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The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE

Chapter 1: Exploring Data. Introduction Data Analysis: Making Sense of Data. The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE. Chapter 1 Exploring Data. Introduction : Data Analysis: Making Sense of Data 1.1 Analyzing Categorical Data

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The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE

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  1. Chapter 1: Exploring Data Introduction Data Analysis: Making Sense of Data The Practice of Statistics, 4th edition - For AP* STARNES, YATES, MOORE

  2. Chapter 1Exploring Data • Introduction:Data Analysis: Making Sense of Data • 1.1Analyzing Categorical Data • 1.2Displaying Quantitative Data with Graphs • 1.3Describing Quantitative Data with Numbers

  3. IntroductionData 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”

  4. Data Analysis • Statistics 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.

  5. Data Analysis • A 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 Example Dotplot of MPG Distribution Variable of Interest: MPG

  6. How to Explore Data Data Analysis Examine each variable by itself. Then study relationships among the variables. Start with a graph or graphs Add numerical summaries

  7. Data Analysis From Data Analysis to Inference Population Sample Collect data from a representative Sample... Make an Inference about the Population. Perform Data Analysis, keeping probability in mind…

  8. 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

  9. IntroductionData 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.

  10. 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.

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