1 / 10

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

atanya
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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.

More Related