Special Review Section. Copyright 2014 Pearson Education, Inc.

Size: px
Start display at page:

Download "Special Review Section. Copyright 2014 Pearson Education, Inc."

Transcription

1 Special Review Section SRS-1--1

2 Special Review Section Chapter 1: The Where, Why, and How of Data Collection Chapter 2: Graphs, Charts, and Tables Describing Your Data Chapter 3: Describing Data Using Numerical Measures SRS-1--2

3 Transforming Data to Information Data Statistical Tools Information SRS-1--3

4 A Typical Application Sequence Determine a Need for Data Decide on Statistical or Nonstatistical Sampling Define the Population Determine What Data You Will Need Decide How the Data Will Be Collected Determine Data Types and Measurement Level Select Graphic Presentation Tools Compute Numerical Measures Decide on a Census or a Sample Write the Statistical Report SRS-1--4

5 A Typical Application Sequence Determine a Need for Data: Research the issue Analyze business alternatives Respond to request for information Define the Population: All items of interest Determine how to gain access to the population SRS-1--5

6 A Typical Application Sequence Determine What Data You Will Need: Identify the key variables What categorical breakdowns will be needed? Decide How the Data Will Be Collected: Experiment Observation Automation Telephone Survey Written Survey Personal Interview SRS-1--6

7 A Typical Application Sequence Decide on a Census or a Sample: Census: All items in the population Sample: A subset of the population Decide on Statistical or Nonstatistical Sampling: Statistical Sampling: Simple Random Sample Stratied Random Sample Systematic Random Sample Cluster Random Sample Nonstatistical Sampling: Convenience Sampling Judgment Sampling SRS-1--7

8 Data Types and Measurement Level Types of Data Data Timing Quantitative Qualitative Cross- Sectional Time-Series Data Level Nominal Ordinal Interval/Ratio SRS-1--8

9 Graphic Presentation Tools Discrete or Continuous Interval/Ratio Grouped or Ungrouped Data Timing Cross- Sectional Frequency Relative Frequency Cumulative Relative Frequency Joint Frequency Quantitative Timeseries Line Chart Bar Chart (Vertical) Histogram Stem and Leaf Diagram Data Type Scatter Diagram Ogive Box and Whicker Plot Qualitative Frequency Relative Frequency Joint Frequency Categorical/ Nominal/ Ordinal Bar Chart (Vertical or Horizontal) Line Chart SRS-1--9

10 Computing Numerical Measures Mode Ordinal Data Level Nominal Mode Median Ratio/Interval Range Interquartile Range Variation Type of Measures Central Location Median Mean Variance and Standard Deviation Percentiles/ Quartiles Descriptive Analysis & Location Coefficient of Variation Mode Percentiles/ Quartiles Box and Whisker SRS-1--10

11 Writing the Statistical Report Lay the foundation: Provide background and motivation for the analysis Describe the data collection methodology: Explain how the data were gathered and the sampling techniques were used Use a logical sequence: Follow a systematic plan for presenting your findings and analysis Label figures and tables by number: Employ a consistent numbering and labeling format SRS-1--11

12 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. SRS-1--12

2.1: Frequency Distributions and Their Graphs

2.1: Frequency Distributions and Their Graphs 2.1: Frequency Distributions and Their Graphs Frequency Distribution - way to display data that has many entries - table that shows classes or intervals of data entries and the number of entries in each

More information

Data Statistics Population. Census Sample Correlation... Statistical & Practical Significance. Qualitative Data Discrete Data Continuous Data

Data Statistics Population. Census Sample Correlation... Statistical & Practical Significance. Qualitative Data Discrete Data Continuous Data Data Statistics Population Census Sample Correlation... Voluntary Response Sample Statistical & Practical Significance Quantitative Data Qualitative Data Discrete Data Continuous Data Fewer vs Less Ratio

More information

Data Handling. Moving from A to A* Calculate the numbers to be surveyed for a stratified sample (A)

Data Handling. Moving from A to A* Calculate the numbers to be surveyed for a stratified sample (A) Moving from A to A* A* median, quartiles and interquartile range from a histogram (A*) Draw histograms from frequency tables with unequal class intervals (A) Calculate the numbers to be surveyed for a

More information

Chapter 1. Looking at Data-Distribution

Chapter 1. Looking at Data-Distribution Chapter 1. Looking at Data-Distribution Statistics is the scientific discipline that provides methods to draw right conclusions: 1)Collecting the data 2)Describing the data 3)Drawing the conclusions Raw

More information

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

Data can be in the form of numbers, words, measurements, observations or even just descriptions of things. + What is Data? Data is a collection of facts. Data can be in the form of numbers, words, measurements, observations or even just descriptions of things. In most cases, data needs to be interpreted and

More information

8 Organizing and Displaying

8 Organizing and Displaying CHAPTER 8 Organizing and Displaying Data for Comparison Chapter Outline 8.1 BASIC GRAPH TYPES 8.2 DOUBLE LINE GRAPHS 8.3 TWO-SIDED STEM-AND-LEAF PLOTS 8.4 DOUBLE BAR GRAPHS 8.5 DOUBLE BOX-AND-WHISKER PLOTS

More information

Chapter 2 Describing, Exploring, and Comparing Data

Chapter 2 Describing, Exploring, and Comparing Data Slide 1 Chapter 2 Describing, Exploring, and Comparing Data Slide 2 2-1 Overview 2-2 Frequency Distributions 2-3 Visualizing Data 2-4 Measures of Center 2-5 Measures of Variation 2-6 Measures of Relative

More information

Name Date Types of Graphs and Creating Graphs Notes

Name Date Types of Graphs and Creating Graphs Notes Name Date Types of Graphs and Creating Graphs Notes Graphs are helpful visual representations of data. Different graphs display data in different ways. Some graphs show individual data, but many do not.

More information

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

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 Organizing data Learning Outcome 1. make an array 2. divide the array into class intervals 3. describe the characteristics of a table 4. construct a frequency distribution table 5. constructing a composite

More information

Test Bank for Privitera, Statistics for the Behavioral Sciences

Test Bank for Privitera, Statistics for the Behavioral Sciences 1. A simple frequency distribution A) can be used to summarize grouped data B) can be used to summarize ungrouped data C) summarizes the frequency of scores in a given category or range 2. To determine

More information

LESSON 3: CENTRAL TENDENCY

LESSON 3: CENTRAL TENDENCY LESSON 3: CENTRAL TENDENCY Outline Arithmetic mean, median and mode Ungrouped data Grouped data Percentiles, fractiles, and quartiles Ungrouped data Grouped data 1 MEAN Mean is defined as follows: Sum

More information

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

12. A(n) is the number of times an item or number occurs in a data set. Chapter 15 Vocabulary Practice Match each definition to its corresponding term. a. data b. statistical question c. population d. sample e. data analysis f. parameter g. statistic h. survey i. experiment

More information

Unit 7 Statistics. AFM Mrs. Valentine. 7.1 Samples and Surveys

Unit 7 Statistics. AFM Mrs. Valentine. 7.1 Samples and Surveys Unit 7 Statistics AFM Mrs. Valentine 7.1 Samples and Surveys v Obj.: I will understand the different methods of sampling and studying data. I will be able to determine the type used in an example, and

More information

Courtesy :

Courtesy : STATISTICS The Nature of Statistics Introduction Statistics is the science of data Statistics is the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data.

More information

MATH 117 Statistical Methods for Management I Chapter Two

MATH 117 Statistical Methods for Management I Chapter Two Jubail University College MATH 117 Statistical Methods for Management I Chapter Two There are a wide variety of ways to summarize, organize, and present data: I. Tables 1. Distribution Table (Categorical

More information

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

a. divided by the. 1) Always round!! a) Even if class width comes out to a, go up one. Probability and Statistics Chapter 2 Notes I Section 2-1 A Steps to Constructing Frequency Distributions 1 Determine number of (may be given to you) a Should be between and classes 2 Find the Range a The

More information

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

BUSINESS DECISION MAKING. Topic 1 Introduction to Statistical Thinking and Business Decision Making Process; Data Collection and Presentation BUSINESS DECISION MAKING Topic 1 Introduction to Statistical Thinking and Business Decision Making Process; Data Collection and Presentation (Chap 1 The Nature of Probability and Statistics) (Chap 2 Frequency

More information

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

Lesson 18-1 Lesson Lesson 18-1 Lesson Lesson 18-2 Lesson 18-2 Topic 18 Set A Words survey data Topic 18 Set A Words Lesson 18-1 Lesson 18-1 sample line plot Lesson 18-1 Lesson 18-1 frequency table bar graph Lesson 18-2 Lesson 18-2 Instead of making 2-sided copies

More information

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

Spell out your full name (first, middle and last) Spell out your full name (first, middle and last) Be ready to share the following counts: Number of letters in your full name. Number of vowels Number of consonants Section 2-1 Organizing Data After completing

More information

STA 570 Spring Lecture 5 Tuesday, Feb 1

STA 570 Spring Lecture 5 Tuesday, Feb 1 STA 570 Spring 2011 Lecture 5 Tuesday, Feb 1 Descriptive Statistics Summarizing Univariate Data o Standard Deviation, Empirical Rule, IQR o Boxplots Summarizing Bivariate Data o Contingency Tables o Row

More information

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

Overview. Frequency Distributions. Chapter 2 Summarizing & Graphing Data. Descriptive Statistics. Inferential Statistics. Frequency Distribution Chapter 2 Summarizing & Graphing Data Slide 1 Overview Descriptive Statistics Slide 2 A) Overview B) Frequency Distributions C) Visualizing Data summarize or describe the important characteristics of a

More information

M7D1.a: Formulate questions and collect data from a census of at least 30 objects and from samples of varying sizes.

M7D1.a: Formulate questions and collect data from a census of at least 30 objects and from samples of varying sizes. M7D1.a: Formulate questions and collect data from a census of at least 30 objects and from samples of varying sizes. Population: Census: Biased: Sample: The entire group of objects or individuals considered

More information

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

Vocabulary. 5-number summary Rule. Area principle. Bar chart. Boxplot. Categorical data condition. Categorical variable. 5-number summary 68-95-99.7 Rule Area principle Bar chart Bimodal Boxplot Case Categorical data Categorical variable Center Changing center and spread Conditional distribution Context Contingency table

More information

Chapter 2: Descriptive Statistics

Chapter 2: Descriptive Statistics Chapter 2: Descriptive Statistics Student Learning Outcomes By the end of this chapter, you should be able to: Display data graphically and interpret graphs: stemplots, histograms and boxplots. Recognize,

More information

Chapter 3 - Displaying and Summarizing Quantitative Data

Chapter 3 - Displaying and Summarizing Quantitative Data Chapter 3 - Displaying and Summarizing Quantitative Data 3.1 Graphs for Quantitative Data (LABEL GRAPHS) August 25, 2014 Histogram (p. 44) - Graph that uses bars to represent different frequencies or relative

More information

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

Section 2-2 Frequency Distributions. Copyright 2010, 2007, 2004 Pearson Education, Inc Section 2-2 Frequency Distributions Copyright 2010, 2007, 2004 Pearson Education, Inc. 2.1-1 Frequency Distribution Frequency Distribution (or Frequency Table) It shows how a data set is partitioned among

More information

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

STAT STATISTICAL METHODS. Statistics: The science of using data to make decisions and draw conclusions STAT 515 --- STATISTICAL METHODS Statistics: The science of using data to make decisions and draw conclusions Two branches: Descriptive Statistics: The collection and presentation (through graphical and

More information

Descriptive Statistics

Descriptive Statistics Descriptive Statistics Library, Teaching & Learning 014 Summary of Basic data Analysis DATA Qualitative Quantitative Counted Measured Discrete Continuous 3 Main Measures of Interest Central Tendency Dispersion

More information

15 Wyner Statistics Fall 2013

15 Wyner Statistics Fall 2013 15 Wyner Statistics Fall 2013 CHAPTER THREE: CENTRAL TENDENCY AND VARIATION Summary, Terms, and Objectives The two most important aspects of a numerical data set are its central tendencies and its variation.

More information

STA Module 2B Organizing Data and Comparing Distributions (Part II)

STA Module 2B Organizing Data and Comparing Distributions (Part II) STA 2023 Module 2B Organizing Data and Comparing Distributions (Part II) Learning Objectives Upon completing this module, you should be able to 1 Explain the purpose of a measure of center 2 Obtain and

More information

STA Learning Objectives. Learning Objectives (cont.) Module 2B Organizing Data and Comparing Distributions (Part II)

STA Learning Objectives. Learning Objectives (cont.) Module 2B Organizing Data and Comparing Distributions (Part II) STA 2023 Module 2B Organizing Data and Comparing Distributions (Part II) Learning Objectives Upon completing this module, you should be able to 1 Explain the purpose of a measure of center 2 Obtain and

More information

Acquisition Description Exploration Examination Understanding what data is collected. Characterizing properties of data.

Acquisition Description Exploration Examination Understanding what data is collected. Characterizing properties of data. Summary Statistics Acquisition Description Exploration Examination what data is collected Characterizing properties of data. Exploring the data distribution(s). Identifying data quality problems. Selecting

More information

3. Data Analysis and Statistics

3. Data Analysis and Statistics 3. Data Analysis and Statistics 3.1 Visual Analysis of Data 3.2.1 Basic Statistics Examples 3.2.2 Basic Statistical Theory 3.3 Normal Distributions 3.4 Bivariate Data 3.1 Visual Analysis of Data Visual

More information

Chapter 3: Data Description - Part 3. Homework: Exercises 1-21 odd, odd, odd, 107, 109, 118, 119, 120, odd

Chapter 3: Data Description - Part 3. Homework: Exercises 1-21 odd, odd, odd, 107, 109, 118, 119, 120, odd Chapter 3: Data Description - Part 3 Read: Sections 1 through 5 pp 92-149 Work the following text examples: Section 3.2, 3-1 through 3-17 Section 3.3, 3-22 through 3.28, 3-42 through 3.82 Section 3.4,

More information

Math 227 EXCEL / MEGASTAT Guide

Math 227 EXCEL / MEGASTAT Guide Math 227 EXCEL / MEGASTAT Guide Introduction Introduction: Ch2: Frequency Distributions and Graphs Construct Frequency Distributions and various types of graphs: Histograms, Polygons, Pie Charts, Stem-and-Leaf

More information

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

Chapter 2. Descriptive Statistics: Organizing, Displaying and Summarizing Data Chapter 2 Descriptive Statistics: Organizing, Displaying and Summarizing Data Objectives Student should be able to Organize data Tabulate data into frequency/relative frequency tables Display data graphically

More information

Part I, Chapters 4 & 5. Data Tables and Data Analysis Statistics and Figures

Part I, Chapters 4 & 5. Data Tables and Data Analysis Statistics and Figures Part I, Chapters 4 & 5 Data Tables and Data Analysis Statistics and Figures Descriptive Statistics 1 Are data points clumped? (order variable / exp. variable) Concentrated around one value? Concentrated

More information

Quantitative - One Population

Quantitative - One Population Quantitative - One Population The Quantitative One Population VISA procedures allow the user to perform descriptive and inferential procedures for problems involving one population with quantitative (interval)

More information

Middle Years Data Analysis Display Methods

Middle Years Data Analysis Display Methods Middle Years Data Analysis Display Methods Double Bar Graph A double bar graph is an extension of a single bar graph. Any bar graph involves categories and counts of the number of people or things (frequency)

More information

STA Rev. F Learning Objectives. Learning Objectives (Cont.) Module 3 Descriptive Measures

STA Rev. F Learning Objectives. Learning Objectives (Cont.) Module 3 Descriptive Measures STA 2023 Module 3 Descriptive Measures Learning Objectives Upon completing this module, you should be able to: 1. Explain the purpose of a measure of center. 2. Obtain and interpret the mean, median, and

More information

MHPE 494: Data Analysis. Welcome! The Analytic Process

MHPE 494: Data Analysis. Welcome! The Analytic Process MHPE 494: Data Analysis Alan Schwartz, PhD Department of Medical Education Memoona Hasnain,, MD, PhD, MHPE Department of Family Medicine College of Medicine University of Illinois at Chicago Welcome! Your

More information

B. Graphing Representation of Data

B. Graphing Representation of Data B Graphing Representation of Data The second way of displaying data is by use of graphs Although such visual aids are even easier to read than tables, they often do not give the same detail It is essential

More information

Chapter 6: DESCRIPTIVE STATISTICS

Chapter 6: DESCRIPTIVE STATISTICS Chapter 6: DESCRIPTIVE STATISTICS Random Sampling Numerical Summaries Stem-n-Leaf plots Histograms, and Box plots Time Sequence Plots Normal Probability Plots Sections 6-1 to 6-5, and 6-7 Random Sampling

More information

Lecture Series on Statistics -HSTC. Frequency Graphs " Dr. Bijaya Bhusan Nanda, Ph. D. (Stat.)

Lecture Series on Statistics -HSTC. Frequency Graphs  Dr. Bijaya Bhusan Nanda, Ph. D. (Stat.) Lecture Series on Statistics -HSTC Frequency Graphs " By Dr. Bijaya Bhusan Nanda, Ph. D. (Stat.) CONTENT Histogram Frequency polygon Smoothed frequency curve Cumulative frequency curve or ogives Learning

More information

UNIT 1A EXPLORING UNIVARIATE DATA

UNIT 1A EXPLORING UNIVARIATE DATA A.P. STATISTICS E. Villarreal Lincoln HS Math Department UNIT 1A EXPLORING UNIVARIATE DATA LESSON 1: TYPES OF DATA Here is a list of important terms that we must understand as we begin our study of statistics

More information

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

Chapter 2. Frequency Distributions and Graphs. Bluman, Chapter 2 Chapter 2 Frequency Distributions and Graphs 1 Chapter 2 Overview Introduction 2-1 Organizing Data 2-2 Histograms, Frequency Polygons, and Ogives 2-3 Other Types of Graphs 2 Chapter 2 Objectives 1. Organize

More information

Table of Contents (As covered from textbook)

Table of Contents (As covered from textbook) Table of Contents (As covered from textbook) Ch 1 Data and Decisions Ch 2 Displaying and Describing Categorical Data Ch 3 Displaying and Describing Quantitative Data Ch 4 Correlation and Linear Regression

More information

STA 490H1S Initial Examination of Data

STA 490H1S Initial Examination of Data Initial Examination of Data Alison L. Department of Statistics University of Toronto Winter 2011 Course mantra It s OK not to know. Expressing ignorance is encouraged. It s not OK to not have a willingness

More information

KS4 Course Outline: Mathematics

KS4 Course Outline: Mathematics 6+ Topic Index Sheet, Autumn Term Year 10 D Factorise an expression eg. 6a+8 = 2(3a+4); a 2-3a = a(a - 3) 104 C Factorise an expression with 2 or more factors eg. 4x 3 + 6xy = 2x(2x 2 +3y) 104 D Write

More information

Spring 2017 CS130 - Intro to R 1 R VISUALIZING DATA. Spring 2017 CS130 - Intro to R 2

Spring 2017 CS130 - Intro to R 1 R VISUALIZING DATA. Spring 2017 CS130 - Intro to R 2 Spring 2017 CS130 - Intro to R 1 R VISUALIZING DATA Spring 2017 Spring 2017 CS130 - Intro to R 2 Goals for this lecture: Review constructing Data Frame, Categorizing variables Construct basic graph, learn

More information

Interactive Math Glossary Terms and Definitions

Interactive Math Glossary Terms and Definitions Terms and Definitions Absolute Value the magnitude of a number, or the distance from 0 on a real number line Addend any number or quantity being added addend + addend = sum Additive Property of Area the

More information

Unit WorkBook 2 Level 4 ENG U2 Engineering Maths LO2 Statistical Techniques 2018 UniCourse Ltd. All Rights Reserved. Sample

Unit WorkBook 2 Level 4 ENG U2 Engineering Maths LO2 Statistical Techniques 2018 UniCourse Ltd. All Rights Reserved. Sample Pearson BTEC Levels 4 and 5 Higher Nationals in Engineering (RQF) Unit 2: Engineering Maths (core) Unit Workbook 2 in a series of 4 for this unit Learning Outcome 2 Statistical Techniques Page 1 of 37

More information

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

CHAPTER 1. Introduction. Statistics: Statistics is the science of collecting, organizing, analyzing, presenting and interpreting data. 1 CHAPTER 1 Introduction Statistics: Statistics is the science of collecting, organizing, analyzing, presenting and interpreting data. Variable: Any characteristic of a person or thing that can be expressed

More information

Things you ll know (or know better to watch out for!) when you leave in December: 1. What you can and cannot infer from graphs.

Things you ll know (or know better to watch out for!) when you leave in December: 1. What you can and cannot infer from graphs. 1 2 Things you ll know (or know better to watch out for!) when you leave in December: 1. What you can and cannot infer from graphs. 2. How to construct (in your head!) and interpret confidence intervals.

More information

TMTH 3360 NOTES ON COMMON GRAPHS AND CHARTS

TMTH 3360 NOTES ON COMMON GRAPHS AND CHARTS To Describe Data, consider: Symmetry Skewness TMTH 3360 NOTES ON COMMON GRAPHS AND CHARTS Unimodal or bimodal or uniform Extreme values Range of Values and mid-range Most frequently occurring values In

More information

Page 1. Graphical and Numerical Statistics

Page 1. Graphical and Numerical Statistics TOPIC: Description Statistics In this tutorial, we show how to use MINITAB to produce descriptive statistics, both graphical and numerical, for an existing MINITAB dataset. The example data come from Exercise

More information

Minitab 17 commands Prepared by Jeffrey S. Simonoff

Minitab 17 commands Prepared by Jeffrey S. Simonoff Minitab 17 commands Prepared by Jeffrey S. Simonoff Data entry and manipulation To enter data by hand, click on the Worksheet window, and enter the values in as you would in any spreadsheet. To then save

More information

University of Florida CISE department Gator Engineering. Visualization

University of Florida CISE department Gator Engineering. Visualization Visualization Dr. Sanjay Ranka Professor Computer and Information Science and Engineering University of Florida What is visualization? Visualization is the process of converting data (information) in to

More information

AP Statistics Summer Assignment:

AP Statistics Summer Assignment: AP Statistics Summer Assignment: Read the following and use the information to help answer your summer assignment questions. You will be responsible for knowing all of the information contained in this

More information

UNIT 1: NUMBER LINES, INTERVALS, AND SETS

UNIT 1: NUMBER LINES, INTERVALS, AND SETS ALGEBRA II CURRICULUM OUTLINE 2011-2012 OVERVIEW: 1. Numbers, Lines, Intervals and Sets 2. Algebraic Manipulation: Rational Expressions and Exponents 3. Radicals and Radical Equations 4. Function Basics

More information

Engineering Methods in Microsoft Excel. Part 3: Data Analysis in Excel

Engineering Methods in Microsoft Excel. Part 3: Data Analysis in Excel Engineering Methods in Microsoft Excel Part 3: Data Analysis in Excel by Kwabena Ofosu, Ph.D., P.E., PTOE Abstract This course is the part of a series on engineering methods in Microsoft Excel; tailored

More information

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

Statistical Methods. Instructor: Lingsong Zhang. Any questions, ask me during the office hour, or  me, I will answer promptly. Statistical Methods Instructor: Lingsong Zhang 1 Issues before Class Statistical Methods Lingsong Zhang Office: Math 544 Email: lingsong@purdue.edu Phone: 765-494-7913 Office Hour: Monday 1:00 pm - 2:00

More information

Frequency Distributions and Graphs

Frequency Distributions and Graphs //05 C H A P T E R T W O s and s and Outline CHAPTER - Organizing Data - Histograms, Polygons, and - Other Types of -4 Paired Data and Scatter Plots Learning Objectives Organize data using a frequency

More information

CREATING THE DISTRIBUTION ANALYSIS

CREATING THE DISTRIBUTION ANALYSIS Chapter 12 Examining Distributions Chapter Table of Contents CREATING THE DISTRIBUTION ANALYSIS...176 BoxPlot...178 Histogram...180 Moments and Quantiles Tables...... 183 ADDING DENSITY ESTIMATES...184

More information

Probability and Statistics. Copyright Cengage Learning. All rights reserved.

Probability and Statistics. Copyright Cengage Learning. All rights reserved. Probability and Statistics Copyright Cengage Learning. All rights reserved. 14.5 Descriptive Statistics (Numerical) Copyright Cengage Learning. All rights reserved. Objectives Measures of Central Tendency:

More information

Applied Regression Modeling: A Business Approach

Applied Regression Modeling: A Business Approach i Applied Regression Modeling: A Business Approach Computer software help: SAS SAS (originally Statistical Analysis Software ) is a commercial statistical software package based on a powerful programming

More information

SLStats.notebook. January 12, Statistics:

SLStats.notebook. January 12, Statistics: Statistics: 1 2 3 Ways to display data: 4 generic arithmetic mean sample 14A: Opener, #3,4 (Vocabulary, histograms, frequency tables, stem and leaf) 14B.1: #3,5,8,9,11,12,14,15,16 (Mean, median, mode,

More information

LSP 121. LSP 121 Math and Tech Literacy II. Topics. Quartiles. Intro to Statistics. More Descriptive Statistics

LSP 121. LSP 121 Math and Tech Literacy II. Topics. Quartiles. Intro to Statistics. More Descriptive Statistics Greg Brewster, DePaul University Page 1 LSP 121 Math and Tech Literacy II More Descriptive Statistics Greg Brewster DePaul University Topics More Descriptive Statistics Quartiles Percentiles Categorical

More information

AP Statistics Prerequisite Packet

AP Statistics Prerequisite Packet Types of Data Quantitative (or measurement) Data These are data that take on numerical values that actually represent a measurement such as size, weight, how many, how long, score on a test, etc. For these

More information

Tabular & Graphical Presentation of data

Tabular & Graphical Presentation of data Tabular & Graphical Presentation of data bjectives: To know how to make frequency distributions and its importance To know different terminology in frequency distribution table To learn different graphs/diagrams

More information

1. To condense data in a single value. 2. To facilitate comparisons between data.

1. To condense data in a single value. 2. To facilitate comparisons between data. The main objectives 1. To condense data in a single value. 2. To facilitate comparisons between data. Measures :- Locational (positional ) average Partition values Median Quartiles Deciles Percentiles

More information

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.

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. Chapter 2 2.1 Descriptive Statistics A stem-and-leaf graph, also called a stemplot, allows for a nice overview of quantitative data without losing information on individual observations. It can be a good

More information

Enduring Understandings: Some basic math skills are required to be reviewed in preparation for the course.

Enduring Understandings: Some basic math skills are required to be reviewed in preparation for the course. Curriculum Map for Functions, Statistics and Trigonometry September 5 Days Targeted NJ Core Curriculum Content Standards: N-Q.1, N-Q.2, N-Q.3, A-CED.1, A-REI.1, A-REI.3 Enduring Understandings: Some basic

More information

Descriptive Statistics By

Descriptive Statistics By Faculty of Medicine Epidemiology and Biostatistics الوبائيات واإلحصاء الحيوي (31505204) Lecture 3-5 Descriptive Statistics By Hatim Jaber MD MPH JBCM PhD 11+12-6-2017 1 Presentation outline 11-6-2017 Time

More information

Fathom Dynamic Data TM Version 2 Specifications

Fathom Dynamic Data TM Version 2 Specifications Data Sources Fathom Dynamic Data TM Version 2 Specifications Use data from one of the many sample documents that come with Fathom. Enter your own data by typing into a case table. Paste data from other

More information

Summarising Data. Mark Lunt 09/10/2018. Arthritis Research UK Epidemiology Unit University of Manchester

Summarising Data. Mark Lunt 09/10/2018. Arthritis Research UK Epidemiology Unit University of Manchester Summarising Data Mark Lunt Arthritis Research UK Epidemiology Unit University of Manchester 09/10/2018 Summarising Data Today we will consider Different types of data Appropriate ways to summarise these

More information

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

This chapter will show how to organize data and then construct appropriate graphs to represent the data in a concise, easy-to-understand form. CHAPTER 2 Frequency Distributions and Graphs Objectives Organize data using frequency distributions. Represent data in frequency distributions graphically using histograms, frequency polygons, and ogives.

More information

CHAPTER 2: SAMPLING AND DATA

CHAPTER 2: SAMPLING AND DATA CHAPTER 2: SAMPLING AND DATA This presentation is based on material and graphs from Open Stax and is copyrighted by Open Stax and Georgia Highlands College. OUTLINE 2.1 Stem-and-Leaf Graphs (Stemplots),

More information

Data Management Project Using Software to Carry Out Data Analysis Tasks

Data Management Project Using Software to Carry Out Data Analysis Tasks Data Management Project Using Software to Carry Out Data Analysis Tasks This activity involves two parts: Part A deals with finding values for: Mean, Median, Mode, Range, Standard Deviation, Max and Min

More information

3 Graphical Displays of Data

3 Graphical Displays of Data 3 Graphical Displays of Data Reading: SW Chapter 2, Sections 1-6 Summarizing and Displaying Qualitative Data The data below are from a study of thyroid cancer, using NMTR data. The investigators looked

More information

STP 226 ELEMENTARY STATISTICS NOTES PART 2 - DESCRIPTIVE STATISTICS CHAPTER 3 DESCRIPTIVE MEASURES

STP 226 ELEMENTARY STATISTICS NOTES PART 2 - DESCRIPTIVE STATISTICS CHAPTER 3 DESCRIPTIVE MEASURES STP 6 ELEMENTARY STATISTICS NOTES PART - DESCRIPTIVE STATISTICS CHAPTER 3 DESCRIPTIVE MEASURES Chapter covered organizing data into tables, and summarizing data with graphical displays. We will now use

More information

CHAPTER 2 DESCRIPTIVE STATISTICS

CHAPTER 2 DESCRIPTIVE STATISTICS CHAPTER 2 DESCRIPTIVE STATISTICS 1. Stem-and-Leaf Graphs, Line Graphs, and Bar Graphs The distribution of data is how the data is spread or distributed over the range of the data values. This is one of

More information

Chapter 1: Overview and Descriptive Statistics

Chapter 1: Overview and Descriptive Statistics Chapter 1: Overview and Descriptive Statistics Curtis Miller 2018-05-13 Introduction This chapter is devoted to basic statistical ideas and statistical summaries. We start with describing what statistics

More information

Basic Statistical Terms and Definitions

Basic Statistical Terms and Definitions I. Basics Basic Statistical Terms and Definitions Statistics is a collection of methods for planning experiments, and obtaining data. The data is then organized and summarized so that professionals can

More information

1 Overview of Statistics; Essential Vocabulary

1 Overview of Statistics; Essential Vocabulary 1 Overview of Statistics; Essential Vocabulary Statistics: the science of collecting, organizing, analyzing, and interpreting data in order to make decisions Population and sample Population: the entire

More information

10.4 Measures of Central Tendency and Variation

10.4 Measures of Central Tendency and Variation 10.4 Measures of Central Tendency and Variation Mode-->The number that occurs most frequently; there can be more than one mode ; if each number appears equally often, then there is no mode at all. (mode

More information

10.4 Measures of Central Tendency and Variation

10.4 Measures of Central Tendency and Variation 10.4 Measures of Central Tendency and Variation Mode-->The number that occurs most frequently; there can be more than one mode ; if each number appears equally often, then there is no mode at all. (mode

More information

BUSINESS ANALYTICS. 96 HOURS Practical Learning. DexLab Certified. Training Module. Gurgaon (Head Office)

BUSINESS ANALYTICS. 96 HOURS Practical Learning. DexLab Certified. Training Module. Gurgaon (Head Office) SAS (Base & Advanced) Analytics & Predictive Modeling Tableau BI 96 HOURS Practical Learning WEEKDAY & WEEKEND BATCHES CLASSROOM & LIVE ONLINE DexLab Certified BUSINESS ANALYTICS Training Module Gurgaon

More information

Day 4 Percentiles and Box and Whisker.notebook. April 20, 2018

Day 4 Percentiles and Box and Whisker.notebook. April 20, 2018 Day 4 Box & Whisker Plots and Percentiles In a previous lesson, we learned that the median divides a set a data into 2 equal parts. Sometimes it is necessary to divide the data into smaller more precise

More information

ECLT 5810 Data Preprocessing. Prof. Wai Lam

ECLT 5810 Data Preprocessing. Prof. Wai Lam ECLT 5810 Data Preprocessing Prof. Wai Lam Why Data Preprocessing? Data in the real world is imperfect incomplete: lacking attribute values, lacking certain attributes of interest, or containing only aggregate

More information

Homework Packet Week #3

Homework Packet Week #3 Lesson 8.1 Choose the term that best completes statements # 1-12. 10. A data distribution is if the peak of the data is in the middle of the graph. The left and right sides of the graph are nearly mirror

More information

Understanding Statistical Questions

Understanding Statistical Questions Unit 6: Statistics Standards, Checklist and Concept Map Common Core Georgia Performance Standards (CCGPS): MCC6.SP.1: Recognize a statistical question as one that anticipates variability in the data related

More information

1.3 Graphical Summaries of Data

1.3 Graphical Summaries of Data Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan 1.3 Graphical Summaries of Data In the previous section we discussed numerical summaries of either a sample or a data. In this

More information

Data Preprocessing. S1 Teknik Informatika Fakultas Teknologi Informasi Universitas Kristen Maranatha

Data Preprocessing. S1 Teknik Informatika Fakultas Teknologi Informasi Universitas Kristen Maranatha Data Preprocessing S1 Teknik Informatika Fakultas Teknologi Informasi Universitas Kristen Maranatha 1 Why Data Preprocessing? Data in the real world is dirty incomplete: lacking attribute values, lacking

More information

2.1: Frequency Distributions

2.1: Frequency Distributions 2.1: Frequency Distributions Frequency Distribution: organization of data into groups called. A: Categorical Frequency Distribution used for and level qualitative data that can be put into categories.

More information

Grade 6 Curriculum and Instructional Gap Analysis Implementation Year

Grade 6 Curriculum and Instructional Gap Analysis Implementation Year Grade 6 Curriculum and Implementation Year 2014-2015 Revised Number and operations Proportionality What new content moves into the grade 6 curriculum in Use a visual representation to describe the relationship

More information

MAT 110 WORKSHOP. Updated Fall 2018

MAT 110 WORKSHOP. Updated Fall 2018 MAT 110 WORKSHOP Updated Fall 2018 UNIT 3: STATISTICS Introduction Choosing a Sample Simple Random Sample: a set of individuals from the population chosen in a way that every individual has an equal chance

More information

Measures of Dispersion

Measures of Dispersion Measures of Dispersion 6-3 I Will... Find measures of dispersion of sets of data. Find standard deviation and analyze normal distribution. Day 1: Dispersion Vocabulary Measures of Variation (Dispersion

More information

MATH 1070 Introductory Statistics Lecture notes Descriptive Statistics and Graphical Representation

MATH 1070 Introductory Statistics Lecture notes Descriptive Statistics and Graphical Representation MATH 1070 Introductory Statistics Lecture notes Descriptive Statistics and Graphical Representation Objectives: 1. Learn the meaning of descriptive versus inferential statistics 2. Identify bar graphs,

More information

Design of Experiments

Design of Experiments Seite 1 von 1 Design of Experiments Module Overview In this module, you learn how to create design matrices, screen factors, and perform regression analysis and Monte Carlo simulation using Mathcad. Objectives

More information