ADM 2304 Lecture Notes - Lecture 1: Statistical Parameter, Statistic, Random Variable
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1. The Department of Transportation would like to test the hypothesis that the average age of cars on the road is less than 10 years. A random sample of 50 cars had an average age of 9.5 years. It is believed that the population standard deviation for the age of cars is 3.4 years. The Department of Transportation would like to set = 0.10. The conclusion for this hypothesis test would be that because the test statistic is
A. more than the critical value, we can conclude that the average age of cars on the road is less than 10 years.
B. more than the critical value, we cannot conclude that the average age of cars on the road is less than 10 years.
C. less than the critical value, we can conclude that the average age of cars on the road is less than 10 years.
D. ess than the critical value, we cannot conclude that the average age of cars on the road is less than 10 years.
2. The p-value for a hypothesis test is defined as the probability of observing a
A. critical value at least as extreme as the one selected for the hypothesis test, assuming the null hypothesis is true. | ||
B. critical value at least as extreme as the one selected for the hypothesis test, assuming the null hypothesis is false. | ||
C. sample mean at least as extreme as the one selected for the hypothesis test, assuming the null hypothesis is true. | ||
D. population mean at least as extreme as the one selected for the hypothesis test, assuming the alternative hypothesis is true. |
QUESTION 1
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The expected frequency of satisfied customers from the Berwicksample is ________.
60 | ||
75 | ||
80 | ||
90 |
QUESTION 2
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The expected frequency of satisfied customers from the Miltonsample is ________.
60 | ||
75 | ||
80 | ||
90 |
QUESTION 3
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The expected frequency of satisfied customers from the Leesburgsample is ________.
60 | ||
75 | ||
80 | ||
90 |
QUESTION 4
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The chi-square test statistic for these samples is ________.
1.49 | ||
2.44 | ||
4.15 | ||
5.33 |
QUESTION 5
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The degrees of freedom for the chi-square critical value is________.
1 | ||
2 | ||
3 | ||
4 |
QUESTION 6
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
The chi-square critical value using ? = 0.05 is________.
2.706 | ||
3.841 | ||
5.991 | ||
7.815 |
QUESTION 7
Lisa is a regional manager for a restaurant chain that haslocations in the towns of Berwick, Milton, and Leesburg. She wouldlike to investigate if a difference exists in the proportion ofcustomers who rate their experience as satisfactory or betterbetween the three locations. The following data represent thenumber of customers who indicated they were satisfied from randomsamples taken at each location.
Berwick | Milton | Leesburg | |
Number Satisfied | 80 | 85 | 60 |
Sample Size | 100 | 120 | 80 |
Using ? = 0.05, the conclusion for this chi-square testwould be that because the test statistic is
More than the critical value, we can reject the null hypothesisand conclude that there is a difference in proportion of satisfiedcustomers between these three locations | ||
Less than the critical value, we can reject the null hypothesisand conclude that there is a difference in proportion of satisfiedcustomers between these three locations | ||
More than the critical value, we fail to reject the nullhypothesis and conclude that there is no difference in proportionof satisfied customers between these three locations | ||
Less than the critical value, we fail to reject the nullhypothesis and conclude that there is no difference in proportionof satisfied customers between these three locations |
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
A. The rejection region and the t-table value generally gets smaller for sample size below 31. |
A. Yes. The data are significantly correlated through the 12th 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. |
A. Type 2 error |
A. Yes. They move in the same direction as statistical significance. |
A. The weight cannot be calculated since the data observation is not given. |
A. Yes. The correlation coefficient is .873 that is greater than .05. |
A. Yes, since the residuals randomly vary in magnitude. |
A. -101.0 |
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