th edition For AP STARNES YATES MOORE Chapter 1 Exploring Data Introduction Data Analysis Making Sense of Data Chapter 1 Exploring Data Introduction Data Analysis Making Sense of Data ID: 716397
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The Practice of Statistics, 4th edition - For AP*STARNES, YATES, MOORE
Chapter 1: Exploring Data
Introduction
Data Analysis: Making Sense of DataSlide2
Chapter 1Exploring DataIntroduction
: Data Analysis: Making Sense of Data1.1 Analyzing Categorical Data1.2 Displaying Quantitative Data with Graphs1.3 Describing Quantitative Data with NumbersSlide3
IntroductionData Analysis: Making Sense of Data
After this section, you should be able to…DEFINE “Individuals” and “Variables”DISTINGUISH between “Categorical” and “Quantitative” variablesDEFINE “Distribution”DESCRIBE the idea behind “Inference”Learning ObjectivesSlide4
Data AnalysisStatistics is the science of data.
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.Slide5
Data AnalysisCommon to transform from categorical to quantitative.Letter grade (categorical) from scores on exams (quantitative)Reporting exceeds the standard, meets standard, or does not meet standard (categorical) based on results of standardized test scores (quantitative)Not every variable that takes number values is quantitative!
Zip code—categoricalArea codes—categoricalFloor of a building that employees work on—categorical Slide6
Example: U.S. CensusState
Number of Family MembersAgeGenderMaritalStatusTotal IncomeTravel time to workKentucky
2
61
Female
Married
21000
20
Florida
6
27
FemaleMarried2130020Wisconsin
227MaleMarried300005California
433
Female
Married
26000
10
Michigan349FemaleMarried1510025Virginia326FemaleMarried2500015Pennsylvania444MaleMarried4300010Virginia422MaleNever married/ single30000California130MaleNever married/ single4000015New York434FemaleSeparated3000040
Here is information about 10 randomly selected US residents from the 2000 census imported using Fathom software.
Who are the individuals in this data set?
What variables are measured? Identify each as categorical or quantitative. In what units where the quantitative variables measured?
Describe the individual in the first row. Slide7
Data AnalysisA variable generally takes on many different values. In data analysis, we are interested in how often a variable takes on each value.
Definition:Distribution – tells us what values a variable takes and how often it takes those values
Variable of Interest:
MPG
Dotplot of MPG Distribution
ExampleSlide8
Add numerical summaries
Data Analysis
Examine each variable by itself.
Then study relationships among the variables.
Start with a graph or graphs
How to Explore DataSlide9
Check your understandingJake is a car buff who wants to find out more about vehicles that students at his school drive. He gets permission to go to the student parking lot and record some data. Later, he does some research about each model of car on the Internet. Finally, Jake makes a spreadsheet that includes each car’s model, year, color, number of cylinders, gas mileage, weight, and whether it has a navigation system.Who are the individuals in Jake’s study?What variables did Jake measure? Identify each as categorical or quantitative. Slide10
Data AnalysisFrom Data Analysis to Inference
PopulationSample
Collect data
from a representative
Sample
...
Perform
Data Analysis
, keeping probability in mind…
Make an
Inference
about the
Population
.Slide11
Activity: Hiring DiscriminationFollow 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 AnalysisSlide12
IntroductionData Analysis: Making Sense of Data
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.
SummarySlide13
Looking Ahead…
We’ll learn how to analyze categorical data.Bar GraphsPie ChartsTwo-Way TablesConditional DistributionsWe’ll also learn how to organize a statistical problem
.
In the next Section…Slide14
Homework
Problems:1, 3, 5, 7, 8
Textbook
pg
7