A market research analyst is helping a Real Estate Investment Trust (REIT) company to study the relationship

A market research analyst is helping a Real Estate Investment Trust (REIT) company to study the relationship between income and education level in a county in the state of Illinois. The outcome of the research will be used to decide whether to invest in Municipal bonds issued by local government of that county. As part of the study the analysis collected a random sample of 10 households, each identified by variable “ID”, and asked for education level of the main income provider of the household (variable “Income”, annual, in U.S. Dollar) and his/her education level (variable “Education”, number of years in school). Below table provides the data collected in this sample. ID
Education
Income
1
439,000
N
12 42,000
3
12 34,000
4
8 87,000
5
16 45,000
6
6 6
18 210,000
7 7
22 250,000
00
12 100,000
9

Based on this data:
(a)Calculated average of income variable
(b)Create two new categorical variables:
·“Education Level” with two levels: “Less than or equal 12 years”, “Greater than 12 years”
·“Income Level” with two levels: “Below or equal average”, “Above average”, using the average value calculated in part (a).
Show these new variables in two new columns, and for each household (each ID)
(c)Create a cross-tab table with “Education Level” and “Income Level” on rows and columns.
(d)Convert cross-table in part (c) above from count to percentage (either based on row totals or column totals)
(e)Without performing any statistical test, interpret the cross-tab table in part (d) and provide your conclusion if there is (or is not) evidence of dependency between “Education Level” and “Income Level” variables.
NOTE: You can do these steps in Excel and Copy results.

 


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