comparative analysis There are primarily two types of recoding that you would

Comparative analysis there are primarily two types of

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comparative analysis There are primarily two types of re‐coding that you would encounter in this unit ‐ Creating new variables that allow you to classify/group your responses differently ‐ Use a different set of values to code an existing variable (often to create dummy variables ) 43 Data manipulation ‐ re‐coding Re‐coding example: create new variable “age group” The new variable contains two categories Young (<=35) is assigned the value 1 Middle aged and older (> 35) is assigned the value 2 44 Subject Age Income 1 29 $40,000 2 45 $36,000 4 22 $16,000 5 41 $98,000 6 33 $60,000 7 22 $24,000 9 33 $55,000 10 45 $80,000 Subject Age Income Age Group 1 29 $40,000 1 2 45 $36,000 2 4 22 $16,000 1 5 41 $98,000 2 6 33 $60,000 1 7 22 $24,000 1 9 33 $55,000 1 10 45 $80,000 2 45 Re‐coding example: re‐assigning value to create dummy variables current coding ‐ Domestic – 1 ‐ International ‐ 2 Nationality Variable Re‐coding into a dummy variable ‐ Domestic – 0 ‐ International ‐ 1 Subject Nationality Income 1 1 $40,000 2 2 $36,000 4 2 $16,000 5 2 $98,000 6 1 $60,000 7 2 $24,000 9 1 $55,000 10 1 $80,000 Subject Nationality Income New Nationality 1 1 $40,000 0 2 2 $36,000 1 4 2 $16,000 1 5 2 $98,000 1 6 1 $60,000 0 7 2 $24,000 1 9 1 $55,000 0 10 1 $80,000 0
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10/04/2019 16 Quick recap about descriptive data characteristics 46 Categorical variables: counting and tallying data distribution (frequency and bar chart) Metric variables: the “average” behavior Distribution (histogram) Mean vs median – Outliers Data manipulation - re-coding Today’s agenda 47 Data preparation Coding (including the concept of dummy variable ) – Cleaning Getting to know your data – descriptive data characteristics Categorical variables: counting and tallying ( data distribution (frequencies and bar charts)) Metric variables: the “average” behavior (data distribution (histogram), mean , median and outliers ) Data manipulation - re-coding variables Intro to hypothesis testing Recall that most research questions are about variables and their relationships 4/10/2019 48 Relational – RQs that are about the relationship between two different constructs/variables Comparative – RQs that compare two different constructs or measures of the same construct across different groups or scenarios (often between 2 groups)
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10/04/2019Now you have the data, how do you “answer” a researchquestion (RQ) like the one below? 17 49 RQ: do male and female studentson averagediffer in theirgrade expectation for MKF2121?BTW, what are the variables involved? We already have the data for the variables collected throughthe mini survey on Moodle4/10/201950Gender – Q9Grade expectation – Q7How to answer the RQ? – compare the average grade
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