Variables. Lecture 13 Sections Wed, Sep 16, Hampden-Sydney College. Displaying Distributions - Quantitative.

Similar documents
Outline. Drawing the Graph. 1 Homework Review. 2 Introduction. 3 Histograms. 4 Histograms on the TI Assignment

Displaying Distributions with Graphs

Chapter 4. September 08, appstats 4B.notebook. Displaying Quantitative Data. Aug 4 9:13 AM. Aug 4 9:13 AM. Aug 27 10:16 PM.

Section 1: Data (Major Concept Review)

Chapter 4 Displaying and Describing Quantitative Data

Sections Descriptive Statistics for Numerical Variables

Chapter 10. Definition: Categorical Variables. Graphs, Good and Bad. Distribution

Lecture 16 Sections Tue, Sep 23, 2008

Chapter 4. Displaying and Summarizing Quantitative Data. Copyright 2012, 2008, 2005 Pearson Education, Inc.

Chapter 1. Statistics. Individuals and Variables. Basic Practice of Statistics - 3rd Edition. Chapter 1 1. Picturing Distributions with Graphs

Chapter 1: Stats Starts Here Chapter 2: Data

Section 1.5 Graphs and Describing Distributions

Chpt 2. Frequency Distributions and Graphs. 2-3 Histograms, Frequency Polygons, Ogives / 35

Chapter 3. Graphical Methods for Describing Data. Copyright 2005 Brooks/Cole, a division of Thomson Learning, Inc.

Notes: Displaying Quantitative Data

Lecture 16 Sections Tue, Feb 10, 2009

Chapter 1. Picturing Distributions with Graphs

Describing Data Visually. Describing Data Visually. Describing Data Visually 9/28/12. Applied Statistics in Business & Economics, 4 th edition

Chapter Displaying Graphical Data. Frequency Distribution Example. Graphical Methods for Describing Data. Vision Correction Frequency Relative

Name: Date: Period: Histogram Worksheet

What Is a Histogram? A bar graph that shows the distribution of data A snapshot of data taken from a process HISTOGRAM VIEWGRAPH 1

11 Wyner Statistics Fall 2018

DESCRIBING DATA. Frequency Tables, Frequency Distributions, and Graphic Presentation

AP Statistics Composition Book Review Chapters 1 2

LESSON 2: FREQUENCY DISTRIBUTION

i. Are the shapes of the two distributions fundamentally alike or fundamentally different?

Probability WS 1 Counting , , , a)625 b)1050c) a)20358,520 b) 1716 c) 55,770

1.1 Displaying Distributions with Graphs, Continued

STK110. Chapter 2: Tabular and Graphical Methods Lecture 1 of 2. ritakeller.com. mathspig.wordpress.com

Numerical: Data with quantity Discrete: whole number answers Example: How many siblings do you have?

Organizing Data 10/11/2011. Focus Points. Frequency Distributions, Histograms, and Related Topics. Section 2.1

Review. In an experiment, there is one variable that is of primary interest. There are several other factors, which may affect the measured result.

Learning Objectives. Describing Data: Displaying and Exploring Data. Dot Plot. Dot Plot 12/9/2015

Describing Data: Displaying and Exploring Data. Chapter 4

Business Statistics. Lecture 2: Descriptive Statistical Graphs and Plots

Lecture 5 Understanding and Comparing Distributions

Chapter 2 Frequency Distributions and Graphs

Counting and Probability

You must have: Pen, HB pencil, eraser, calculator, ruler, protractor.

SAMPLE. This chapter deals with the construction and interpretation of box plots. At the end of this chapter you should be able to:

Interval of Head Circumferences (mm) XS 510 < 530 S 530 < 550 M 550 < 570 L 570 < 590 XL 590 < 610 XXL 610 < 630. Hat Sizes.

Name Class Date. Introducing Probability Distributions

A C E. Answers Investigation 3. Applications. Sample 2: 11 moves. or 0.44; MAD Sample 2: 22. , or 2.44; MAD Sample 3: 0, or 0.

Frequency Distribution and Graphs

CCMR Educational Programs

Left skewed because it is stretched to the left side. Lesson 5: Box Plots. Lesson 5

Descriptive Statistics II. Graphical summary of the distribution of a numerical variable. Boxplot

A Visual Display. A graph is a visual display of information or data. This is a graph that shows a girl walking her dog. Communicating with Graphs

Algebra 2 P49 Pre 10 1 Measures of Central Tendency Box and Whisker Plots Variation and Outliers

PSY 307 Statistics for the Behavioral Sciences. Chapter 2 Describing Data with Tables and Graphs

Data About Us Practice Answers

SPIRIT 2.0 Lesson: How Far Am I Traveling?

Digital Logic Circuits

Mathematics Success Level C

Why Should We Care? More importantly, it is easy to lie or deceive people with bad plots

TJP TOP TIPS FOR IGCSE STATS & PROBABILITY

Why Should We Care? Everyone uses plotting But most people ignore or are unaware of simple principles Default plotting tools are not always the best

Data Analysis and Probability

10 Wyner Statistics Fall 2013

CHAPTER 13A. Normal Distributions

Data Presentation. Esra Akdeniz. February 12th, 2016

CC.2.1.HSF2a: Convert between fractions and decimals in a real-world problem

UNCORRECTED PAGE PROOFS

The Coin Toss Experiment

Background knowledge in statistics

Frequency Tables, Stem-and-Leaf Plots, and Line Plots

Please Turn Over Page 1 of 7

Chapter 2. The Excel functions, Excel Analysis ToolPak Add-ins or Excel PHStat2 Add-ins needed to create frequency distributions are:

Going back to the definition of Biostatistics. Organizing and Presenting Data. Learning Objectives. Nominal Data 10/10/2016. Tabulation and Graphs

NUMERICAL DATA and OUTLIERS

Possible responses to the 2015 AP Statistics Free Resposne questions, Draft #2. You can access the questions here at AP Central.

Problem Solving with the Coordinate Plane

First Practice Test 1 Levels 5-7 Calculator not allowed

Algebra I Notes Unit One: Real Number System

3. A box contains three blue cards and four white cards. Two cards are drawn one at a time.

Symmetric (Mean and Standard Deviation)

IE 361 Module 17. Process Capability Analysis: Part 1. Reading: Sections 5.1, 5.2 Statistical Quality Assurance Methods for Engineers

University of Tennessee at. Chattanooga

Section 3.5 Graphing Techniques: Transformations

Regression: Tree Rings and Measuring Things

Introduction. Descriptive Statistics. Problem Solving. Inferential Statistics. Chapter1 Slides. Maurice Geraghty

What is the expected number of rolls to get a Yahtzee?

HPS Scope Sequence Last Revised June SUBJECT: Math GRADE: 7. Michigan Standard (GLCE) Code & Language. What this Standard means:

To describe the centre and spread of a univariate data set by way of a 5-figure summary and visually by a box & whisker plot.

Chapter 2. Organizing Data. Slide 2-2. Copyright 2012, 2008, 2005 Pearson Education, Inc.

Important Considerations For Graphical Representations Of Data

Problem Solving with Length, Money, and Data

Elementary Statistics. Graphing Data

Scatter Plots, Correlation, and Lines of Best Fit

Stat 20: Intro to Probability and Statistics

Determine if the function is even, odd, or neither. 1) f(x) = 8x4 + 7x + 5 A) Even B) Odd C) Neither

LabVIEW Day 2: Other loops, Other graphs

Incoming Advanced Grade 7

Controlling Bias; Types of Variables

Session 5 Variation About the Mean

Elko County School District 5 th Grade Math Learning Targets

Univariate Descriptive Statistics

Engineering Fundamentals and Problem Solving, 6e

Cumulative Test (Multiple Choice)

MAT Mathematics in Today's World

Transcription:

- - Lecture 13 Sections 4.4.1-4.4.3 Hampden-Sydney College Wed, Sep 16, 2009

Outline - 1 2 3 4 5 6 7 Even-numbered

- Exercise 4.7, p. 226. According to the National Center for Health Statistics, in the year 1940, the percentage of people age 65 who were expected to survive to the age of 90 was 7%. For the year 1960, that percentage was 14%. For the year 1980, that percentage was 25%. Based on projections, the percentages for the years 2000 and 2050 are 26% and 42%, respective. Present a bar graph to display the percentage of people age 65 who are expected to live to the age of 90 for the years 1940, 1960, 1980, and projections for the years 2000 and 2050.

- Solution The bar graph. Percentage 50% 40% 30% 20% 10% 1940 1960 1980 2000 2050 Year

- Solution As a time-series plot. Percentage 50% 40% 30% 20% 10% 1940 1960 1980 2000 2050 Year

- Solution An improved time-series plot. Percentage 50% 40% 30% 20% 10% 1940 1960 1980 2000 2050 Year

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- Now we wish to create displays of quantitative data. With quantitative data, what is it that we wish to convey through our display? Some possibilities: Are the data clustered around the middle? Or are they spread out? Where is the middle? Are they any outliers? What are the extremes? Are the values shifted to the left or right?

- To obtain such information, we need a graph that plots the value of the variable on one axis and its frequency on the other axis.

Example - The following data represent rainfall amounts at the Richmond airport in September for the years 1979-2008 (30 years). 5.94 1.11 9.52 0.08 6.14 8.68 2.93 2.03 3.60 14.71 4.01 0.85 6.89 11.07 4.42 3.41 2.85 2.56 1.92 5.15 1.58 4.44 0.77 4.76 1.15 3.02 1.73 2.60 2.56 10.01 How might we display these data graphically?

- Definition ( plot) A frequency plot is a display of quantitative data in which each data point is represented by an X over that value on a horizontal scale.

Drawing - Draw a horizontal line. Choose a resolution, e.g., 0.1. Keeping in mind the minimum and maximum values, mark reference points on the scale, as on a ruler. Mark at regular intervals. For each data value, draw an X over that value on the scale.

Example - Make a frequency plot of the rainfall data. 5.94 1.11 9.52 0.08 6.14 8.68 2.93 2.03 3.60 14.71 4.01 0.85 6.89 11.07 4.42 3.41 2.85 2.56 1.92 5.15 1.58 4.44 0.77 4.76 1.15 3.02 1.73 2.60 2.56 10.01

- 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 What information is conveyed by this frequency plot?

- Definition (Symmetric) The distribution is symmetric if the left side is a mirror image of the right side. Definition (Unimodal) The distribution is unimodal if it has a single peak, showing the most common values. Definition (Bimodal) The distribution is bimodal if it has two peaks.

- Definition (Uniform) The distribution is uniform if all values have equal frequency. Definition (Skewed) The distribution is skewed if it is stretched out more on one side than the other.

- 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 What properties does this distribution have?

- 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 What properties does this distribution have?

- Definition (leaf display) A stem-and-leaf display is a display of quantitative data in which the numerical representation of each data value is split into a stem and a leaf. The stem is the part to the left of the division point. The leaf is the first digit to the right of the division point.

- For example, the value 1.23 could be split as 1 23 stem = 1, leaf = 2, or 12 3 stem = 12, leaf = 3. Indeed, it could even be split as 123 stem = 0, leaf = 1, or 123 stem = 123, leaf = 0.

- The stem consists of the digits to the left of the division point. The leaf consists of the first digit to the right of the division point. A note should be added indicating how to interpret the numbers. Note: 12 3 means 1.23.

Example - Draw a stem-and-leaf display of the rainfall data. 5.94 1.11 9.52 0.08 6.14 8.68 2.93 2.03 3.60 14.71 4.01 0.85 6.89 11.07 4.42 3.41 2.85 2.56 1.92 5.15 1.58 4.44 0.77 4.76 1.15 3.02 1.73 2.60 2.56 10.01

Splitting the Numbers - We choose where to split the numbers in order to avoid Too many stems, each with too few leaves. Too few stems, each with too many leaves.

Splitting the Numbers - We choose where to split the numbers in order to avoid Too many stems, each with too few leaves. Too few stems, each with too many leaves

Example - Draw a stem-and-leaf display of the rainfall data, in centimeters. 15.09 2.82 24.18 0.20 15.60 22.04 7.44 5.16 9.14 37.36 10.19 2.16 17.50 28.12 11.23 8.66 7.24 6.50 4.88 13.08 4.01 11.28 1.96 12.09 2.92 7.67 4.39 6.60 6.50 25.43

Example - We may split the values after the 10 s digit: Stem Note: 1 2 means 12. 0 2 0 7 5 9 2 8 7 6 4 4 1 2 7 4 6 6 1 5 5 0 7 1 3 1 2 2 4 2 8 5 3 7

Example - Or we may split the values at the decimal point: Stem Note: 12 3 means 12.3. 0 2 1 9 2 8 1 9 3 4 8 0 3 5 1 6 5 6 5 7 4 2 6.. 37 3

Example - Which is better? Is either one particularly good?

- We can obtain a good compromise (in this example) by splitting the stems. Each stems appears twice. The first time for leaves 0-4. The second time for leaves 5-9.

- Display with split stems: Stem Note: 1 2 means 12. 0 2 0 2 4 4 1 2 4 0 7 5 9 8 7 6 7 6 6 1 0 1 3 1 2 1 5 5 7 2 4 2 2 8 5 3 3 7

- Read Section 4.4.1-4.4.3, pages 238-241, 242-248. Let s Do It! 4.10, 4.12. Page 241, exercise 18. Page 248, exercises 22-27, 29.

Even-numbered - Page 241, Exercise 18 4.18 (a) 2 4 6 8 10 12 (b) The distribution is symmetric and unimodal. The middle is near 7. There do not appear to be any outliers.

Even-numbered - Page 248, 22, 24, 26 4.22 Symmetric, unimodal:] Characteristic No. of heads out of 12 tosses of a fair coin. Characteristic Amount of money a family spends on college Characteristic Housing prices Characteristic No. of years a person lives Characteristic Length of time sitting at a particular red light 4.24 (a) Stem -1 0 0 1 2 9 4 8 3 9 3 1 5 6 4 8 4 8 7 5 4 5 3 5 9 7 7 0 3 0 4 0 8 4 1 9 9 7 3 5 7 0 6 9 5 1 0 4 8 2 0 0 5 4 7 6 1 0

Even-numbered - Page 248, 22, 24, 26 4.24 (b) Unimodal, symmetric with one outlier. (c) Connecticut. (d) 93-94 Stem 96-97 -1 0-1 0 0 1 1 4 2 4 8 7 2 9 8 1 3 3 1 4 6 8 7 9 3 9 5 6 8 3 0 2 3 1 3 1 4 4 4 3 0 3 0 4 0 4 1 3 0 9 7 9 7 6 8 9 9 7 5 4 8 7 5 5 5 9 7 7 8 9 9 7 5 7 6 9 1 4 4 3 4 2 0 1 1 5 1 0 4 2 0 0 4 6 7 9 6 5 8 5 7 1 4 3 3 1 6 1 0 6 4 0 7 7 8 6 5 8 9 5 9 10 9 10 They are both unimodal and symmetric, and with similar middles. 93-94 has more large outliers; 96-97 has more small outliers.

Even-numbered - Page 248, 22, 24, 26 4.26 (a) Calories (my choice). Stem 7 5 8 2 4 3 9 10 9 11 7 9 12 7 6 (b) 13 2 14 15 5 7 16 17 18 19 6 Hard to say, because there is not much data. I would probably say it is uniform because I see no clear shape. Maybe it is skewed right. (c) Best: Orange Roughy; worst: Salmon.

Even-numbered - Page 248, 22, 24, 26 4.26 (d) Fat: Stem 0 9 8 5 1 7 5 3 2 5 3 8 4 4 2 5 3 6 9 7 8 9 10 11 4 Unimodal and skewed right. (e) No. Yes.