EC295 Lecture Notes - Lecture 2: Standard Deviation, Random Variable, Normal Distribution

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17 Jan 2018

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Standard normal distributions: normal distribution mean 0 and standard deviation 1. Expected value: the weighted average of all possible values of a random variable. Variance: expected value of squared distance from the mean. Standard deviation: the square root of the variance (more useful because it is measured in same units as the variable. If c is a constant, e(c) = c. If a and b are constants, e(ax + b) = ae(x) + b. If c is a constant, var(c) = 0. If a and b are constants, var(ax + b) = (a^2)var(x) Two random variables: most interesting application involve multiple random variables (how one influence the others, conditional expectation: the average value of a random variable, for a given value of another. Joint distribution: describes likelihood of simultaneous occurrence of two or more events random variable: the law of iterated expectations: the expected value of a random variable is the average of conditional expectations.

Related Questions

1. You are given only three quarterly seasonal indices and quarterly seasonally adjusted data for the entire year. What is the raw data value for Q4? Raw data is not adjusted for seasonality.

Quarter Seasonal Index Seasonally Adjusted Data

Q1 .80 295

Q2 .85 299

Q3 1.15 270

Q4 --- 271

2. One model of exponential smoothing will provide almost the same forecast as a liner trend method. What are linear trend intercept and slope counterparts for exponential smoothing?

A. Alpha and Delta

B. Delta and Gamma

C. Alpha and Gamma

D. Standard Deviation and Mean

3. When performing correlation analysis what is the null hypothesis? What measure in Minitab is used to test it and to be 95% confident in the significance of correlation coefficient.

A. Ho: r = .05 p < .5

B. Ho: r = 0 p >.05

C. Ho: r ? 0 p?.05

D. Ho: r = 0 p?.05

In decomposition what does the cycle factor (CF) of .80 represent for a monthly forecast estimate of a Y variable?

A. The estimated value is 80% of the average monthly seasonal estimate.
B. The estimate is .80 of the forecasted Y trend value.
C. The estimated value is .80 of the historical average CMA values.
D. The estimated value has 20% more variation than the average historical Y data values.

5. A Wendy's franchise owner notes that the sales per store has fallen below the stated national Wendy's outlet average of $1,368,000. He asserts a change has occurred that reduced the fast food eating habits of Americans. What is his hypothesis (H1) and what type of test for significance must be applied?

A. H1: u ? $1,368,000 A one-tailed t-test to the left.
B. H1: u = $1,368,000 A two-tailed t-test.
C. H1: u < $1,368,000 A one-tailed t-test to the left.
D. H1: p < $1,368,000 A one-tailed test to the right

6. As the sample size from a population increases, for a given level of significance what happens to the null hypothesis rejection region and size of the t-table value?

A. The rejection region and the t-table value generally gets smaller for sample size below 31.
B. The rejection region gets larger and the t-table value generally gets smaller for sample sizes below 31.
C. The rejection region remains unchanged while the t-table value gets smaller for all sample sizes.
D. The zero mean hypothesis region gets larger and the t-table value gets larger as well for sample sizes below 31.

7. You obtained autocorrelation LBQ value of 18.58 for the 12^th lag from a data sample. Are the data significantly correlated at the lag examined or not? You want to be 95% confident in your answer.

A. Yes. The data are significantly correlated through the 12th lag.
B. No. The data are not significantly correlated through the 12^th lag.

C. No. Only the 12 lag period is not correlated.

D. You cannot tell since the number of sample observations is not provided.

E. The p-value is above .05 so the data is correlated.

8. Sometimes forecasters get lazy or forgetful and do not check the significance of XY data correlations and use the X variable to forecast Y. What is the result of this?

A. Type 2 error
B. Autocorrelation error
C. Type 3 error
D. Type 1 error

9. Do error measures indicate the statistical significance of forecast model variables?

A. Yes. They move in the same direction as statistical significance.
B. Yes. As error measures decrease the variable significance increases.
C. No They indicate only the magnitude of estimate error.
D. No. They indicate only the statistical significance of a forecast or fitted values.

10. In exponential smoothing what is the weight of the alpha coefficient for a time series data observation from the 3^rd previous period if the original alpha value is set at .8?

A. The weight cannot be calculated since the data observation is not given.
B. The weight is zero since the alpha value is set relatively high.
C. .548
D. .0064

11.Given the data series below for variables Y (Monthly Inventory Balance) and X (Monthly Sales) are they significantly correlated at the 95% confidence level and how can you tell?

Ending Inv. Bal. Y		Monthly Sales X
1544		5053
1913		5052
2028		7507
1178		2887
1554		3880
1910		4454
1208		3855
2467		8824
2101		5716

A. Yes. The correlation coefficient is .873 that is greater than .05.
B. Yes. The correlation p-value is .002 which is less than .05.
C. No. The correlation coefficient is above the p-value.
D.No. The correlation p-value is greater than the 95% confidence level.

12. You have forecast the sales for your company for the last 12 months and the forecast residuals are shown below. Are these residuals to be considered random?
Residuals

-24

-348

-892

-62

-378

-489

-342

490

578

198

A. Yes, since the residuals randomly vary in magnitude.
B. Yes since the residuals are positive and negative and vary in magnitude.
C. No, since the residuals are stationary and vary in magnitude.
D. No, since the residuals indicate positive slope.

13. Given the residuals in problem 12 above what is the RMSE for the forecast?

A. -101.0
B. 411.8
C. 169603
D. 220.1

14. Which form of exponential smoothing can result in a na

Salvatore Chapter 1:

Discussion Questions: 9. How is the concept of a normal return on investment related to the distinction between business and economic profit?

Problems:

5. Determine which of the two investment projects a manager should choose if the discount rate of the firm is 10%. The first project promises a profit of $100,000 in each of the next 4 years, while the second project promises a profit of $75,000 in each of the next 6 years.

6. Determine which of the two investment projects of Problem 5 the manager should choose if the discount rate of the firm is 20%.

15. Integration Problem Samantha Roberts has a job as a pharmacist earning $30,000 per year, and she is deciding whether to take another job as the manager of another pharmacy for $40,000 per year or to purchase a pharmacy that generates a revenue of $200,000per year. To purchase the pharmacy, Samantha would have to use her $20,000 savings and borrow another $80,000 at an interest rate of 10% per year. The pharmacy that Samantha is contemplating purchasing has additional expenses of $80,000 for supplies, $40,000 for hired help, $10,000 for rent, and $5,000 for utilities. Assume that income and business taxes are zero and that the repayment of the principle of the loan does not start before 3 years. (a) What would be the business and economic profit if Samantha purchased the pharmacy? Should Samantha purchase the pharmacy? (b) Suppose that Samantha expects that another pharmacy will open nearby at the end of 3 years and that this will drive the economic profit of the pharmacy to zero. What would the revenue of the pharmacy be in 3 years? (c) What theory of profit would account for profits being earned by the pharmacy during the first 3 years of operation? (d) Suppose that Samantha expects to sell the pharmacy at the end of 3 years for $50,000 more than the price she paid for it and that she requires a 15% return on her investment. Should she still purchase the pharmacy?

Spreadsheet Problem (see attached Excel doc)

Using the data below, (Excel doc) where column A represents student numbers, column B the finishing time for a 1 mile race for 10 students, and column C the age of the students, (a) Use the data analysis tools to plot a line graph of all the finishing times. (b) Calculate a mean, median, mode, sample variance, sample standard deviation, and coefficient of variation to statistically describe the data. (c) Use Excel to fine the covariance between the two variables. What does the covariance indicate about the relationship between finishing time and age?

Note:

P15(d): Change ââ¦ for $50,000 more than â¦â to ââ¦ for $50,000 less than â¦â Compare the present value of economic profit in each of the next three years and the loss of $50,000 in the third year using 15% as the discount rate.

The spreadsheet problem (b): Calculate a mean, â¦. to statistically describe the data of both variables, Time and Age.

Individual problems:

3-1 You won a free ticket to see a Bruce Springsteen concert (assume the ticket has no resale value). U2 has a concert the same knight, and this represents your next-best alternative activity. Tickets to the U2 concert cost $80, and on any particular day, you would be willing to pay up to $100 to see this band. Assume that there are no additional costs of seeing either show. Based on the information presented, what is the opportunity cost of seeing Bruce Springsteen?

3-3 Because of the housing bubble, many houses are now selling for much less than their selling price just 2 to 3 years ago. There is evidence that homeowners with virtually identical houses tend to ask for more is they paid more for the house. What fallacy are they making?

Salvatore Chapter 3:

Discussion Questions:

9. How would you react to a sales managerâs announcement that he or she has in place a marketing program to maximize sales?

Problems:

1(a). Given the following total-revenue function: TR= 9Q - Q^2

Derive the total-, average-, and marginal- revenue schedules from Q=0 to Q=6 by 1âs.

7. Given the total-cost schedule: Q 0 1 2 3 4

TC 1 12 14 15 20

Derive the average- and marginal-cost schedules.

9. With the total-revenue curve of Problem 1 and the total-cost curve of problem 7, derive the total-profit function and show how the firm determines the profit-maximizing level of output.

Note:

DQ9: Does maximum sales (revenue) equal maximum profit (see figure 3-4)?

Revised P1(a): Derive the total-revenue, average-revenue, and marginal-revenue schedules from Q = 0 to Q = 4 by 1s.

Average revenue (AR) = total revenue (TR)/Q

Marginal revenue (MR) = change in total revenue/change in Q

For example:

Q	TR	AR	MR
2	14	7 (=14/2)
3	18	6 (=18/3)	4 (=(18-14)/(3-2)

Revised P9: With the total-revenue schedule of Problem 1 and the total-cost schedule of Problem 7, show the profit-maximizing level of output (profit=TR-TC).

Froeb et al. Chapter 4:

Individual problems:

4-5 Your insurance firm processes claims through its newer, larger high-tech facility and its older, smaller low-tech facility. Each month, the high-tech facility handles 10,000 claims, incurs $100,000 in fixed costs and $100,000 in variable costs. Each month, the low-tech facility handles 2,000 claims, incurs $16,000 in fixed costs and $24,000 in variable costs. If you anticipate a decrease in the number of claims, where will you lay off workers?

4-6 A copier company wants to expand production. It currently has 20 workers who share eight copiers. Two months ago, the firm added two new copiers, and output increased by 100,000 pages per day. One month ago, they added five workers, and productivity also increased by 50,000 pages per day. Copiers cost about twice as much as workers. Would you recommend they hire another employee or buy another copier?

EC295 Lecture Notes - Lecture 2: Standard Deviation, Random Variable, Normal Distribution

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