代写BSD131 Business Analytics Sample final exam questions调试Haskell程序

Sample final exam questions

Question 1:

a. Based on the order month, which month has the highest average cost per order?

b. What is the standard deviation of the cost per order rounded to the nearest 2 decimal places (e.g. 1234.56)?

c. Is the distribution of item costs positively or negatively skewed?

Question 2. How many outliers are there in the cost-per-order column?

Question 3. What is the relative frequency of Gaskets as a percentage to 2 decimal places (e.g. 12.34)?

Question 4. Imagine that we know that 14.89% of customers our sales team contacts will order Airframe. Fastners. For every 40 customer contacts, what is the binomial probability that exactly 5 customers will make a purchase? Write your answer down to the nearest 2 decimal places as a percentage (e.g. 12.34).

Question 5. What is the probability that a purchase order is for the supplier Pylon Accessories for the Item (Description) Gasket as a percentage to the nearest 1 decimal place (e.g. 12.3)?

Question 6. Suppose that we want to find a 95% confidence interval for the mean cost per order. We also don't know the population standard deviation, so we can use the worksheet in the stimulus, Question 6. Using the same sample data in Question 1, use the cost per order sample standard deviation, sample size (there are 94 purchase orders in the sample), and cost per order sample average to work out what the upper bound is for the cost per order population mean. Write down the upper bound confidence interval to the nearest 1 decimal place (e.g. 1234.5).

Question 7. We want to predict the next purchase order amount (Cost per order) using a Prediction Interval. The data you will use is the same data as in the Question 1 stimulus. Use the worksheet in the Question 7 stimulus to work out the cost per order sample mean, cost per order sample standard deviation, and number of samples to predict the lower PI with a 95% confidence. Write down the lower PI to the nearest 2 decimal places  (e.g. 12.34).

Question 8. Use simple linear regression to predict what the cost per order might be for a quantity of 13750 airframe. fasteners. Write your answer to the nearest 2 decimal places.

Question 9. Suppose that a logistic regression analysis was performed on our purchase order data set and produced the following table measuring true negative, true positive, false negative, and false positive predictions. In the answer boxes below, write down:

a. the logistic regression model Accuracy % (to 2 decimal places, e.g. 12.34).

b. the logistic regression model Sensitivity% (to 2 decimal places, e.g. 12.34).

c. the logistic regression model Specificity % (to 2 decimal places, e.g. 12.34).

10. We want to predict Quantity, given some of the variables Item Cost, Cost per order, and A/P Terms (Months). Use a multiple linear regression to identify which variables are statistically significant in predicting Quantity.