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Lecture 2

STAT 101 Lecture Notes - Lecture 2: Contingency Table, Dependent And Independent Variables


Department
Statistics
Course Code
STAT 101
Professor
haleyjeppson
Lecture
2

Page:
of 4
2.1$ Summarizing$ and$ Displaying$ a$Single$ Categorical$ Variable
Frequency$ table-contains$ categories$ and$ your$ values
Relative$ frequency$ table-displays$ the$ percentages$ of$ the$ categories
Frequency) Tables
Bar) Charts)
Pie) Chart
Chapter(Two
Saturda y,$ Septem be r$ 3,$ 2016
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Response$ variable-variable$ of$interest$ (rows)
Explanatory$ variable-explains$ the$ differences$ in$ the$ response$ variable$
(columns)
Contingency$ table-compares$ various$ variables
Marginal$ distributions-looks$ at$ percentages$ for$ each$ variable$ separately,$
take$ the$ total$ of$ each$ subcategory$ divided$ by$ the$ grand$ total
Conditional$ distributions-looks$ at$ percentages$ for$ one$ variable$
conditioned$ on$ a$particular$ category,$ take$ the$ totals$ of$ the$ specific$
category$ divided$ by$ just$ the$ total$ in$that$ row$
The) Relationship) Between) Two) Categorical) Variables
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category$ divided$ by$ just$ the$ total$ in$that$ row$
Rows$ are$ categories$ of$ response$ variable$ while$ columns$ are$ the$
categories$ of$ the$ explanatory$ varible$
Mosaic$ plot-graphical$ summary$ of$ conditional$ distributions$ in$
contingency$ table
Association=$ lines$ of$ plot$ do$not$line$ up,$ conditional$ distributions$ are$
different
No$association=$ lines$ in$plot$match$ up,$conditional$ distributions$ are$ the$
same
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