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Activity on
PART I: (15 Points):
Problem 1.1 (5 Points) The response variable of the observed data and the fitted prediction are listed in the following table.
Response (Y) Model I Prediction (𝑌̂1) Model II Prediction (𝑌̂2)
3 3.2 3.3
4 4.3 4.2
5 4.9 4.8
6 5.7 5.9
7 6.9 7.1
1. Calculate the sum squared of error of Model I and Model II.
2. Calculate the average squared error of Model I and Model II.
3. Calculate both 𝑅𝐼2 and 𝑅𝐼𝐼2 .
4. Calculate both 𝑀𝐴𝑃𝐸𝐼 and 𝑀𝐴𝑃𝐸𝐼𝐼
5. Calculate both 𝑀𝐴𝐸𝐼 and 𝑀𝐴𝐸𝐼𝐼
Measure Model I Model II
SSE
ASE
R2
MAPE
MAE
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ISC 4241 – Activity #2
Problem 1.2 (10 Points) Work on Problem 1, Problem 2, and Problem 3 in the Textbook (Chapter 5 on Page 219)
PART II Programming (15 Points)
Data Used: “House_Prices_PRED.CSV” with three variables: ID, House_Price (observed value), and P_House_Price (Model Predicted Value).
Problem 2.1 (0 Points) Read the CSV file “House_Prices_PRED.CSV”
Problem 2.2 (3 Points) Write a program to calculate the sum squared of error and the average squared error of the Model (i.e., P_House_Price).
Problem 2.3 (3 Points) Write a program to calculate the R2 of the Model (i.e., P_House_Price).
Problem 2.4 (3 Points) Write a program to calculate the MAPE of the Model (i.e., P_House_Price).
Problem 2.5 (3 Points) Write a program to calculate the MAE of the Model (i.e., P_House_Price).
Problem 2.6 (3 Points) Write a program to produce a residual plot with residual on the Y-axis and observed value (House_Price) and to impose a loess line on the graph.
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