4.3 Categorical Data Relationships.

Slides:



Advertisements
Similar presentations
Data Analysis for Two-Way Tables
Advertisements

Introduction to Stats Honors Analysis. Data Analysis Individuals: Objects described by a set of data. (Ex: People, animals, things) Variable: Any characteristic.
C HAPTER 1.1 Analyzing Categorical Data. I NDIVIDUALS AND V ARIABLES Individuals are the objects described by a set of data. Individuals may be people,animals,
Chapter 1: Exploring Data
Chapter 4: More on Two- Variable Data.  Correlation and Regression Describe only linear relationships Are not resistant  One influential observation.
Comparitive Graphs.
AP Statistics Section 4.2 Relationships Between Categorical Variables.
CHAPTER 1 Exploring Data 1.1 Analyzing Categorical Data.
Section 2.6 Relations in Categorical Variables So far in chapter two we have dealt with data that is quantitative. In this section we consider categorical.
Chapter 3 Graphical and Numerical Summaries of Categorical Data UNIT OBJECTIVES At the conclusion of this unit you should be able to: n 1)Construct graphs.
Chapter 3 Graphical and Numerical Summaries of Qualitative Data UNIT OBJECTIVES At the conclusion of this unit you should be able to: n 1)Construct graphs.
AP STATISTICS Section 4.2 Relationships between Categorical Variables.
Chapter 3 Graphical and Numerical Summaries of Qualitative Data UNIT OBJECTIVES At the conclusion of this unit you should be able to: n 1)Construct graphs.
Jeopardy Chi-Squared Confidence Intervals Hypothesis Testing Vocabulary Formulas Q $100 Q $200 Q $300 Q $400 Q $500 Q $100 Q $200 Q $300 Q $400 Q $500.
Warm-Up List all of the different types of graphs you can remember from previous years:
BPS - 5TH ED.CHAPTER 6 1 An important measure of the performance of a locomotive is its "adhesion," which is the locomotive's pulling force as a multiple.
Data Analysis Making Sense of Data.  Individuals: are the objects described by a set of data. Individuals may be people, but they may also by animals.
HW#8: Chapter 2.5 page Complete three questions on the last two slides.
Relations and Categorical Data Target Goal: I can describe relationships among categorical data using two way tables. 1.1 cont. Hw: pg 24: 20, 21, 23,
Exploring Data Section 1.1 Analyzing Categorical Data.
Unit 3 Relations in Categorical Data. Looking at Categorical Data Grouping values of quantitative data into specific classes We use counts or percents.
CHAPTER 6: Two-Way Tables. Chapter 6 Concepts 2  Two-Way Tables  Row and Column Variables  Marginal Distributions  Conditional Distributions  Simpson’s.
Warm Up The number of motor vehicles registered (in millions) in the U.S. has grown as charted in the table. 1)Plot the number of vehicles against time.
Two-way tables BPS chapter 6 © 2006 W. H. Freeman and Company.
Analysis of two-way tables - Data analysis for two-way tables IPS chapter 2.6 © 2006 W.H. Freeman and Company.
 Some variables are inherently categorical, for example:  Sex  Race  Occupation  Other categorical variables are created by grouping values of a.
Chapter 3: Displaying and Describing Categorical Data Sarah Lovelace and Alison Vicary Period 2.
BPS - 3rd Ed. Chapter 61 Two-Way Tables. BPS - 3rd Ed. Chapter 62 u In this chapter we will study the relationship between two categorical variables (variables.
Stat1510: Statistical Thinking and Concepts Two Way Tables.
Two-Way Tables Categorical Data. Chapter 4 1.  In this chapter we will study the relationship between two categorical variables (variables whose values.
Aim: How do we analyze data with a two-way table?
+ Chapter 1: Exploring Data Section 1.1 Analyzing Categorical Data.
Inference about a population proportion. 1. Paper due March 29 Last day for consultation with me March 22 2.
Chapter 2 Displaying and Describing Categorical Data UNIT OBJECTIVES At the conclusion of this unit you should be able to: n 1)Construct graphs that appropriately.
Warm-up An investigator wants to study the effectiveness of two surgical procedures to correct near-sightedness: Procedure A uses cuts from a scalpel and.
DO NOW: Oatmeal and cholesterol Does eating oatmeal reduce cholesterol
Chapter 6 Two-Way Tables BPS - 5th Ed.Chapter 61.
The TITANIC In 1912 the luxury liner Titanic, on its first voyage across the Atlantic, struck an iceberg and sank. Some passengers got off the ship in.
Categorical Data! Frequency Table –Records the totals (counts or percentage of observations) for each category. If percentages are shown, it is a relative.
BPS - 3rd Ed. Chapter 61 Two-Way Tables. BPS - 3rd Ed. Chapter 62 u In prior chapters we studied the relationship between two quantitative variables with.
AP Statistics Section 4.2 Relationships Between Categorical Variables
4.3 Relations in Categorical Data.  Use categorical data to calculate marginal and conditional proportions  Understand Simpson’s Paradox in context.
+ Chapter 1: Exploring Data Section 1.1 Analyzing Categorical Data The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE.
+ Warm Up Which of these variables are categorical? Which are quantitative?
Categorical Data! Frequency Table –Records the totals (counts or percentage of observations) for each category. If percentages are shown, it is a relative.
Chapter 1.1 – Analyzing Categorical Data A categorical variable places individuals into one of several groups of categories. A quantitative variable takes.
CHAPTER 6: Two-Way Tables*
Copyright ©2011 Brooks/Cole, Cengage Learning Turning Data Into Information Use table and/or graph to represent Categorical Data Chapter 2 – Class 11 1.
+ Chapter 1: Exploring Data Section 1.1 Analyzing Categorical Data The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE.
Objectives Given a contingency table of counts, construct a marginal distribution. Given a contingency table of counts, create a conditional distribution.
+ Analyzing Categorical Data Categorical Variables place individuals into one of several groups or categories The values of a categorical variable are.
Graphical and Numerical Summaries of Qualitative Data
Second factor: education
Jeopardy Vocabulary Formulas Q $100 Q $100 Q $100 Q $100 Q $100 Q $200
Analyzing Categorical Data
Inference about a population proportion.
Analysis of two-way tables - Data analysis for two-way tables
Second factor: education
Day 21 AGENDA: Rev Ch 3 and minutes Begin Ch 4.2.
AP STATISTICS LESSON 4 – 3 ( DAY 1 )
Second factor: education
Relations in Categorical Data
Warmup Which part- time jobs employed 10 or more of the students?
1.1 Analyzing Categorical Data.
Chapter 1: Exploring Data
Section 4-3 Relations in Categorical Data
Displaying and Describing Categorical data
Section Way Tables and Marginal Distributions
Relations in Categorical Data
Chapter 4: More on Two-Variable Data
Presentation transcript:

4.3 Categorical Data Relationships

Analysis Analyze categorical data by looking at the counts or percents of individuals that fall into various categories.

Marginal Distributions Totals that appear at the bottom and right margins of a two – way table.

Seat Belts and Children Do child restraints and seat belts prevent injuries to young passengers in automobile accidents? Here are data on the 26,971 passengers under the age of 15 in accidents reported in North Carolina during two years before the law required restraints. Page 254: 4.69 Restrained Unrestrained Totals Injured 197 3,844 4,041 Uninjured 1,749 21,181 22,930 1,946 25,025 26,971

Marginal Distributions Sometimes the totals may contain roundoff errors. Often percents give more information about the data than the actual counts. What is the percent of injured children who wore a restraint? 197/1946 = 10% What is the percent of uninjured children who wore a restraint? 1749/1946 = 90%

To ensure we get the answer to the question we want, ask … “What group represents the total that we want a percent of?” Calculating the appropriate percents will help describe the relationships being depicted by the data. A graphical display (bar graph) conveys the information plainly for the reader.

Seat Belts and Restraints What is the percent of children who weren’t restrained and injured? 15% What is the percent of children who weren’t restrained and uninjured? 85% Looking at these comparisons it seems like there was only a slight difference between being injured and restrained (10%) versus injured unrestrained (15%)

Conditional Distributions When the distribution refers to a specific people/group who satisfies the condition. To draw a more accurate conclusion from the data, we should look at the table Horizontally. What percentage of children were injured who wore a restraint versus the percentage of children who were injured and not wearing a restraint? Injured and restrained – 4.9% Injured and unrestrained – 95.1% Therefore supporting the need for a state law to require child restraints.

Now for the rest of the story … For those who are not in favor of child restraint laws, they would use the bottom half conditional data. Uninjured and restrained – 7.6% Uninjured and unrestrained – 92.4% Can statistics support whatever we want?

Seat Belt and Children Does the data provide evidence that young passengers are less likely to be injured in an accident if they wear restraints? Calculate and compare percents. Restrained and injured – 10.1% Unrestrained and injured – 15.6%

Finale Seat Belts & Children

Cautions No single graph summarizes the relationship between categorical variables. No single numerical measure summarizes the strength of an association. Visuals (bar graph) are helpful in making comparisons. Percents are more useful if they are well chosen based upon the need of the question being asked.

Simpson’s Paradox Reversal of the direction of a comparison or an association when data from several groups are combined to form a single group.

College Admissions Paradox Page 251: 4.60 Exercises 4.53-4.55, 4.60, 4.67