Reference no: EM13825883
Part 1
Question 1
On a Minnesota December day, the probability of snow is 0.30. The probability of a cold day is 0.50. The probability of snow and cold weather is 0.15. Are snow and cold weather independent events?
Question 2
As a company manager for the Quick Money Business there is a 0.40 probability that you will be promoted this year. There is a 0.72 probability that you will get a promotion or a raise. The probability of getting a promotion and a raise is 0.25. If you get a promotion, what is the probability that you will get a raise?
Question 3
Alison has all her money invested in two mutual funds, A and B. She knows that there is a 40% chance that fund A will rise in price.
There is a 60% chance that fund B will rise in price given that fund A rises in price.
There is also a 30% chance that fund B will rise in price.
What is the probability that at least one of the funds will rise in price?
Question 4
If P(A) = 0.40, P(B | A) = 0.35, P(A ? B) = 0.69, then P(B) =
Question 5
A recent survey shows that the probability of a college student drinking alcohol is 0.6.
Further, given that the student is over 21 years old, the probability of drinking alcohol is 0.8.
It is also known that 30% of the college students are over 21 years old.
Of the students who are not over 21, what is the probability they drink alcohol?
Question 6
Alison has all her money invested in two mutual funds, A and B. She knows that there is a 40% chance that fund A will rise in price.
There is a 60% chance that fund B will rise in price given that fund A rises in price.
What is the probability that both fund A and fund B will rise in price?
Question 7
Three workers at a fast food restaurant pack the take-out chicken dinners. John packs 45% of the dinners, Mary packs 25% of the dinners and Sue packs the remaining dinners. Of the dinners John packs 4% do not include a salt packet. If Mary packs the dinner 2% of the time the salt is omitted. Lastly, 3% of the dinners do not include salt if Sue does the packing. What is the probability that you will have salt packed with your dinner?
Question 8
Use the table below which contains data on 1200 students in a law class. If a student passed the course, what is the probability that their GPA was greater than 3.0?
GPA 0.0 - 2.0 GPA 2.01 - 3.0 GPA 3.01 - 4.0 Total
Pass 100 200 540 840
Fail 200 120 40 360
Total 300 320 580 1200
Question 9
A six-sided die is tossed. You win $10 if the tossed die shows a 5 or an even number. What is the probability that you will win the game?
Question 10
The final exam in QMB3600 is worth what percent of your total course grade?
Part 2
Question 1
Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). The percent of the variability in the prediction of Y that can be attributed to the variable X
Regression Statistics
Multiple R 0.7732
R Square 0.5978
Adjusted R Square 0.5476
Standard Error 3.0414
Observations 10
ANOVA
df SS MS F Significance F
Regression 1 110 110 11.892 0.009
Residual 8 74 9.25
Total 9 184
Coefficients Standard Error t Stat P-value
Intercept 39.222 5.942 6.600 0.000
X -0.556 0.161 -3.448 0.009
Question 2
Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). Is this model significant at the 0.05 level?
Regression Statistics
Multiple R 0.1347
R Square 0.0181
Adjusted R Square -0.0574
Standard Error 3.384
Observations 15
ANOVA
df SS MS F Significance F
Regression 1 2.750 2.75 0.2402 0.6322
Residual 13 148.850 11.45
Total 14 151.600
Coefficients Standard Error t Stat p-value
Intercept 8.6 2.2197 3.8744 0.0019
X 0.25 0.5101 0.4901 0.6322
Question 3
A regression analysis between sales and price resulted in the following equation Y=50,000 - 8000X
The above equation implies that an
Question 4
The actual demand for a product and the forecast for the product are shown below. Calculate the MAD.
Observation Actual Demand (A) Forecast (F)
1 35 ---
2 30 35
3 26 30
4 34 26
5 28 34
6 38 28
Question 5
Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast.
Time Period (t) Time Series Value (Y t) Exponential Smoothing
Forecast (F t)
1 22 22
2 26 22
If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is
Question 6
What is the forecast for June based on a three-month weighted moving average applied to the following past demand data and using the weights: .5, .3, and .2 (largest weight is for the most recent data)?
Month Demand Forecast
January 40
February 45
March 57
April 60
May 75
June 87
Question 7
The following time series shows the number of units of a particular product sold over the past six months. Compute the MSE for the 3-month moving average.
Month Units Sold
(Thousands)
1 8
2 3
3 4
4 5
5 12
6 10
Question 8
Given an actual demand of 61, forecast of 58, and an alpha factor of .2, what would the forecast for the next period be using simple exponential smoothing?