Diagrams and Graphs of Statistical Data


 Steven Daniel Roberts
 1 years ago
 Views:
Transcription
1 Diagrams and Graphs of Statistical Data One of the most effective and interesting alternative way in which a statistical data may be presented is through diagrams and graphs. There are several ways in which statistical data may be displayed pictorially such as different types of graphs and diagrams. 1
2 Patterns in Data Graphic displays are useful for seeing patterns in data. Patterns in data are commonly described in terms of: center, spread, shape, and unusual features. Some common distributions have special descriptive labels, such as: symmetric, bellshaped, skewed, etc. 2
3 Center Graphically, the center of a distribution is located at the median of the distribution. This is the point in a graphic display where about half of the observations are on either side. In the chart to the right, the height of each column indicates the frequency of observations. Here, the observations are centered over 4. 3
4 Spread The spread of a distribution refers to the variability of the data. If the observations cover a wide range, the spread is larger. If the observations are clustered around a single value, the spread is smaller. Consider the figures above. In the figure on the left, data values range from 3 to 7; whereas in the figure on the right, values range from 1 to 9. The figure on the right is more variable, so it has the greater spread. 4
5 Shape The shape of a distribution is described by the following characteristics. 1. Symmetry. When it is graphed, a symmetric distribution can be divided at the center so that each half is a mirror image of the other. 2. Number of peaks. Distributions can have few or many peaks. Distributions with one clear peak are called unimodal, and distributions with two clear peaks are called bimodal. When a symmetric distribution has a single peak at the center, it is referred to as bellshaped. 3. Skewness. When they are displayed graphically, some distributions have many more observations on one side of the graph than the other. Distributions with most of their observations on the left (toward lower values) are said to be skewed right; and distributions with most of their observations on the right (toward higher values) are said to be skewed left. 4. Uniform. When the observations in a set of data are equally spread across the range of the distribution, the distribution is called a uniform distribution. A uniform distribution has no clear peaks. 5
6 Some examples of distributions and shapes. 6
7 Unusual Features Sometimes, statisticians refer to unusual features in a set of data. The two most common unusual features are gaps and outliers. Gaps. Gaps refer to areas of a distribution where there are no observations. The first figure below has a gap; there are no observations in the middle of the distribution. Outliers. Sometimes, distributions are characterized by extreme values that differ greatly from the other observations. These extreme values are called outliers. The second figure below illustrates a distribution with an outlier. Except for one lonely observation (the outlier on the extreme right), all of the observations fall between 0 and 4. 7
8 Graphs in Statistics 1. Bar graph 2. Histogram 3. Pie graph 4. Line graph 5. Boxplot graph 6. Scatter graph 8
9 Bar Charts A bar graph is a way to visually represent qualitative data. A bar chart is made up of columns plotted on a graph. Here is how to read a bar chart. The columns are positioned over a label that represents a categorical variable. The height of the column indicates the size of the group defined by the column label. 9
10 Frecvency table
11 Histograms Histograms are graphs of a distribution of data designed to show centering, dispersion (spread), and shape (relative frequency) of the data. Like a bar chart, a histogram is made up of columns plotted on a graph. Usually, there is no space between adjacent columns. The columns are positioned over a label that represents a quantitative variable. The column label can be a single value or a range of values. The height of the column indicates the size of the group defined by the column label. 11
12 Frecvency table
13
14 Problem Consider the histograms below. Which of the following statements are true? I. Both data sets are symmetric. II. Both data sets have the same range. (A) I only (B) II only (C) I and II (D) Neither is true. (E) There is insufficient information to answer this question.
15 Pie Chart Pie Chart or Circle Graph  A pie chart displays qualitative data in the form of a pie. Each slice of pie represents a different category. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. 15
16 Pie chart Eye colors of 100 third grader students. Brown corresponds to brown eyes, blue to blue eyes, and green to hazel eyes. A pie chart is a way of summarizing a set of categorical data. It is a circle which is divided into segments. Each segment represents a particular category. The area of each segment is proportional to the number of cases in that category. 16
17 Haw to create a pie chart. Expenditure Items Expenditure Angle of sectors Cumulative angle Food Clothing House rent Fuel and Lighting Miscellaneous Total Food House rent Miscellaneous Clothing Fuel and Lighting 17
18 Line graph A line graph is often used to represent a set of data values in which a quantity varies with time. These graphs are useful for finding trends. That is, finding a general pattern in data sets including temperature, sales, employment, company profit or cost over a period of time. 18
19 Line graph. Exemple A cylinder of liquid was heated. Its temperature was recorded at tenminute intervals as shown in the following table Time in minutes Temperature in C a. Draw a line graph to represent this information. b. Estimate the temperature of the cylinder after 25 minutes of heating. 19
20 Boxplot graph What is a box plot? A box plot is a diagram that gives a visual representation to the distribution of the data, highlighting where most values lie and those values that greatly differ from the norm, called outliers. The box plot is also referred to as box and whisker plot or box and whisker diagram 20
21 Elements of the box plot 21
22 Consider the boxplot below. Which of the following statements are true? I. The distribution is skewed right. II. The interquartile range is about 8. III. The median is about 10. (A) I only (B) II only (C) III only (D) I and III (E) II and III 22
23 Scatter graph A scatterplot is a graphic tool used to display the relationship between two quantitative variables. It gives a good visual picture of the relationship between the two variables, and aids the interpretation of the correlation coefficient or regression model. Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation. 23
24 More about Scatter Plot What is a trend line? A line on a graph showing the general direction that a group of points seem to be heading. A scatter plot describes a positive trend if, as one set of values increases, the other set tends to increase. A scatter plot describes a negative trend if, as one set of values increases, the other set tends to decrease. A scatter plot shows no trend if the ordered pairs show no correlation. 24
25 Patterns of Data in Scatterplots Scatterplots are used to analyze patterns in bivariate data. These patterns are described in terms of linearity, slope, and strength. Linearity refers to whether a data pattern is linear (straight) or nonlinear (curved). Slope refers to the direction of change in variable Y when variable X gets bigger. If variable Y also gets bigger, the slope is positive; but if variable Y gets smaller, the slope is negative. Strength refers to the degree of "scatter" in the plot. If the dots are widely spread, the relationship between variables is weak. If the dots are concentrated around a line, the relationship is strong. 25
26 Patterns of Data in Scatterplots 26
27 Problem The scatterplot below shows the relation between two variables. Which of the following statements are true? I. The relation is strong. II. The slope is positive. III. The slope is negative. (A) I only (B) II only (C) III only (D) I and II (E) I and III
Summarizing and Displaying Categorical Data
Summarizing and Displaying Categorical Data Categorical data can be summarized in a frequency distribution which counts the number of cases, or frequency, that fall into each category, or a relative frequency
More informationExercise 1.12 (Pg. 2223)
Individuals: The objects that are described by a set of data. They may be people, animals, things, etc. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual.
More informationIII. GRAPHICAL METHODS
Pie Charts and Bar Charts: III. GRAPHICAL METHODS Pie charts and bar charts are used for depicting frequencies or relative frequencies. We compare examples of each using the same data. Sources: AT&T (1961)
More informationChapter 2 Summarizing and Graphing Data
Chapter 2 Summarizing and Graphing Data 21 Review and Preview 22 Frequency Distributions 23 Histograms 24 Graphs that Enlighten and Graphs that Deceive Preview Characteristics of Data 1. Center: A
More informationChapter 2  Graphical Summaries of Data
Chapter 2  Graphical Summaries of Data Data recorded in the sequence in which they are collected and before they are processed or ranked are called raw data. Raw data is often difficult to make sense
More informationChapter 2: Exploring Data with Graphs and Numerical Summaries. Graphical Measures Graphs are used to describe the shape of a data set.
Page 1 of 16 Chapter 2: Exploring Data with Graphs and Numerical Summaries Graphical Measures Graphs are used to describe the shape of a data set. Section 1: Types of Variables In general, variable can
More informationSTATS8: Introduction to Biostatistics. Data Exploration. Babak Shahbaba Department of Statistics, UCI
STATS8: Introduction to Biostatistics Data Exploration Babak Shahbaba Department of Statistics, UCI Introduction After clearly defining the scientific problem, selecting a set of representative members
More informationFrequency Distributions
Displaying Data Frequency Distributions After collecting data, the first task for a researcher is to organize and summarize the data to get a general overview of the results. Remember, this is the goal
More informationExploratory data analysis (Chapter 2) Fall 2011
Exploratory data analysis (Chapter 2) Fall 2011 Data Examples Example 1: Survey Data 1 Data collected from a Stat 371 class in Fall 2005 2 They answered questions about their: gender, major, year in school,
More informationData Mining Part 2. Data Understanding and Preparation 2.1 Data Understanding Spring 2010
Data Mining Part 2. and Preparation 2.1 Spring 2010 Instructor: Dr. Masoud Yaghini Introduction Outline Introduction Measuring the Central Tendency Measuring the Dispersion of Data Graphic Displays References
More informationGraphical and Tabular. Summarization of Data OPRE 6301
Graphical and Tabular Summarization of Data OPRE 6301 Introduction and Recap... Descriptive statistics involves arranging, summarizing, and presenting a set of data in such a way that useful information
More informationChapter 1: Looking at Data Distributions. Dr. Nahid Sultana
Chapter 1: Looking at Data Distributions Dr. Nahid Sultana Chapter 1: Looking at Data Distributions 1.1 Displaying Distributions with Graphs 1.2 Describing Distributions with Numbers 1.3 Density Curves
More informationM 225 Test 1 A Name (1 point) SHOW YOUR WORK FOR FULL CREDIT!
M 225 Test 1 A Name (1 point) SHOW YOUR WORK FOR FULL CREDIT! Problem Max. Points Your Points 114 14 15 3 16 5 17 4 18 4 19 11 20 9 21 8 22 16 Total 75 1 Multiple choice questions (1 point each) 1. Look
More informationCopyright 2006 Pearson Education, Inc. Publishing as Pearson AddisonWesley. Slide 41
Slide 41 Chapter 4 Displaying Quantitative Data Dealing With a Lot of Numbers Summarizing the data will help us when we look at large sets of quantitative data. Without summaries of the data, it s hard
More informationCommon Core Unit Summary Grades 6 to 8
Common Core Unit Summary Grades 6 to 8 Grade 8: Unit 1: Congruence and Similarity 8G18G5 rotations reflections and translations,( RRT=congruence) understand congruence of 2 d figures after RRT Dilations
More informationBiostatistics: A QUICK GUIDE TO THE USE AND CHOICE OF GRAPHS AND CHARTS
Biostatistics: A QUICK GUIDE TO THE USE AND CHOICE OF GRAPHS AND CHARTS 1. Introduction, and choosing a graph or chart Graphs and charts provide a powerful way of summarising data and presenting them in
More informationData Exploration Data Visualization
Data Exploration Data Visualization What is data exploration? A preliminary exploration of the data to better understand its characteristics. Key motivations of data exploration include Helping to select
More informationT O P I C 1 2 Techniques and tools for data analysis Preview Introduction In chapter 3 of Statistics In A Day different combinations of numbers and types of variables are presented. We go through these
More informationGeorgia Standards of Excellence Curriculum Frameworks. Mathematics. GSE Coordinate Algebra Unit 4: Describing Data
Georgia Standards of Excellence Curriculum Frameworks Mathematics GSE Coordinate Algebra Unit 4: Describing Data Unit 4 Describing Data Table of Contents OVERVIEW... 3 STANDARDS ADDRESSED IN THIS UNIT...
More informationLecture I. Definition 1. Statistics is the science of collecting, organizing, summarizing and analyzing the information in order to draw conclusions.
Lecture 1 1 Lecture I Definition 1. Statistics is the science of collecting, organizing, summarizing and analyzing the information in order to draw conclusions. It is a process consisting of 3 parts. Lecture
More informationMTH 140 Statistics Videos
MTH 140 Statistics Videos Chapter 1 Picturing Distributions with Graphs Individuals and Variables Categorical Variables: Pie Charts and Bar Graphs Categorical Variables: Pie Charts and Bar Graphs Quantitative
More informationSPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav)
Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Organize and Display One Quantitative Variable (Descriptive Statistics, Boxplot & Histogram) 1. Move the mouse pointer
More informationThere are some general common sense recommendations to follow when presenting
Presentation of Data The presentation of data in the form of tables, graphs and charts is an important part of the process of data analysis and report writing. Although results can be expressed within
More informationDesciptive Statistics Qualitative data Quantitative data Graphical methods Numerical methods
Desciptive Statistics Qualitative data Quantitative data Graphical methods Numerical methods Qualitative data Data are classified in categories Non numerical (although may be numerically codified) Elements
More informationA frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes
A frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes together with the number of data values from the set that
More informationF. Farrokhyar, MPhil, PhD, PDoc
Learning objectives Descriptive Statistics F. Farrokhyar, MPhil, PhD, PDoc To recognize different types of variables To learn how to appropriately explore your data How to display data using graphs How
More informationNumerical Measures of Central Tendency
Numerical Measures of Central Tendency Often, it is useful to have special numbers which summarize characteristics of a data set These numbers are called descriptive statistics or summary statistics. A
More informationSlides by. JOHN LOUCKS St. Edward s University
s by JOHN LOUCKS St. Edward s University 1 Chapter 2, Part A Descriptive Statistics: Tabular and Graphical Presentations Summarizing Qualitative Data Summarizing Quantitative Data 2 Summarizing Qualitative
More informationVertical Alignment Colorado Academic Standards 6 th  7 th  8 th
Vertical Alignment Colorado Academic Standards 6 th  7 th  8 th Standard 3: Data Analysis, Statistics, and Probability 6 th Prepared Graduates: 1. Solve problems and make decisions that depend on un
More informationIntro to Statistics 8 Curriculum
Intro to Statistics 8 Curriculum Unit 1 Bar, Line and Circle Graphs Estimated time frame for unit Big Ideas 8 Days... Essential Question Concepts Competencies Lesson Plans and Suggested Resources Bar graphs
More informationLean Six Sigma Training/Certification Book: Volume 1
Lean Six Sigma Training/Certification Book: Volume 1 Six Sigma Quality: Concepts & Cases Volume I (Statistical Tools in Six Sigma DMAIC process with MINITAB Applications Chapter 1 Introduction to Six Sigma,
More informationDemographics of Atlanta, Georgia:
Demographics of Atlanta, Georgia: A Visual Analysis of the 2000 and 2010 Census Data 36315 Final Project Rachel Cohen, Kathryn McKeough, Minnar Xie & David Zimmerman Ethnicities of Atlanta Figure 1: From
More informationDescriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2
Chapter Descriptive Statistics.1 Frequency Distributions and Their Graphs Frequency Distributions A frequency distribution is a table that shows classes or intervals of data with a count of the number
More informationInteractive 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 Additive Property of Area the process of finding an the area of a shape by totaling the areas
More informationExploratory Data Analysis
Exploratory Data Analysis Johannes Schauer johannes.schauer@tugraz.at Institute of Statistics Graz University of Technology Steyrergasse 17/IV, 8010 Graz www.statistics.tugraz.at February 12, 2008 Introduction
More informationMathematics. Probability and Statistics Curriculum Guide. Revised 2010
Mathematics Probability and Statistics Curriculum Guide Revised 2010 This page is intentionally left blank. Introduction The Mathematics Curriculum Guide serves as a guide for teachers when planning instruction
More informationData Chart Types From Jet Reports
Data Chart Types From Jet Reports Variable Width Column Chart Bar Chart Column Chart Circular Area Chart Line Chart Column Chart Line Chart Two Variables Per Item Many Items Few Items Cyclical Data NonCyclical
More informationVisualizing Data. Contents. 1 Visualizing Data. Anthony Tanbakuchi Department of Mathematics Pima Community College. Introductory Statistics Lectures
Introductory Statistics Lectures Visualizing Data Descriptive Statistics I Department of Mathematics Pima Community College Redistribution of this material is prohibited without written permission of the
More information909 responses responded via telephone survey in U.S. Results were shown by political affiliations (show graph on the board)
1 21 Overview Chapter 2: Learn the methods of organizing, summarizing, and graphing sets of data, ultimately, to understand the data characteristics: Center, Variation, Distribution, Outliers, Time. (Computer
More informationLecture 2: Descriptive Statistics and Exploratory Data Analysis
Lecture 2: Descriptive Statistics and Exploratory Data Analysis Further Thoughts on Experimental Design 16 Individuals (8 each from two populations) with replicates Pop 1 Pop 2 Randomly sample 4 individuals
More informationWHICH TYPE OF GRAPH SHOULD YOU CHOOSE?
PRESENTING GRAPHS WHICH TYPE OF GRAPH SHOULD YOU CHOOSE? CHOOSING THE RIGHT TYPE OF GRAPH You will usually choose one of four very common graph types: Line graph Bar graph Pie chart Histograms LINE GRAPHS
More informationHow to interpret scientific & statistical graphs
How to interpret scientific & statistical graphs Theresa A Scott, MS Department of Biostatistics theresa.scott@vanderbilt.edu http://biostat.mc.vanderbilt.edu/theresascott 1 A brief introduction Graphics:
More informationFinal Review Sheet. Mod 2: Distributions for Quantitative Data
Things to Remember from this Module: Final Review Sheet Mod : Distributions for Quantitative Data How to calculate and write sentences to explain the Mean, Median, Mode, IQR, Range, Standard Deviation,
More informationA Correlation of. to the. South Carolina Data Analysis and Probability Standards
A Correlation of to the South Carolina Data Analysis and Probability Standards INTRODUCTION This document demonstrates how Stats in Your World 2012 meets the indicators of the South Carolina Academic Standards
More informationTYPES OF DATA TYPES OF VARIABLES
TYPES OF DATA Univariate data Examines the distribution features of one variable. Bivariate data Explores the relationship between two variables. Univariate and bivariate analysis will be revised separately.
More informationWeek 1. Exploratory Data Analysis
Week 1 Exploratory Data Analysis Practicalities This course ST903 has students from both the MSc in Financial Mathematics and the MSc in Statistics. Two lectures and one seminar/tutorial per week. Exam
More informationVariables. Exploratory Data Analysis
Exploratory Data Analysis Exploratory Data Analysis involves both graphical displays of data and numerical summaries of data. A common situation is for a data set to be represented as a matrix. There is
More informationDescribe what is meant by a placebo Contrast the doubleblind procedure with the singleblind procedure Review the structure for organizing a memo
Readings: Ha and Ha Textbook  Chapters 1 8 Appendix D & E (online) Plous  Chapters 10, 11, 12 and 14 Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability
More informationChapter 3: Data Description Numerical Methods
Chapter 3: Data Description Numerical Methods Learning Objectives Upon successful completion of Chapter 3, you will be able to: Summarize data using measures of central tendency, such as the mean, median,
More informationList of Examples. Examples 319
Examples 319 List of Examples DiMaggio and Mantle. 6 Weed seeds. 6, 23, 37, 38 Vole reproduction. 7, 24, 37 Wooly bear caterpillar cocoons. 7 Homophone confusion and Alzheimer s disease. 8 Gear tooth strength.
More informationDESCRIPTIVE STATISTICS AND EXPLORATORY DATA ANALYSIS
DESCRIPTIVE STATISTICS AND EXPLORATORY DATA ANALYSIS SEEMA JAGGI Indian Agricultural Statistics Research Institute Library Avenue, New Delhi  110 012 seema@iasri.res.in 1. Descriptive Statistics Statistics
More information9.8 Rockin the Residuals
SECONDARY MATH 1 // MODULE 9 43 9.8 Rockin the Residuals A Solidify Understanding Task The correlation coefficient is not the only tool that statisticians use to analyze whether or not a line is a good
More informationChapter 2. Objectives. Tabulate Qualitative Data. Frequency Table. Descriptive Statistics: Organizing, Displaying and Summarizing Data.
Objectives Chapter Descriptive Statistics: Organizing, Displaying and Summarizing Data Student should be able to Organize data Tabulate data into frequency/relative frequency tables Display data graphically
More informationThe Big 50 Revision Guidelines for S1
The Big 50 Revision Guidelines for S1 If you can understand all of these you ll do very well 1. Know what is meant by a statistical model and the Modelling cycle of continuous refinement 2. Understand
More information1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number
1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x  x) B. x 3 x C. 3x  x D. x  3x 2) Write the following as an algebraic expression
More informationvs. relative cumulative frequency
Variable  what we are measuring Quantitative  numerical where mathematical operations make sense. These have UNITS Categorical  puts individuals into categories Numbers don't always mean Quantitative...
More informationGraphical methods for presenting data
Chapter 2 Graphical methods for presenting data 2.1 Introduction We have looked at ways of collecting data and then collating them into tables. Frequency tables are useful methods of presenting data; they
More informationThe Comparisons. Grade Levels Comparisons. Focal PSSM K8. Points PSSM CCSS 912 PSSM CCSS. Color Coding Legend. Not Identified in the Grade Band
Comparison of NCTM to Dr. Jim Bohan, Ed.D Intelligent Education, LLC Intel.educ@gmail.com The Comparisons Grade Levels Comparisons Focal K8 Points 912 prek through 12 Instructional programs from prekindergarten
More informationTechnology StepbyStep Using StatCrunch
Technology StepbyStep Using StatCrunch Section 1.3 Simple Random Sampling 1. Select Data, highlight Simulate Data, then highlight Discrete Uniform. 2. Fill in the following window with the appropriate
More informationDescriptive Statistics. Understanding Data: Categorical Variables. Descriptive Statistics. Dataset: Shellfish Contamination
Descriptive Statistics Understanding Data: Dataset: Shellfish Contamination Location Year Species Species2 Method Metals Cadmium (mg kg  ) Chromium (mg kg  ) Copper (mg kg  ) Lead (mg kg  ) Mercury
More informationIntroduction. One of the most convincing and appealing ways in which statistical results may be presented is through diagrams and graphs.
Introduction One of the most convincing and appealing ways in which statistical results may be presented is through diagrams and graphs. Just one diagram is enough to represent a given data more effectively
More informationContent DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS
Content DESCRIPTIVE STATISTICS Dr Najib Majdi bin Yaacob MD, MPH, DrPH (Epidemiology) USM Unit of Biostatistics & Research Methodology School of Medical Sciences Universiti Sains Malaysia. Introduction
More informationChapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs
Types of Variables Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs Quantitative (numerical)variables: take numerical values for which arithmetic operations make sense (addition/averaging)
More informationStatistics Chapter 2
Statistics Chapter 2 Frequency Tables A frequency table organizes quantitative data. partitions data into classes (intervals). shows how many data values are in each class. Test Score Number of Students
More informationTutorial 3: Graphics and Exploratory Data Analysis in R Jason Pienaar and Tom Miller
Tutorial 3: Graphics and Exploratory Data Analysis in R Jason Pienaar and Tom Miller Getting to know the data An important first step before performing any kind of statistical analysis is to familiarize
More informationChapter 2: Looking at Data Relationships (Part 1)
Chapter 2: Looking at Data Relationships (Part 1) Dr. Nahid Sultana Chapter 2: Looking at Data Relationships 2.1: Scatterplots 2.2: Correlation 2.3: LeastSquares Regression 2.5: Data Analysis for TwoWay
More informationIn this course, we will consider the various possible types of presentation of data and justification for their use in given situations.
PRESENTATION OF DATA 1.1 INTRODUCTION Once data has been collected, it has to be classified and organised in such a way that it becomes easily readable and interpretable, that is, converted to information.
More informationFrequency distributions, central tendency & variability. Displaying data
Frequency distributions, central tendency & variability Displaying data Software SPSS Excel/Numbers/Google sheets Social Science Statistics website (socscistatistics.com) Creating and SPSS file Open the
More informationDomain: Statistics and Probability (SP) Cluster: Investigate patterns of association in bivariate data.
Domain: Statistics and Probability (SP) Standard: 8.SP.1. Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns
More informationUnit 9 Describing Relationships in Scatter Plots and Line Graphs
Unit 9 Describing Relationships in Scatter Plots and Line Graphs Objectives: To construct and interpret a scatter plot or line graph for two quantitative variables To recognize linear relationships, nonlinear
More informationMATHEMATICS GRADE LEVEL VOCABULARY DRAWN FROM SBAC ITEM SPECIFICATIONS VERSION 1.1 JUNE 18, 2014
VERSION 1.1 JUNE 18, 2014 MATHEMATICS GRADE LEVEL VOCABULARY DRAWN FROM SBAC ITEM SPECIFICATIONS PRESENTED BY: WASHINGTON STATE REGIONAL MATH COORDINATORS Smarter Balanced Vocabulary  From SBAC test/item
More informationThe Big Picture. Describing Data: Categorical and Quantitative Variables Population. Descriptive Statistics. Community Coalitions (n = 175)
Describing Data: Categorical and Quantitative Variables Population The Big Picture Sampling Statistical Inference Sample Exploratory Data Analysis Descriptive Statistics In order to make sense of data,
More informationModule 2 Project Maths Development Team Draft (Version 2)
5 Week Modular Course in Statistics & Probability Strand 1 Module 2 Analysing Data Numerically Measures of Central Tendency Mean Median Mode Measures of Spread Range Standard Deviation InterQuartile Range
More informationChapter 7: Scatter Plots, Association, and Correlation
Chapter 7: Scatter Plots, Association, and Correlation Scatterplots compare two quantitative variables in the same way that segmented bar charts compared two categorical variables. You can start observing
More informationMinitab Guide. This packet contains: A Friendly Guide to Minitab. Minitab StepByStep
Minitab Guide This packet contains: A Friendly Guide to Minitab An introduction to Minitab; including basic Minitab functions, how to create sets of data, and how to create and edit graphs of different
More informationwith functions, expressions and equations which follow in units 3 and 4.
Grade 8 Overview View unit yearlong overview here The unit design was created in line with the areas of focus for grade 8 Mathematics as identified by the Common Core State Standards and the PARCC Model
More informationHISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS
Mathematics Revision Guides Histograms, Cumulative Frequency and Box Plots Page 1 of 25 M.K. HOME TUITION Mathematics Revision Guides Level: GCSE Higher Tier HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS
More informationIf the Shoe Fits! Overview of Lesson GAISE Components Common Core State Standards for Mathematical Practice
If the Shoe Fits! Overview of Lesson In this activity, students explore and use hypothetical data collected on student shoe print lengths, height, and gender in order to help develop a tentative description
More information2. Describing Data. We consider 1. Graphical methods 2. Numerical methods 1 / 56
2. Describing Data We consider 1. Graphical methods 2. Numerical methods 1 / 56 General Use of Graphical and Numerical Methods Graphical methods can be used to visually and qualitatively present data and
More informationR Graphics Cookbook. Chang O'REILLY. Winston. Tokyo. Beijing Cambridge. Farnham Koln Sebastopol
R Graphics Cookbook Winston Chang Beijing Cambridge Farnham Koln Sebastopol O'REILLY Tokyo Table of Contents Preface ix 1. R Basics 1 1.1. Installing a Package 1 1.2. Loading a Package 2 1.3. Loading a
More informationData Visualization Techniques
Data Visualization Techniques From Basics to Big Data with SAS Visual Analytics WHITE PAPER SAS White Paper Table of Contents Introduction.... 1 Generating the Best Visualizations for Your Data... 2 The
More informationSouth Carolina College and CareerReady (SCCCR) Probability and Statistics
South Carolina College and CareerReady (SCCCR) Probability and Statistics South Carolina College and CareerReady Mathematical Process Standards The South Carolina College and CareerReady (SCCCR)
More informationAP Statistics: Syllabus 3
AP Statistics: Syllabus 3 Scoring Components SC1 The course provides instruction in exploring data. 4 SC2 The course provides instruction in sampling. 5 SC3 The course provides instruction in experimentation.
More informationGRADES 7, 8, AND 9 BIG IDEAS
Table 1: Strand A: BIG IDEAS: MATH: NUMBER Introduce perfect squares, square roots, and all applications Introduce rational numbers (positive and negative) Introduce the meaning of negative exponents for
More informationMath Review Large Print (18 point) Edition Chapter 4: Data Analysis
GRADUATE RECORD EXAMINATIONS Math Review Large Print (18 point) Edition Chapter 4: Data Analysis Copyright 2010 by Educational Testing Service. All rights reserved. ETS, the ETS logo, GRADUATE RECORD EXAMINATIONS,
More informationCOMMON CORE STATE STANDARDS FOR
COMMON CORE STATE STANDARDS FOR Mathematics (CCSSM) High School Statistics and Probability Mathematics High School Statistics and Probability Decisions or predictions are often based on data numbers in
More informationInterpreting Data in Normal Distributions
Interpreting Data in Normal Distributions This curve is kind of a big deal. It shows the distribution of a set of test scores, the results of rolling a die a million times, the heights of people on Earth,
More information1.3 Measuring Center & Spread, The Five Number Summary & Boxplots. Describing Quantitative Data with Numbers
1.3 Measuring Center & Spread, The Five Number Summary & Boxplots Describing Quantitative Data with Numbers 1.3 I can n Calculate and interpret measures of center (mean, median) in context. n Calculate
More informationIntroduction to Stata: Graphic Displays of Data and Correlation
Math 143 Lab #1 Introduction to Stata: Graphic Displays of Data and Correlation Overview Thus far in the course, you have produced most of our graphical displays by hand, calculating summaries and correlations
More informationMathematics Common Core Cluster. Mathematics Common Core Standard. Domain
Mathematics Common Core Domain Mathematics Common Core Cluster Mathematics Common Core Standard Number System Know that there are numbers that are not rational, and approximate them by rational numbers.
More informationCommon Tools for Displaying and Communicating Data for Process Improvement
Common Tools for Displaying and Communicating Data for Process Improvement Packet includes: Tool Use Page # Box and Whisker Plot Check Sheet Control Chart Histogram Pareto Diagram Run Chart Scatter Plot
More informationData Visualization Techniques
Data Visualization Techniques From Basics to Big Data with SAS Visual Analytics WHITE PAPER SAS White Paper Table of Contents Introduction.... 1 Generating the Best Visualizations for Your Data... 2 The
More informationSan Jose State University Engineering 10 1
KY San Jose State University Engineering 10 1 Select Insert from the main menu Plotting in Excel Select All Chart Types San Jose State University Engineering 10 2 Definition: A chart that consists of multiple
More informationModule 2: Introduction to Quantitative Data Analysis
Module 2: Introduction to Quantitative Data Analysis Contents Antony Fielding 1 University of Birmingham & Centre for Multilevel Modelling Rebecca Pillinger Centre for Multilevel Modelling Introduction...
More informationPresentation of data
2 Presentation of data Using various types of graph and chart to illustrate data visually In this chapter we are going to investigate some basic elements of data presentation. We shall look at ways in
More information13.2 Measures of Central Tendency
13.2 Measures of Central Tendency Measures of Central Tendency For a given set of numbers, it may be desirable to have a single number to serve as a kind of representative value around which all the numbers
More informationREVISED GCSE Scheme of Work Mathematics Higher Unit T3. For First Teaching September 2010 For First Examination Summer 2011
REVISED GCSE Scheme of Work Mathematics Higher Unit T3 For First Teaching September 2010 For First Examination Summer 2011 Version 1: 28 April 10 Version 1: 28 April 10 Unit T3 Unit T3 This is a working
More informationComments 2 For Discussion Sheet 2 and Worksheet 2 Frequency Distributions and Histograms
Comments 2 For Discussion Sheet 2 and Worksheet 2 Frequency Distributions and Histograms Discussion Sheet 2 We have studied graphs (charts) used to represent categorical data. We now want to look at a
More informationBusiness Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.
Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationGCSE Statistics Revision notes
GCSE Statistics Revision notes Collecting data Sample This is when data is collected from part of the population. There are different methods for sampling Random sampling, Stratified sampling, Systematic
More information