Assignment:
Q1: A sample of size 25 provides a sample variance of 400. The standard error, in this case equal to 4, is best described as the estimate of the standard deviation of means calculated from samples of size 25.
Blossom's Flowers purchases roses for sale for Valentine's Day. The roses are purchased for $10 a dozen and are sold for $20 a dozen. Any roses not sold on Valentine's Day can be sold for $5 per dozen. The owner will purchase 1 of 3 amounts of roses for Valentine's Day: 100, 200, or 400Â dozen roses. The number of alternatives for the payoff table is
2
3
4
The data below represents the amount of grams of carbohydrates in a sample serving of breakfast cereal.
10 18 24 30 19 22 24 20 18 25 20 22 19
The coefficient of variation for this data would be __________%.
Q2: The manager of a service station is in the process of analyzing the number of times car owners change the oil in their cars. She believes that the average motorist changes his or her car's oil less frequently than recommended by the owner's manual (two times per year). In a preliminary survey she asked 15 car owners how many times they changed their car's oil in the last 12Â months. The results are listed below.
1 1 2 1 2
2 0 1 0 1
2 3 1 3 0
The value of the test statistic in this problem is approximately equal to __________?
Q3: What would be your decision if a hypothesis test was conducted on this problem with the null hypothesis given as H0 : µ ≥ 2 and the alternate hypothesis given as H1 < 2.
Reject H0 at the 10%, 5% and 1% level of significance
Reject H0 at the 10% and 5% level of significance but do not reject H0 at the 1% level of significance
Reject H0 at the 10% level of significance but do not reject H0 at the 5% or 1% level of significance
Do not reject H0 at either the 10%, 5% or 1% level of significance.
Q4: The following information refers to the next two questions:
Refer to the following table which contains the sales (in $,000) for a department store for the first ten months of the year.
Month Sales
January 440
February 480
March 590
April 400
May 500
June 550
July 470
August 500
September 600
October 520
Using a three period moving average (i.e. MA(3)) as a forecasting method, what is the MSE for this forecasting model?
Using simple exponential smoothing (with a smoothing constant of 0.2) as a forecasting method, what is the MAPE for this forecast model
Q5: The following information refers to the next question:
The ordered array below resulted from taking a sample of 25 batches of 500 computer chips and determining how many in each batch were defective.
Defects
1 2 4 4 5 5 6 7 9 10 12 12 14
17 20 21 23 23 24 26 27 27 28 29 29
If a frequency distribution for the defects data is constructed, using '0 but less than 5' as the first class, what would be the cumulative relative frequency of the '10 but less than 15' class __________%
Q6: The following information refers to the next question:
A manufacturer of power tools claims that the average amount of time required to assemble their top-of-the-line table saw is fifty (50) minutes with a standard deviation of forty (40) minutes (the very large standard deviation is due to a variety of factors including a large variation in skills amongst the 'Do it yourself' home handyman which is traditionally one of the companies customer base). Suppose a random sample of 64 purchasers of this table saw is taken.
Q7: What is the probability that the sample mean will be less than 46 minutes __________?
The following information refers to the next question:
A quality control engineer is interested in the mean length of sheet insulation being cut automatically by machine. The desired length of the insulation is 12 metres. It is known that the standard deviation in the cutting length is 0.15 metres. A sample of 144 cut sheets yield a mean length of 12.14 metres. This sample will be used to obtain a 95% confidence interval for the mean length cut by machine.
Q8: What are the two limits of the confidence interval __________ and __________?
Q9: An insurance company wishes to examine the relationship between income (in $,000) and the amount of life insurance (in $,000) held by families. The company drew a simple random sample of families and obtained the following results:
Family Income Amount of life insurance
A 40 110
B 80 200
C 110 220
D 80 150
E 80 170
F 120 270
G 60 140
H 100 240
I 60 150
J 90 200
What is the least squares estimate of the slope?
What is the least squares estimate of the Y intercept?
What is the prediction for the amount of life insurance for a family whose income is $85,000?
What would be the residual (error) term for a family income of $90,000?