quinn Co.. | |
| 24 | Sold merchandise on account to Rabel Co., $56,900, terms 1/10, n/30. The cost of the merchandise sold was $34,000. | |
| 28 | Paid VISA service fee of $3,540. | |
| 30 | Paid Quinn Co. a cash refund of $6,000 for returned merchandise from sale of November 8. The cost of the returned merchandise was $3,300. |
Journalize the entries to record the transactions of Babcock Company for November using the periodic inventory system. Refer to the Chart of Accounts for exact wording of account titles.
Chart of Accounts
| CHART OF ACCOUNTS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Babcock Company | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| General Ledger | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In: Accounting
What are the five main differences between a Income statement that is produced by a for-profit company versus a local government Statements of Revenue, Expenditures and Changes in Fund Balances?
In: Accounting
The Farr-Kroger Classic is a women’s professional golf tournament played each year in Ohio. Listed below are the total purse winnings (the amount of money that is distributed to the top golfers) and the prize for the winner for the 15 years from 1991 through 2005. The operators of this golf tournament believe that there is a relationship between the purse winnings and the prize and the prize is related to the purse winnings. In addition to the data provided, some of the possible linear regression relationships are provided. These might be of help in your analysis.
| Year | Purse Winnings | Prize | Ind Var | Year | SUMMARY OUTPUT | ||||||||||||||
| 1991 | $225,000 | $33,750 | Dep var | Purse Winnings | |||||||||||||||
| 1992 | $275,000 | $41,250 | Regression Statistics | ||||||||||||||||
| 1993 | $325,000 | $41,250 | Multiple R | 0.969387633 | |||||||||||||||
| 1994 | $325,000 | $48,750 | R Square | 0.939712382 | |||||||||||||||
| 1995 | $350,000 | $52,500 | Adjusted R Square | 0.935074873 | |||||||||||||||
| 1996 | $400,000 | $60,000 | Standard Error | 65072.5152 | |||||||||||||||
| 1997 | $450,000 | $67,500 | Observations | 15 | |||||||||||||||
| 1998 | $500,000 | $75,000 | |||||||||||||||||
| 1999 | $500,000 | $75,000 | ANOVA | ||||||||||||||||
| 2000 | $575,000 | $86,250 | df | SS | MS | F | Significance F | ||||||||||||
| 2001 | $700,000 | $105,000 | Regression | 1 | 8.58036E+11 | 8.58036E+11 | 202.6330017 | 2.62887E-09 | |||||||||||
| 2002 | $800,000 | $120,000 | Residual | 13 | 55047619048 | 4234432234 | |||||||||||||
| 2003 | $800,000 | $120,000 | Total | 14 | 9.13083E+11 | ||||||||||||||
| 2004 | $1,000,000 | $150,000 | |||||||||||||||||
| 2005 | $1,000,000 | $150,000 | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |||||||||
| Intercept | -110055238.1 | 7769893.698 | -14.16431709 | 2.79418E-09 | -126841072.9 | -93269403.32 | -126841072.9 | -93269403.32 | |||||||||||
| Regression Relationship | Independent Variable | Dependent Variable | Value of b | Value of a | Coefficent of Determination, r2 | Year | 55357.14286 | 3888.826592 | 14.23492191 | 2.62887E-09 | 46955.84379 | 63758.44192 | 46955.84379 | 63758.44192 | |||||
| Regression 1 | Year | Purse Winnings | 55,357.14 | -110,055,238.10 | 0.94 | ||||||||||||||
| Regression 2 | Purse Winnings | Prize | 0.15 | -1,505.89 | 1.00 | ||||||||||||||
| Regression 3 | Prize | Purse Winnings | 6.57 | 11,179.24 | 1.00 | ||||||||||||||
| Regression 4 | Prize | Year | 0.00 | 1,988.85 | 0.94 | Ind Var | Purse Winnings | SUMMARY OUTPUT | |||||||||||
| Regression 5 | Year | Prize | 8,437.50 | -16,776,375.00 | 0.94 | Dep var | Prize | ||||||||||||
| Regression Statistics | |||||||||||||||||||
| a) x = | $996,430 | Multiple R | 0.998828015 | ||||||||||||||||
| y = -1505.89 + 0.15x = | $149,786.51 | R Square | 0.997657404 | ||||||||||||||||
| Adjusted R Square | 0.997477205 | ||||||||||||||||||
| b) x = | 2006 | Standard Error | 1949.897566 | ||||||||||||||||
| y = -110055238.10 + 55357.14x = | $991,190.48 | Observations | 15 | ||||||||||||||||
| ANOVA | |||||||||||||||||||
| df | SS | MS | F | Significance F | |||||||||||||||
| Regression | 1 | 21049947693 | 21049947693 | 5536.399574 | 1.7382E-18 | ||||||||||||||
| Residual | 13 | 49427306.74 | 3802100.519 | ||||||||||||||||
| Total | 14 | 21099375000 | |||||||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||||||||
| Intercept | -1505.886648 | 1226.975151 | -1.227316337 | 0.241465598 | -4156.605301 | 1144.832005 | -4156.605301 | 1144.832005 | |||||||||||
| Purse Winnings | 0.151834444 | 0.002040594 | 74.40698606 | 1.7382E-18 | 0.147426009 | 0.156242879 | 0.147426009 | 0.156242879 | |||||||||||
| Ind Var | Prize | SUMMARY OUTPUT | |||||||||||||||||
| Dep var | Purse Winnings | ||||||||||||||||||
| Regression Statistics | |||||||||||||||||||
| Multiple R | 0.998828015 | ||||||||||||||||||
| R Square | 0.997657404 | ||||||||||||||||||
| Adjusted R Square | 0.997477205 | ||||||||||||||||||
| Standard Error | 12827.21014 | ||||||||||||||||||
| Observations | 15 | ||||||||||||||||||
| ANOVA | |||||||||||||||||||
| df | SS | MS | F | Significance F | |||||||||||||||
| Regression | 1 | 9.10944E+11 | 9.10944E+11 | 5536.399574 | 1.7382E-18 | ||||||||||||||
| Residual | 13 | 2138985160 | 164537320 | ||||||||||||||||
| Total | 14 | 9.13083E+11 | |||||||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||||||||
| Intercept | 11179.24109 | 7942.610888 | 1.407502048 | 0.182737687 | -5979.726488 | 28338.20867 | -5979.726488 | 28338.20867 | |||||||||||
| Prize | 6.57069226 | 0.088307464 | 74.40698606 | 1.7382E-18 | 6.379915582 | 6.761468937 | 6.379915582 | 6.761468937 | |||||||||||
| Ind Var | Prize | SUMMARY OUTPUT | |||||||||||||||||
| Dep var | Year | ||||||||||||||||||
| Regression Statistics | |||||||||||||||||||
| Multiple R | 0.971981516 | ||||||||||||||||||
| R Square | 0.944748067 | ||||||||||||||||||
| Adjusted R Square | 0.940497919 | ||||||||||||||||||
| Standard Error | 1.090890292 | ||||||||||||||||||
| Observations | 15 | ||||||||||||||||||
| ANOVA | |||||||||||||||||||
| df | SS | MS | F | Significance F | |||||||||||||||
| Regression | 1 | 264.5294588 | 264.5294588 | 222.2858866 | 1.48781E-09 | ||||||||||||||
| Residual | 13 | 15.47054119 | 1.19004163 | ||||||||||||||||
| Total | 14 | 280 | |||||||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||||||||
| Intercept | 1988.846441 | 0.675479471 | 2944.347723 | 3.02269E-39 | 1987.387156 | 1990.305726 | 1987.387156 | 1990.305726 | |||||||||||
| Prize | 0.00011197 | 7.51011E-06 | 14.90925507 | 1.48781E-09 | 9.57455E-05 | 0.000128195 | 9.57455E-05 | 0.000128195 | |||||||||||
| Ind Var | Year | SUMMARY OUTPUT | |||||||||||||||||
| Dep var | Prize | ||||||||||||||||||
| Regression Statistics | |||||||||||||||||||
| Multiple R | 0.971981516 | ||||||||||||||||||
| R Square | 0.944748067 | ||||||||||||||||||
| Adjusted R Square | 0.940497919 | ||||||||||||||||||
| Standard Error | 9469.713869 | ||||||||||||||||||
| Observations | 15 | ||||||||||||||||||
| ANOVA | |||||||||||||||||||
| df | SS | MS | F | Significance F | |||||||||||||||
| Regression | 1 | 19933593750 | 19933593750 | 222.2858866 | 1.48781E-09 | ||||||||||||||
| Residual | 13 | 1165781250 | 89675480.77 | ||||||||||||||||
| Total | 14 | 21099375000 | |||||||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||||||||
| Intercept | -16776375 | 1130718.09 | -14.83692102 | 1.57972E-09 | -19219142.92 | -14333607.08 | -19219142.92 | -14333607.08 | |||||||||||
| Year | 8437.5 | 565.9236469 | 14.90925507 | 1.48781E-09 | 7214.896294 | 9660.103706 | 7214.896294 | 9660.103706 | |||||||||||
Using linear regression relationships, answer the questions a) through c) below and on the following page.
a) Develop a projection for the amount of the prize for the winner for the year 2008 if the purse winnings for that year are projected to be $996,430. As part of your answer, include the independent and dependent variables and the accompanying linear regression relationship.
b) Now let’s suppose that we believe the prize for the winner is a function of time (dependent on time). Given this belief, develop a projection for the amount of the prize for the winner for the year 2008 and discuss your results compared to what you found in part a)
c) Would you recommend using the forecasts you found in parts a) and b) based on the strengths of the relationship? Why?
In: Operations Management