ADMS 2320 Lecture Notes - Lecture 7: Sample Size Determination, Confidence Interval, Alternative Hypothesis

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violetmuskrat777

15 Sep 2016

School

York University

Department

Administrative Studies

Course

ADMS 2320

Professor

Nursel Ruzgar

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Document Summary

Point estimator estimate in future from given point; not many people use this, not very useful. Interval estimator draw on probability, error, confidence to estimate what is going to happen. Confidence level is proportion of time you are correct with estimate; 1-confidence level = error. Significance level is proportion of time that you are going to be wrong. Alpha divided by 2 because you need 2 numbers since you need a lower and upper level number. No confidence level or not given one in question, assumption is confidence level is 95% Lead time - time it takes for initiation and completion of production process. Key words: estimate of the mean demand during lead time; estimate lead time demand with. Width of confidence interval (good for multiple choice question) Sample size (n), increasing sample size will decrease the confidence interval; we want intervals that are tight because it makes decision easier and it makes it more accurate.

Related Questions

1. The width of a confidence interval estimate for a proportion will be: a. narrower for 90% confidence than for 95% confidence. b. wider for a sample size of 100 than for a sample size of 50. c. narrower for 99% confidence than for 95% confidence. d. narrower when the sample proportion if 0.50 than when the sample proportion is 0.20. 2. When determining the sample size needed for a proportion for a given level of confidence and sampling error, the closer to 0.50 that p is estimated to be: a. the smaller the sample size required. b. the larger the sample size required. c. the sample size is not affected. d. the effect cannot be determined from the information given. 3. Which of the following would be an appropriate alternative hypothesis? a. The population proportion is less than 0.65. b. The sample proportion is less than 0.65. c. The population proportion is equal to 0.65. d. The sample proportion is equal to 0.65. 4. Which of the following would be an appropriate null hypothesis? a. The population proportion is equal to 0.60. b. The sample proportion is equal to 0.60. c. The population proportion is not equal to 0.60. d. All of these choices are true.






Expected Responses
Responses	Blue-collar workers	White-collar workers	Managers
For
Against


p =

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

ADMS 2320 Lecture Notes - Lecture 7: Sample Size Determination, Confidence Interval, Alternative Hypothesis

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