Chapter 2: Graphical Summaries of Data 2.1 Graphical Summaries for Qualitative Data. Frequency: Frequency distribution:

Similar documents
Chapter 2 - Graphical Summaries of Data

Section 2-2 Frequency Distributions. Copyright 2010, 2007, 2004 Pearson Education, Inc

Lecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 2.1- #

2.1: Frequency Distributions

TMTH 3360 NOTES ON COMMON GRAPHS AND CHARTS

Overview. Frequency Distributions. Chapter 2 Summarizing & Graphing Data. Descriptive Statistics. Inferential Statistics. Frequency Distribution

2.3 Organizing Quantitative Data

Chapter 3 - Displaying and Summarizing Quantitative Data

This chapter will show how to organize data and then construct appropriate graphs to represent the data in a concise, easy-to-understand form.

+ Statistical Methods in

STP 226 ELEMENTARY STATISTICS NOTES

Organizing and Summarizing Data

Chapter 2 Organizing and Graphing Data. 2.1 Organizing and Graphing Qualitative Data

Prepare a stem-and-leaf graph for the following data. In your final display, you should arrange the leaves for each stem in increasing order.

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1

Chapter 2 - Frequency Distributions and Graphs

Visualizing Data: Freq. Tables, Histograms

Chapter 2 Describing, Exploring, and Comparing Data

Chapter 2. Frequency Distributions and Graphs. Bluman, Chapter 2

Frequency Distributions

Chapter 2 Descriptive Statistics I: Tabular and Graphical Presentations. Learning objectives

Frequency Distributions and Graphs

Lesson 18-1 Lesson Lesson 18-1 Lesson Lesson 18-2 Lesson 18-2

Chapter 2: Descriptive Statistics

2.1: Frequency Distributions and Their Graphs

Graphical Presentation for Statistical Data (Relevant to AAT Examination Paper 4: Business Economics and Financial Mathematics) Introduction

B. Graphing Representation of Data

Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation

Test Bank for Privitera, Statistics for the Behavioral Sciences

MATH1635, Statistics (2)

MATH 117 Statistical Methods for Management I Chapter Two

Section 1.2. Displaying Quantitative Data with Graphs. Mrs. Daniel AP Stats 8/22/2013. Dotplots. How to Make a Dotplot. Mrs. Daniel AP Statistics

2.4-Statistical Graphs

1.2. Pictorial and Tabular Methods in Descriptive Statistics

Chapters 1.5 and 2.5 Statistics: Collecting and Displaying Data

Chapter 2 Descriptive Statistics. Tabular and Graphical Presentations

Slides Prepared by JOHN S. LOUCKS St. Edward s s University Thomson/South-Western. Slide

Courtesy :

Chapter 2. Descriptive Statistics: Organizing, Displaying and Summarizing Data

Chapter 2. Frequency distribution. Summarizing and Graphing Data

Round each observation to the nearest tenth of a cent and draw a stem and leaf plot.

Raw Data. Statistics 1/8/2016. Relative Frequency Distribution. Frequency Distributions for Qualitative Data

Sections Graphical Displays and Measures of Center. Brian Habing Department of Statistics University of South Carolina.

1.3 Graphical Summaries of Data

Chapter 1. Looking at Data-Distribution

2.1 Objectives. Math Chapter 2. Chapter 2. Variable. Categorical Variable EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES

2. The histogram. class limits class boundaries frequency cumulative frequency

The basic arrangement of numeric data is called an ARRAY. Array is the derived data from fundamental data Example :- To store marks of 50 student

- 1 - Class Intervals

Math Tech IIII, Sep 14

AND NUMERICAL SUMMARIES. Chapter 2

Chapter 6: DESCRIPTIVE STATISTICS

Elementary Statistics

Chapter 2: Understanding Data Distributions with Tables and Graphs

Prob and Stats, Sep 4

Making Science Graphs and Interpreting Data

Raw Data is data before it has been arranged in a useful manner or analyzed using statistical techniques.

Displaying Distributions - Quantitative Variables

28 CHAPTER 2 Summarizing and Graphing Data

Lesson 1. Unit 2 Practice Problems. Problem 2. Problem 1. Solution 1, 4, 5. Solution. Problem 3

Vocabulary. 5-number summary Rule. Area principle. Bar chart. Boxplot. Categorical data condition. Categorical variable.

Table of Contents (As covered from textbook)

a. divided by the. 1) Always round!! a) Even if class width comes out to a, go up one.

Slides by. John Loucks. St. Edward s University. Slide South-Western, a part of Cengage Learning

Data can be in the form of numbers, words, measurements, observations or even just descriptions of things.

CHAPTER 2. Objectives. Frequency Distributions and Graphs. Basic Vocabulary. Introduction. Organise data using frequency distributions.

BUSINESS DECISION MAKING. Topic 1 Introduction to Statistical Thinking and Business Decision Making Process; Data Collection and Presentation

The variable: scores on a 60 question exam for 20 students 50, 46, 58, 49, 50, 57, 49, 48, 53, 45, 50, 55, 43, 49, 46, 48, 44, 56, 57, 44

No. of blue jelly beans No. of bags

Name Date Types of Graphs and Creating Graphs Notes

Applied Statistics for the Behavioral Sciences

download instant at Summarizing Data: Listing and Grouping

Spell out your full name (first, middle and last)

CHAPTER 2: SAMPLING AND DATA

Chapter 2: Frequency Distributions

STAT STATISTICAL METHODS. Statistics: The science of using data to make decisions and draw conclusions

Chapter 2: Descriptive Statistics (Part 1)

Parents Names Mom Cell/Work # Dad Cell/Work # Parent List the Math Courses you have taken and the grade you received 1 st 2 nd 3 rd 4th

8 Organizing and Displaying

CHAPTER 1. Introduction. Statistics: Statistics is the science of collecting, organizing, analyzing, presenting and interpreting data.

Name: Date: Period: Chapter 2. Section 1: Describing Location in a Distribution

Slide Copyright 2005 Pearson Education, Inc. SEVENTH EDITION and EXPANDED SEVENTH EDITION. Chapter 13. Statistics Sampling Techniques

CHAPTER 3: Data Description

NOTES TO CONSIDER BEFORE ATTEMPTING EX 1A TYPES OF DATA

UNIT 15 GRAPHICAL PRESENTATION OF DATA-I

Statistical Tables and Graphs

UNIT 1A EXPLORING UNIVARIATE DATA

12. A(n) is the number of times an item or number occurs in a data set.

MATH& 146 Lesson 10. Section 1.6 Graphing Numerical Data

Bar Graphs and Dot Plots

Statistical Methods. Instructor: Lingsong Zhang. Any questions, ask me during the office hour, or me, I will answer promptly.

At the end of the chapter, you will learn to: Present data in textual form. Construct different types of table and graphs

Section 2-2. Histograms, frequency polygons and ogives. Friday, January 25, 13

Course Guide (/8/teachers/teacher_course_guide.html) Print (/8/teachers/print_materials.html) LMS (/8

Select Cases. Select Cases GRAPHS. The Select Cases command excludes from further. selection criteria. Select Use filter variables

3. Data Analysis and Statistics

Measures of Central Tendency

Using a percent or a letter grade allows us a very easy way to analyze our performance. Not a big deal, just something we do regularly.

Chapter 5snow year.notebook March 15, 2018

SCHEME OF WORK YR 8 THETA 2 UNIT / LESSON

Transcription:

Chapter 2: Graphical Summaries of Data 2.1 Graphical Summaries for Qualitative Data Frequency: Frequency distribution: Example 2.1 The following are survey results from Fall 2014 Statistics class regarding eye color. Construct a frequency distribution. Blue Brown Brown Brown Blue Blue Brown Hazel Hazel Brown Blue Brown Blue Hazel Brown Brown Brown Blue Hazel Blue Brown Hazel Brown Brown Blue Hazel Brown Blue Blue Brown Hazel Hazel Blue Brown brown Relative frequency: Relative frequency distribution:

Relative Frequency = Example Construct a relative frequency distribution for the eye color data. Eye Color Brown Blue Hazel Frequency Bar graph: Example Construct a frequency bar graph and the relative frequency bar graph for the eye color data. Eye Color Frequency Relative Frequency Brown Blue Hazel

Pareto Charts: Pie Charts: Example Construct a pie chart for the eye color data. Eye Color Brown Blue Hazel Relative Frequency

Do You Know How to construct a frequency and relative frequency distribution for qualitative data? How to construct the various kinds of bar graphs? 2.2 Frequency Distributions and Their Graphs To summarize quantitative data, we use a frequency distribution just like those for qualitative data. Frequency distributions have the following: Classes: Lower class limit: Upper class limit: Class width:

Here s a random example: Choosing Classes Constructing a Frequency Distribution Step 1: Step 2: Step 3: Step 4: Step 5:

Note: If you are not told the class width, you can figure it out yourself by doing (largest data value - smallest data value) divided by the number of classes. Round this (always up) to a convenient number. You will always either be given the class width or the number of classes. Example Following are the number of years lived by selected US presidents after their first inauguration. Construct a frequency distribution starting with a lower class limit of 0 and a class width of 5. 10, 29, 26, 28, 15, 23, 17, 25, 0, 4, 1, 16, 12, 4, 17, 16, 0, 24, 12, 4, 18, 21, 11, 2, 9, 36, 12, 28, 16, 3, 9, 25, 23 Given a frequency distribution, a relative frequency distribution can be constructed by computing the relative frequency for each class. Now create a relative frequency of the previous data. (in your notes, put it above here). Recall: Relative Frequency = Histograms Once we have a frequency distribution or a relative frequency distribution, we can put the information in graphical form by constructing a Histogram:

Example Construct a frequency histogram and relative frequency histogram for the president data. Choosing the Number of Classes There are no hard and fast rules for choosing the number of classes. There are two principles that can guide the choice: Note: there are ways to do a histogram on the calculator, but honestly, it is quicker and easier (in my opinion) to just do it by hand, assuming you have already created a frequency distribution. Shape of a Distribution from the Histogram Symmetric: Skewed right (positively skewed): Skewed left (negatively skewed):

Example: which histogram below is symmetric, skewed right, skewed left? Mode: Unimodal: Bimodal: Class Midpoints: Class Midpoint = Example: Find all class midpoints for presidential data. Frequency polygon:

Example Construct a frequency polygon for the presidential data. Relative frequency polygon: Ogives: Example Construct an ogive for the presidential data.

Do You Know How to construct frequency and relative frequency distributions for quantitative data? How to construct frequency and relative frequency histograms How to determine the shape of a distribution from a histogram? How to construct frequency and relative frequency polygons? How to construct an ogive? 2.3 More Graphs for Quantitative Data Stem-and-Leaf Plots Stem-and-leaf plots and dotplots illustrate the shape of the data set, while allowing every value in the data set to be seen. In a stem-and-leaf plot, the rightmost digit is the leaf, and the remaining digits form the stem. Consider the values 14.8 and 2,739: Procedure to Construct a Stem-and-Leaf Plot Step 1: Step 2: Step 3: Example The following are quiz scores from a Calculus quiz I once gave. Create a stem and leaf plot. 10, 12, 16, 25, 19, 21, 22, 27, 29, 25, 29, 17, 5, 12, 13, 29, 23, 12, 15, 7, 8, 23, 25, 27, 12, 17, 18, 12, 19, 18, 23

Sometimes you can split the stem and have two or more lines for each stem. Do this with above quiz score data. Dotplots: Example Dotplot Construct a dotplot of the Calculus quiz data. Do You Know How to construct various types of stem-and-leaf plots? How to construct dotplots?

2.4 Misleading Graphs Introduction Statistical graphs, when properly used, are powerful forms of communication. Unfortunately, when graphs are improperly used, they can misrepresent the data, and lead people to draw incorrect conclusions. Misrepresentation There are three common forms of misrepresentation. They are Incorrect Position of the Vertical Scale The baseline of a chart or plot is the value at which the horizontal axis intersects with the vertical axis. With charts or plots that represent how much or how many of something,. The Area Principle (I stole the rest of this section straight from the book sorry!) When amounts are compared by constructing an image for each amount, the areas of the images must be proportional to the amounts. For example, if one amount is twice as much as another, its image should have twice as much area as the other image. When the Area Principle is violated, the images give a misleading impression of the data. Example The Area Principle Consider a comparison of the cost of jet fuel in 2000 and 2008.

Note that the price in 2008 is about 3.5 times the price in 2000. In a bar chart, the area of the bar for 2008 is also about 3.5 times that of the area of the bar for 2000. This bar chart follows the Area Principle. A common mistake is to vary both dimensions (height and width) of the image. Following is a comparison of the cost of jet fuel that uses a picture of an airplane. The pictures of the planes make the difference appear much larger than the correctly drawn bar chart does. Three-dimensional Graphs Newspapers and magazines often present three-dimensional bar charts because they are visually impressive. Unfortunately, in order to make the tops of the bars visible, these charts are often drawn as though the reader is looking down on them. This makes the bars look shorter than they really are. (Note: I think this is sort of ridiculous. Just me) The following figures present the same cost of jet fuel data. However, in the three-dimensional bar chart, the bars appear shorter than they really are.

Do You Know The three most common forms of misrepresentation?