WEEK 13 & 14 ACTIVITY 9

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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.

Hi hlo Expert Hand written solution is not allowed.

Please provid the breakdown of coordinates for the graph and other answers with explanation:   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.

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.

1-24 A couple of entrepreneurial business students at State University decided to put their education into practice by developing a tutoring company for business students. While private tutoring was offered, it was determined that group tutoring before tests in the large statistics classes would be most beneficial. The students rented a room close to campus for $300 for 3 hours. They developed handouts based on past tests, and these handouts (including color graphs) cost $5 each. The tutor was paid $25 per hour, for a total of $75 for each tutoring session. (a) If students are charged $20 to attend the session, how many students must enroll for the company to break even? (b) A somewhat smaller room is available for $200 for 3 hours. The company is considering this possibility. How would this affect the break-even point?

DEPENDENT VARIABLE Qc R- SQUARE P- VALUE ON F     64 0.8093 0.0001             INDEPENDENTVARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20  4.01 2.04 0.0461           PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439   Explain the interceptand the coefficients of Pc, M, and PA.

Do not solve list all the X and Y variables, objective function and contraints for the below problem                                  ASW Publishing, Inc., a small publisher of college textbooks, must make a decision regarding which books to publish next year. The books under consideration are listed in the following table, along with the projected three­year sales expected from each book.     Book Subject Type of Book Projected Sales (000s)   Business calculus New 20   Finite mathematics Revision 30   General statistics New 15   Mathematical statistics New 10   Business statistics Revision 25   Finance New 18   Financial accounting New 25   Managerial accounting Revision 50   English literature New 20   German New 30   The books that are listed as revisions are texts that ASW already has under contract; these texts are being considered for publication as new editions. The books that are listed as new have been reviewed by the company, but contracts have not yet been signed.The company…

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DEPENDENT VARIABLE Qc R- SQUARE P- VALUE ON F     64 0.8093 0.0001             INDEPENDENTVARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20  4.01 2.04 0.0461           PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439 7. If the price of asphalt (PR) decreases by 15, what will happen to the estimated quantity of cement demanded?  Q = f( P, M, PR) where Qc =  demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard.

DEPENDENT VARIABLE Qc R- SQUARE P- VALUE ON F     64 0.8093 0.0001             INDEPENDENTVARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20  4.01 2.04 0.0461           PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439 9. Calculate the price elasticity, cross-price elasticity, and income elasticity of demand for cement. Explain these figures.  Q = f( P, M, PR) where Qc =  demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard.

DEPENDENT VARIABLE Qc R- SQUARE P- VALUE ON F     64 0.8093 0.0001             INDEPENDENTVARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20  4.01 2.04 0.0461           PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439 6. If tax revenue per capita (M) increases by 10, what will happen to the estimated quantity of cement demanded?  Q = f( P, M, PR) where Qc =  demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard.

DEPENDENT VARIABLE Qc R- SQUARE P- VALUE ON F     64 0.8093 0.0001             INDEPENDENTVARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20  4.01 2.04 0.0461           PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439 10. Write the resulting regression equation.  Q = f( P, M, PR) where Qc =  demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard.

Windies Cricket manufactures Windies supporter jerseys. The quantity q, of thesejerseys demanded weekly is related to the wholesale price per jersey p, by thefollowing equation:? = −0.006? + 15The weekly total cost incurred by Windies Cricket for producing q jerseys is:?(?) = 38? − 0.02?2 + 30,000a. Determine an expression to represent the weekly Revenue functionb. Determine an expression to represent the weekly Profit function.c. Calculate the weekly Revenue when ten dozen jerseys are produced and sold.d. Will Windies Cricket record a loss or profit if they were to produce and sell 2450jerseys?e. If Windies Cricket wishes to maintain a total cost less than $42,000.00, whatrange(s) of Windies jerseys should be produced. f. Calculate the equilibrium price and quantity for Windies jerseys.

What is this equation used for? What do the variables mean? Can you give an example how a research study can be applied to this formula? Does it account for control variables ?

Use the following STATA output to test whether the variable wgt is significant at 5% level: Source | SS df Number of obs = EC 3. Prob > F R-squared MS 392 300.76 0.0000 0.6993 Adj R-squared anba6970 4.2965 388) = Model Juu16656.4443 Residual 162,54916 5552.1481 388 18.4601782 Total Juu23818.9935 391 60.9181419 Root MSE Coef. Std. Err. P>It| [95% Conf. Interval] syl ena wat .2677968 -.012674 -.0057079 44.37096 .4130673 .0082501 .0007139 1.480685 -0.65 -1.54 -8.00 29.97 0.517 0.125 0.000 0.000 -1.079927 -.0288944 -.0071115 41.45979 .5443336 0035465 .0043043 47.28213 _cons The variable is not significant because p-value is less than 0.05. The variable is significant because p-value is less than 0.05. The variable is significant because p-value is less than 0.1. The variable is not significant because p-value is greater than 0.05

i need help with this question 8 from my microeconmics assigments. i have already gotten it wrong twice.

4. The estimation of the model with quarterly car sales in the U.S. from 1975 to 1990 gives: Source | df MS Number of obs = 64 F( 2, Prob > F 61) = 12.21 Model .32720224 2 .16360112 0.0000 Residual | .817286587 61 .013398141 R-squared Adj R-squared = 0.2625 Root MSE 0.2859 Total | 1.14448883 63 .018166489 .11575 lqne | cCoef. t P>|t| std. Err. [95% Conf. Interval] 1price lincome -.4604611 3.37186 6.89398 -.8280926 .1838504 -4.50 0.000 -1.195724 2.399991 . 4860261 4.94 0.000 1.428121 _cons 5.92543 .4843662 12.23 0.000 4.95688 Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?

I need help with c

not use ai please don't

Question 4 - Type Your Answers in Space Provided (a) An accountant wishes to undertake a cost analysis of electricity consumption of office heating for various maximum daily temperatures. He recorded the data over a period of 8 random days, as shown below: 2 3 4 5 6 8 Temp(°C) Max Electricity Consumption 26 31 25 26 14 20 16 34 35 20 37 24 42 41 40 17 You may use the following Excel print-outs or summary statistics provided to answer the questions. SUMMARY OUTPUT SUMMARY STATISTICS Regression Statistics Multiple R R Square Adjusted R Square Standard Error n = 8. 0.895 24 0.801 32 0.768 s2x = 48.29 4.862 s?y = 101.71 %3! Observations 8 Sxy = -62.7143 Coefficient Standard Error t Stat P-value 6.575 Intercept temp(°C) 63.172 9.607 0.000 -1.299 0.264 -4.911 0.003 Find the least squares regression line to predict the electricity consumption from the maximum temperature.

please answer in text form and in proper format answer with must explanation , calculation for each part and steps clearly

please answer the questions on the image attached with work shown, thanks!

The O'Neill Shoe Manufacturing Company will produce a special-style shoe if the order size is large enough to provide a reasonable profit. For each special-style order, the company incurs a fixed cost of $2,625 for the production setup. The variable cost is $55 per pair, and each pair sells for $80. (a) Let x indicate the number of pairs of shoes produced. Develop a mathematical model for the total cost (C) of producing x pairs of shoes. C =        (b) Let P indicate the total profit. Develop a mathematical model for the total profit realized from an order for x pairs of shoes. P =        (c) How large must the shoe order be before O'Neill will break even? x =

The table to the right contains price-demand and total cost data for the production of projectors, where p is the wholesale price (in dollars) of a projector for an annual demand of x projectors and C is the total cost (in dollars) of producing x projectors. Answer the following questions (A) - (D). (A) Find a quadratic regression equation for the price-demand data, using x as the independent variable. X 270 360 520 780 The fixed costs are $. (Round to the nearest dollar as needed.) ITTI y = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) Use the linear regression equation found in the previous step to estimate the fixed costs and variable costs per projector. The variable costs are $ per projector. (Round to the nearest dollar as needed.) (C) Find the break even points. The break even points are (Type ordered pairs. Use a comma to separate answers as needed. Round to the nearest integer as…

If the error term is correlated with any of the independent variables, the OLS estimators are: a. biased and consistent. b. unbiased and inconsistent. C. biased and inconsistent. d. unbiased and consistent. O a. a O b. b О с. с O d. d