Please view the following video before answering this question. Video Solution: 11.03-PR019A proposed project has the following cash flow estimates:Part aEnd of Year Mean Net Cash Flow Standard Deviation of Cash FlowON MV5Mean: $3Standard Deviation: $4$-35,000$3.800$8,100$12.400$12.400Click here to access the TVM Factor Table Calculator$12,400Assuming independent cash flows, a normally distributed net present value, and a minimum attractive rate of return of 18%.determine an analytical solution for the following:The mean and standard deviation of net present value.$750$1.800$2,900$4.900$6,100$7.000 The mean and standard deviation of net present value.Mean: $Standard Deviation: $Carry all interim calculations to 5 decimal places and then round your final answer to the nearest dollar. The tolerance is £5.Save for LaterAttempts: 0 of 3 usedSubmit A

We are to find out the mean and standard deviation of net present value.Mean: $ Standard Deviation:…

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College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter4: Polynomial And Rational Functions

Section4.6: Rational Functions

Problem 11SC: Find the mean hourly cost when the cell phone described above is used for 240 minutes.

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severe storms indicate that e3.5 feet. Does this information suggest that the storm is (perhaps temporarily) increasing above the severe rating? Use off fxed cement piers. Suppose that a reading of 31 waves showed an average wave height of x= 16.7 feet. Previous studies of Weatherwise is a magazine published by the American Meteorological Society. One issue gives a rating system used to classify Nor'easter storms that frequently hit New England and can cause much damage near the ocean. A severe storm has an average peak wave height of 164 feet for waves hitting the shore. Suppose that a Nor'easter is in progress at the severe storm class rating. Peak wave heights are usually measured from land C (a) What is the level of significance? State the null and alternate hypotheses. Ho: H- 16.4 ft; H:>'16.4 ft Ho: H 16.4 ft; H1: = 16.4 ft Ho: H- 16.4 ft; H: H+ 16.4 ft (b) What sampling distribution will you use? Explain the rationale for your choice of sampling distribution. The standard…
Table 1. Violent victimization, by type of crime, 2016, and 2017 Appendix table 3. Standard errors for table 1: Violent victimization, by type of crime, 2016, and 2017 From the estimation of the number of Rape/sexual assault (298,410) in 2016 at 95% CI, what is the lower limit? (Round off to one decimal place if necessary)
Solve attached photo.
Please solve within 1hour and show all the steps.
c. Predict expected lawn mower sales for the first week in August, given fertilizer sales six weeks earlier of 1.8 tons. (Round your answer to two decimal points.) Resulting Forecast
¶ ¶ Situation: The "Small Town Restaurant" uses a forecast of weekly sales revenue to plan their inventory ordering and staffing for the upcoming week. They have been using a regression forecast for the past year and wonder if it is the most accurate method. You have been brought in to determine if another forecasting technique would be more accurate. Data for their weekly sales for the past year is below: ¶ Week Revenue. X Week 1 2 $3,016 3 $3,062.¤ ¤ 4 $ 3,074. X 5 $3,002. 6 ----3,054-¤¤ 7 $3,002.¤ ¤ 8 9 $3,078¤ ¤ 10 $3,010- X 11 $3,148. 12 $3,146 $3,198. 13 X ¶ $3,157.** $ Forecasting S $ 2,984-¤¤ A - Small Town Restaurant Revenue. 14 $3,157 ¤ $3,016 ¤ 15 16 $3,019 ¤ 17 $3,045 ¤ 18 19 $3,046 ¤ $3,157 ¤ $3,016 ¤ $3,078 ¤ 22 $2,984 20 21 ¤ 23 $3,002 ¤ 24 $3,054 ¤ 25 $3,002 ¤ 26 $2,941 X A Week Revenue. 27 $2,899 ¤ 28 $2,942 ¤ 29 $3,062 X ¤ 30 $3,074 31 $3,013 ¤ ¤ 32 $3,067 33 $3,148 ¤ 34 $3,146 ¤ 35 $3,198 ¤ 36 $3,082 ¤ 37 $3,146 ¤ 38 $3,150 ¤ 39 $3,221 ¤ X B Week Revenue. ¤ 40…
Stép 1 (a) Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8? The MSE, mean squared error, is a measure of forecast accuracy and is the average of the squared forecast errors. Before this can be found, we first need to find the forecast values, forecast error, and squared forecast errors. Forecasts will be made using the most recent values known. There will be no forecast for the first month. The forecast value for month 2 will be the observed value from month 1, so the forecast value for month 2 is The forecast value for month 3 will be the observed value from month 2, so the forecast value for month 3 is This pattern will continue for the rest of the months. Complete the column for the forecast value in the table below. Month Value Forecast Value 1 21 2 29 25 4 30 5 26 25 7 30 Find the forecast for month 8 using this pattern. Submit Skip (you cannot come back)
The two scatterplots that follow break the data down further to investigate the relationships between global temperature anomalies and coal emissions and global temperature anomalies and motor gasoline emissions. Global Temperature Anomaly Global Temperature Anomaly 0.7 0.6 y = 0.0006x -0.6093 0.5 R² = 0.6965 0.4 0.3 0.2 0.1 0 -0.1 -0.2 Global Temperature Anomaly by Coal Emissions 0.8 0.7 0.6 0.5 0.4 0.3 0 0.2 0.1 0 -0.1 0 -0.2 500 200 1000 Global Temperature Anomaly by Motor Gasoline Emissions 400 ● 1500 Coal Emissions y = 0.0017x -1.4275 R² = 0.7227 600 800 Motor Gasoline Emissions 2000 000 1200 2500 1400 Part A: Use the coefficient of determination to decide which energy type has a stronger association with global temperature anomalies. Motor Gasoline Emissions O neither coal nor motor gasoline there is not enough information to tell O Coal Emissions
. State the interval estimate that contains more possible values of the population mean (precision) for a 90% CI or a 95% CI for the same data.
Please answer the last 2 parts of the question: Is the actual value above, below or on the line? What is the interpretation of the residual? Thanks!
Please see attached image, I need to create a table showing an exponential smoothing average using the alpha as 0.2 and an assumed forecast for Janaury of year one of 35,000.
Researchers fed mice a specific amount of Toxaphene, a poisonous pesticide, and studied their nervous systems to find out why Toxaphene causes tremors. The absolute refractory period, time required for nerves to recover after a stimulus, was measured and varies Normally. The measurements, in milliseconds, for four mice were 1.7, 1.8, 1.9, and 2.0. Part A: Find the mean refractory period and the standard error of the mean. Part B: Calculate a 90% confidence interval for the mean absolute refractory period for all mice when subjected to the same treatment. Part C: Suppose the mean absolute refractory period for unpoisoned mice is known to be 1.3 milliseconds. Toxaphene poisoning should slow nerve recovery and therefore increase this period. Do the data give good evidence to support this theory? What can you conclude from a hypothesis test? Justify your response with statistical reasoning.

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