The demand for airplane passengers (Y) is a function of a average fare (X1), the fare of the competing airline, and the annual per capital income of the passengers(X3)
Passenger seat sold Fare of the Fare of the competing Annual Per Capital
of the airline airline airline Income of passenger
648 250 250 $105
336 265 250 102
378 265 240 103
333 230 240 105
112 225 240 100
137 225 260 96
109 220 250 93
98 230 240 95
60 235 240 95
83 245 250 97
91 240 250 99
105 250 240 102
76 240 220 105
92 235 250 108
113 235 230 110
102 240 240 109
1. Find the demand for passenger seat (Y) as a function of the fare of the airline(X1), the fare f the competing airline (X2), and the annual per capital income of passengers (X3).
2. Graph the actual and the estimated Y and assess the goodness of fit.
3. State the effects of each of the independent variable on the demand for passengers.
4. State the significance or non significance of each of the independent variables.
5. If the fare of the airline increases to $300 (X1=300), the fare of the competing airline is $200 (X2=$200) and the annual income is (X3=$120), find how many tickets will the airline sell?
In the present problem an example for multiple regression analysis has been worked out. The general procedure for implementing multiple regression analysis by using regression analysis tool of M S Excel is provided. Explanations are given, for how to interpret the estimated regression parameters such as the regression coefficients, coefficient of determination etc. The excel sheet in which the example is worked out is also provided as an attachment.
Use of Simple-Linear and Multiple Regression Analysis
1. Can you think of an example where analysis of simple-linear and multiple regression analysis can be used? How is regression analysis being used in the financial industry, or how should it be used to formulate strategies?
2. What are examples in which regression analysis is used for forecasting?
3. What is correlation analysis? How can correlation analysis be used in a business decision or examples specifically related to strategy formulation and implementation?
4. What are some primary and secondary sources of data that may be used in correlation and regression analysis?
5. What is the difference between correlation and causation? Give examples