EXCEL

ECO 6380 Prof. Tom Fomby Predictive Analytics for Economists Spring 2019

EXERCISE 1

Purpose: To learn how to treat missing observations and detect outliers using XLMiner ©. Go to the website for this course and download the file “Subset Example II.xlsx”. This file is just like the file Subset Example except I have put in one missing observation for Y, one missing observation for X1, and an outlier observe for X4. The missing observations are designated by blank spaces. Use this file and XLMINER to complete the following tasks. Hand in your work on Tuesday, February 5 on CANVAS.

a) Print out the data contained in the Subset Example II.xls file. b) Treat the missing observations in the Y and X1 variables by deleting the

observations (records) that have the missing values in Y or X1. After deletion you should have 28 observations. Print out the XLMiner sheet that displays this treatment of the data.

c) Treat the missing observations in the Y and X1 variables by replacing the missing observations with the mean of the non-missing observations for the given variable. Print out the XLMiner sheet that displays this treatment of the data.

d) The Variable X4 has an outlier observation in it. Generate a Box-Plot for the X4 variable and hand it in with this exercise. Which observation is the outlier? Explain to me the definition of the elements of the Box-Plot.