Download Chapter 1 Intro

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Chapter 1: Exploring Data
Introduction
Data Analysis: Making Sense of Data
The Practice of Statistics, 4th edition - For AP*
STARNES, YATES, MOORE
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Chapter 1
Exploring Data
 Introduction:
Data Analysis: Making Sense of Data
 1.1
Analyzing Categorical Data
 1.2
Displaying Quantitative Data with Graphs
 1.3
Describing Quantitative Data with Numbers
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Introduction
Data Analysis: Making Sense of Data
Learning Objectives
After this section, you should be able to…

DEFINE “Individuals” and “Variables”

DISTINGUISH between “Categorical” and “Quantitative” variables

DEFINE “Distribution”

DESCRIBE the idea behind “Inference”
 Data
Analysis is the process of organizing,
displaying, summarizing, and asking questions
about data.
Definitions:
Individuals – objects (people, animals, things)
described by a set of data
Variable - any characteristic of an individual
Categorical Variable
– places an individual into
one of several groups or
categories.
Quantitative Variable
– takes numerical values for
which it makes sense to find
an average.
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is the science of data.
Data Analysis
 Statistics
Definition:
Distribution – tells us what values a variable
takes and how often it takes those values
Example
2009 Fuel Economy Guide
MODEL
2009 Fuel Economy Guide
2009 Fuel Economy Guide
MPG
MPG
MODEL
<new>MODEL
MPG
1
Acura RL
922 Dodge Avenger
1630 Mercedes-Benz E350
24
2
Audi A6 Quattro
1023 Hyundai Elantra
1733 Mercury Milan
29
3
Bentley Arnage
1114 Jaguar XF
1825 Mitsubishi Galant
27
4
BMW 5281
1228 Kia Optima
1932 Nissan Maxima
26
5
Buick Lacrosse
1328 Lexus GS 350
2026 Rolls Royce Phantom
18
6
Cadillac CTS
1425 Lincolon MKZ
2128 Saturn Aura
33
7
Chevrolet Malibu
1533 Mazda 6
2229 Toyota Camry
31
8
Chrysler Sebring
1630 Mercedes-Benz E350
2324 Volkswagen Passat
29
9
Dodge Avenger
1730 Mercury Milan
2429 Volvo S80
Variable of Interest:
MPG
25
<new>
Dotplot of MPG
Distribution
Data Analysis
generally takes on many different values.
In data analysis, we are interested in how often a
variable takes on each value.
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 A variable
2009 Fuel Economy Guide
Examine each variable
by itself.
Then study
relationships among
the variables.
MODEL
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2009 Fuel Economy Guide
2009 Fuel Economy Guide
MPG
MPG
MODEL
<new>MODEL
MPG
1
Acura RL
9 22 Dodge Avenger
1630 Mercedes-Benz E350
24
2
Audi A6 Quattro
1023 Hyundai Elantra
1733 Mercury Milan
29
3
Bentley Arnage
1114 Jaguar XF
1825 Mitsubishi Galant
27
4
BMW 5281
1228 Kia Optima
1932 Nissan Maxima
26
5
Buick Lacrosse
1328 Lexus GS 350
2026 Rolls Royce Phantom
18
6
Cadillac CTS
1425 Lincolon MKZ
2128 Saturn Aura
33
7
Chevrolet Malibu
1533 Mazda 6
2229 Toyota Camry
31
8
Chrysler Sebring
1630 Mercedes-Benz E350
2324 Volkswagen Passat
29
9
Dodge Avenger
1730 Mercury Milan
2429 Volvo S80
25
Start with a graph or
graphs
Add numerical
summaries
Data Analysis
How to Explore Data
<new>
Population
Sample
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Data Analysis
From Data Analysis to Inference
Collect data from a
representative Sample...
Make an Inference
about the Population.
Perform Data
Analysis, keeping
probability in mind…
Activity: Hiring Discrimination
Follow the directions on Page 5

Perform 5 repetitions of your simulation.

Turn in your results to your teacher.

Teacher: Right-click (control-click) on the graph to edit the counts.
Data Analysis
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Introduction
Data Analysis: Making Sense of Data
Summary
In this section, we learned that…

A dataset contains information on individuals.

For each individual, data give values for one or more variables.

Variables can be categorical or quantitative.

The distribution of a variable describes what values it takes and
how often it takes them.

Inference is the process of making a conclusion about a population
based on a sample set of data.
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Looking Ahead…
In the next Section…
We’ll learn how to analyze categorical data.
Bar Graphs
Pie Charts
Two-Way Tables
Conditional Distributions
We’ll also learn how to organize a statistical problem.