State and describe two examples of how business analytics is used in organizations. 

 

(b) What are the logical functions in Excel. Give a real world example where using a logical function is useful.

 

(c) What is a line chart? What is a scatter diagram? What is the difference between a line chart and a scatter diagram? Give one real world example when using a line chart is appropriate and one real world example when using a scatter diagram is appropriate. 

 

(d) Explain the basic concept of cause-and-effect modeling. Give a real world example when this approach is useful. 

 

(e) Explain how the simple moving average method works in forecasting techniques. Give a real world example when this approach is useful. 

 

 

2. A grocer operates a store in a small city. The total weekly sales of an item depend on the price, coupon (available = 1, not available = 0), and advertising expenditures. After analyzing the data, an analyst has determined the following predictive model:

 

Total Sales = 1210.20 + 50.50 X Price + 120.45 X Coupon + 4.8 X Advertising

 

(a) Explain how to interpret the numbers in this model.

(b) Suppose that for a week, the price for the item was $8, coupon was available, and advertising expenditure was $250. What is the predicted total sales amount for that week?

 

 

3. A manufacturer of dishwashers is preparing to set the price on a new design. Demand is thought to depend on the price and is represented by 

 

D = 2100 - 4.3P

 

The accounting department estimates that the total costs can be represented by 

 

C = 4840 + 6.2D

 

(a) Develop a model for the total profit in terms of the price, P.

(b) What will be the total profit if the price is $380.

 

 

 

 

4. Following is the normalized distance matrix of sales data for four customers of a company. Apply single linkage clustering until only one option remains. Draw a dendogram illustrating the clustering process. What conclusions can you draw from this analysis for this company?

 

Customer	1	2	3	4
1	0	3.88382	2.08990	2.70886
2		0	3.21080	1.97620
3			0	2.99488
4				0