Lecture1-2

# Lecture1-2 - Data Scales of Measurement Describing the...

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Data Scales of Measurement Describing the Shape of a Distribution Graphical Approaches Word descriptions, distribution curves Numerical measures More Measures of Variability Scatter Plots to Study Relationships Between Variables 2
Consists of values of some variables measured or observed for some individuals . E.g., the data set from the class survey (14 variables for the students in our class). Variable is a characteristic of an individual. Qualitative or Categorical : places an individual into one of several groups or categories (finitely many possible) Quantitative : measurements represent quantities, e.g. “how many” (infinitely many possible), could be discrete or continuous 3

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Quantitative Ratio variable, almost all quantitative variables are ratio variables Ratios meaningful, inherently defined zero (e.g., salary, weight, distance) Interval variable, very few quantitative variables are interval variables Ratios not meaningful, no inherently defined zero (e.g., temperature) Categorical Ordinal variable Meaningful ordering or ranking of categories (e.g., class) Nominative variable No meaningful ordering or ranking of categories (e.g., gender, color) 4
5 R a t i o ( a l m o s t a l l ) I n t e r v a l ( v e r y f e w ) Q u a n t i t a t i v e O r d i n a l N o m i n a t i v e Q u a l i t a t i v e ( C a t e g o r i c a l ) D a t a

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Initial examination of the data is called Exploratory Data Analysis (EDA). Strategy for EDA: Begin by examining each variable and then move on to the study of relationships At each stage start with graphs and then add numerical summaries 6
Describes what possible values the variable takes and how frequently it takes those values. We describe the overall pattern of a distribution by its shape, center, and spread. There are many ways to describe and display distributions. Tables Graphs Word descriptions Numerical measures 7

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The values of a categorical variable are the labels for the categories. The distribution of a categorical variable is described by either the count or the percent of individuals who fall in each category. E.g., data on young American adults from the 1999 Current Population Survey 8 Education Count (millions) Percent Less than high school 4.7 12.3 High school graduate 11.8 30.7 Some college 10.9 28.3 Bachelor’s degree 8.5 22.1 Advanced degree 2.5 6.6
Bar chart: the height of each bar is proportional to the count (or percent) in each category. 9

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## This note was uploaded on 09/16/2009 for the course BUAD 14871 taught by Professor Yingyingfan during the Fall '09 term at USC.

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Lecture1-2 - Data Scales of Measurement Describing the...

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