Graphing Data Presentation of Data in Visual Forms


 Rodney Gaines
 1 years ago
 Views:
Transcription
1 Graphing Data Presentation of Data in Visual Forms Purpose of Graphing Data Audience Appeal Provides a visually appealing and succinct representation of data and summary statistics Provides a visually appealing and succinct representation of relationships between variables Diagnostics Determine Characteristics of Data Are there patterns in the data? Could there be relationships between variables? Determine Quality of Data Distribution of data Outliers Data cleaning
2 Graphing Data for Diagnostics Purposes A More Indepth Explanation Determine Quality of Data Distribution of data Is it normally distributed? Outliers Are there anomalies? Data cleaning Does data correspond to possible answer categories? (i.e., Was there a 3 recorded for gender even though codebook only lists 1. male, 2. female?)
3 A Diagnostics Tool for Examining the Distribution of Continuous Data One of the most commonly used diagnostic tools for continuous data is the histogram. The following slides outline how to construct and use this valuable tool.
4 The Importance of Histograms What is a histogram? Why do we use histograms? What does a normal distribution look like? Why is a normal distribution important? How are histograms constructed?
5 What is a histogram? Histograms A histogram is a pictorial representation of the distribution of continuous data ranked from the lowest to the highest value. Below are two histograms representing the distribution of IQ scores for men and women in the U.S. Men Women
6 Histograms Why do we use histograms? Histograms are used for diagnostic purposes, and to answer the following questions. Is data normally distributed? Are there outliers? Histograms can be used to predict. The probability of individual values or scores. The probability of individual values occurring within a designated interval. IQ Scores for Males What is the probability of an IQ between 100 and 120? What is the probability of a score of 140 or above?
7 Histograms Histograms, Tables and Cumulative Graphs Histograms and tables can be used to construct each other Understanding the relationship between tables and histograms can help you present and interpret your data more accurately and precisely Histograms and tables can be used to construct cumulative graphs Cumulative graphs can, in turn, be used to predict individual values Common examples where cumulative graphs are used include Standardized tests (i.e., SAT, ACT) Weight and height charts used in doctor s offices Mental health indices
8 Histograms What does a normal distribution look like? Most histograms have an approximately normal distribution. If you drew a smooth line connecting the midpoints of each interval, the line would outline a figure that is symmetrical and the number of values would decrease steadily as the distance from the mean increases.
9 Histograms What does a normal distribution look like? Normal distributions are symmetrical. The mean and median are the same value. IQ scores of US males and females are an example. Most variables have normally distributed values. Positive skew mean is greater than median. Example is income. Negative skew  mean is less than median. Example is student exam scores. Hamilton
10 Histograms Why is a normal distribution important? Most statistical formulas for analyzing continuous data assumes a normal distribution Therefore the results of statistical analysis is not valid unless the distribution is normal How are histograms constructed? Statistical programs can be used to construct histograms, or you can construct them manually Data is ranked from lowest to highest value Equal intervals are constructed The number of individual values within each interval are calculated The intervals are then distributed on a number line
11 Stem and Leaf Plot An Easy Way to Construct Your Own Histogram Step 1: Line up scores from lowest to highest values Step 2: Decide on width of your stems or categories With a single stem histogram, the width is 10 Step 3: Put the tens digits down the columns, with the ones digits placed in the rows equally spaced Step 4 Rotate the stem and leaf plot 90 degrees, and you have a histogram
12 Variations of the Stem and Leaf Plot The interval widths can be of different sizes. This example uses the same raw data. The width of each stem is 2. Five Stem Histogram Using Same Data 4* 4t 4f 4s * 5t 5f 5s 5. 6* t 4 4 6f s 6. You would use this stem and leaf plot if your data was more tightly clustered
13 Constructing Your Own Histogram Constructing your own histogram and cumulative graph is not recommended: (1) if you data set is large, and/or (2) you plan to enter the data into a computer program anyway for other research purposes (i.e., running statistical tests or generating descriptive statistics) HOWEVER, statisticians recommend that you do know how to construct a histogram manually as it helps you understand and interpret them more easily. It can also give you a quick preliminary summation of your data before entering it into the computer.
14 Understanding the Relationship Between Raw Data, Tables, and Histograms In this example we will construct the table, then the histogram, and finally a cumulative graph. The construction of these graphs/tables can be done in a different order. Constructing a table that can be used to construct a histogram and cumulative graphs: Step 1  Order values from lowest to highest as shown below 33, 50, 52, 60, 63, 65, 65, 65, 66,67, 68, 69, 69, 70, 70, 71, 71, 72, 73, 73, 74,74, 74, 75, 75, 75, 75, 75, 76, 76, 77,77, 77, 78, 78, 80, 81, 82, 83, 84, 84,87, 88, 88, 90, 90, 92, 95, 95, 98,
15 Use a Template Similar to the One Below Class Intervals are Reported Here The Percent of the Total Number of Values is Reported Here The Cumulative Percent is Reported Here Frequency Cumulative Frequency Percent Cumulative Percent A + D + B = C E = F The Number of Values in Each Interval is Reported in This Column The Cumulative Number of Values is Reported Here
16 Step 2 Report the Intervals in the First Column In this Example, the Class Interval is 5 (i.e., 30,31,32,33,34, are in the first interval) Frequency Cumulative Frequency Percent Cumulative Percent
17 Step 3 Count the Number of Values in Each Interval and Report Them Under Frequency Frequency Cumulative Frequency Percent Cumulative Percent
18 Step 4 Count the Number in the Frequency Column and Report it in Cumulative Frequency Frequency Cumulative Frequency Percent Cumulative Percent
19 Step 5 Compute and Report the Percent for Each Frequency For Instance, the Frequency in Interval is 1, and 1 is 2% of the Total (50 cases) Frequency Cumulative Frequency Percent Cumulative Percent
20 Step 6 Compute and Report the Cumulative Percent (Similar to What was Done in Step 3 for Cumulative Frequency) Frequency Cumulative Frequency Percent Cumulative Percent
21 This Histogram can Then be Constructed BINS are constructed. Each bin is the width of the corresponding interval from the table. The first bin should start with the lowest interval, and the last bin should start with the highest interval (i.e., ).
22 This Histogram can Then be Constructed Frequency
23
24 Using the Same Data Set, You Can Construct a Cumulative Graph
25 Frequency Cumulative Frequency Percent Cumulative Percent The Table you have Constructed can be used to Construct a Cumulative Graph.
26 Cumulative Percent Use the Cumulative Percent to Construct the Graph Plot the cumulative percent at the midpoint of each interval. For instance, for the first interval (3034), you would plot a 2 at the midpoint or middle of this interval. Do the same for each interval, and then connect the plot points. Cumulative Graph
27 Cumulative Frequency Cumulative Graph 1 3 OR you could Use the Cumulative Frequency
28 Cumulative Graph To predict percent and/or value, you simply use the cumulative graph line. You draw a straight line from the value/percent to the graph line, and then a straight line to the corresponding percent/value. (1) Determine percent that corresponds to a value of 75. In this instance, a score of 75 is in the 58 percentile. (2) Determine the score of a certain percent. The 75 th percent corresponds to an approximate score of 80. The Cumulative Graph can be used to predict the approximate percentile for any value, and the approximate value for any percentile
29 You can also use a cumulative graph to determine if your data have an approximately normal distribution. The graph in the upper left hand corner corresponds to a bellshaped, or normal distribution.
30 The cumulative graphs at the top are negatively and positively skewed. The correspond to a negatively or positively skewed histogram as shown directly below them.
31 Questions or Comments, Contact: Dr. Carol Albrecht Assessment Specialist USU Ext (979)
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
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 informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. C) (a) 2 (b) 1
Unit 2 Review Name Use the given frequency distribution to find the (a) class width. (b) class midpoints of the first class. (c) class boundaries of the first class. 1) Miles (per day) 12 9 34 22 56
More informationFREQUENCY AND PERCENTILES
FREQUENCY DISTRIBUTIONS AND PERCENTILES New Statistical Notation Frequency (f): the number of times a score occurs N: sample size Simple Frequency Distributions Raw Scores The scores that we have directly
More informationCentral Tendency. n Measures of Central Tendency: n Mean. n Median. n Mode
Central Tendency Central Tendency n A single summary score that best describes the central location of an entire distribution of scores. n Measures of Central Tendency: n Mean n The sum of all scores divided
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 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 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 informationSummarizing 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 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 informationGCSE HIGHER Statistics Key Facts
GCSE HIGHER Statistics Key Facts Collecting Data When writing questions for questionnaires, always ensure that: 1. the question is worded so that it will allow the recipient to give you the information
More informationDensity Curve. A density curve is the graph of a continuous probability distribution. It must satisfy the following properties:
Density Curve A density curve is the graph of a continuous probability distribution. It must satisfy the following properties: 1. The total area under the curve must equal 1. 2. Every point on the curve
More informationReport of for Chapter 2 pretest
Report of for Chapter 2 pretest Exam: Chapter 2 pretest Category: Organizing and Graphing Data 1. "For our study of driving habits, we recorded the speed of every fifth vehicle on Drury Lane. Nearly every
More informationWe will use the following data sets to illustrate measures of center. DATA SET 1 The following are test scores from a class of 20 students:
MODE The mode of the sample is the value of the variable having the greatest frequency. Example: Obtain the mode for Data Set 1 77 For a grouped frequency distribution, the modal class is the class having
More informationCHAPTER 3 CENTRAL TENDENCY ANALYSES
CHAPTER 3 CENTRAL TENDENCY ANALYSES The next concept in the sequential statistical steps approach is calculating measures of central tendency. Measures of central tendency represent some of the most simple
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 informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. C) (a) 3 (b) 51
Chapter 2 Problems to look at Use the given frequency distribution to find the (a) class width. (b) class midpoints of the first class. (c) class boundaries of the first class. 1) Height (in inches) 1)
More informationThe right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median
CONDENSED LESSON 2.1 Box Plots In this lesson you will create and interpret box plots for sets of data use the interquartile range (IQR) to identify potential outliers and graph them on a modified box
More informationSta 309 (Statistics And Probability for Engineers)
Instructor: Prof. Mike Nasab Sta 309 (Statistics And Probability for Engineers) Chapter 2 Organizing and Summarizing Data Raw Data: When data are collected in original form, they are called raw data. The
More informationDESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.
DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,
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 informationSampling, frequency distribution, graphs, measures of central tendency, measures of dispersion
Statistics Basics Sampling, frequency distribution, graphs, measures of central tendency, measures of dispersion Part 1: Sampling, Frequency Distributions, and Graphs The method of collecting, organizing,
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 informationDiagrams and Graphs of Statistical Data
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
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 informationDescriptive statistics Statistical inference statistical inference, statistical induction and inferential statistics
Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data. Descriptive statistics are distinguished from inferential statistics (or inductive statistics),
More informationChapter 15 Multiple Choice Questions (The answers are provided after the last question.)
Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) 1. What is the median of the following set of scores? 18, 6, 12, 10, 14? a. 10 b. 14 c. 18 d. 12 2. Approximately
More informationStatistics 101 Homework 2
Statistics 101 Homework 2 Solution Reading: January 23 January 25 Chapter 4 January 28 Chapter 5 Assignment: 1. As part of a physiology study participants had their heart rate (beats per minute) taken
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 informationMathematics Teachers Self Study Guide on the national Curriculum Statement. Book 2 of 2
Mathematics Teachers Self Study Guide on the national Curriculum Statement Book 2 of 2 1 WORKING WITH GROUPED DATA Material written by Meg Dickson and Jackie Scheiber RADMASTE Centre, University of the
More informationSTAB22 section 1.1. total = 88(200/100) + 85(200/100) + 77(300/100) + 90(200/100) + 80(100/100) = 176 + 170 + 231 + 180 + 80 = 837,
STAB22 section 1.1 1.1 Find the student with ID 104, who is in row 5. For this student, Exam1 is 95, Exam2 is 98, and Final is 96, reading along the row. 1.2 This one involves a careful reading of the
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 informationChapter 2: Frequency Distributions and Graphs
Chapter 2: Frequency Distributions and Graphs Learning Objectives Upon completion of Chapter 2, you will be able to: Organize the data into a table or chart (called a frequency distribution) Construct
More informationThe Ordered Array. Chapter Chapter Goals. Organizing and Presenting Data Graphically. Before you continue... Stem and Leaf Diagram
Chapter  Chapter Goals After completing this chapter, you should be able to: Construct a frequency distribution both manually and with Excel Construct and interpret a histogram Chapter Presenting Data
More informationMEASURES OF VARIATION
NORMAL DISTRIBTIONS MEASURES OF VARIATION In statistics, it is important to measure the spread of data. A simple way to measure spread is to find the range. But statisticians want to know if the data are
More informationExam # 1 STAT The number of people from the state of Alaska الاسكا) (ولاية who voted for a Republican
King Abdulaziz University Faculty of Sciences Statistics Department Name: ID No: Exam # 1 STAT 11 First Term 149143H Section: 6 You have 6 questions in 7 pages. You have 1 minutes to solve the exam. Please
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 2. The Normal Distribution
Chapter 2 The Normal Distribution Lesson 21 Density Curve Review Graph the data Calculate a numerical summary of the data Describe the shape, center, spread and outliers of the data Histogram with Curve
More informationHistograms and density curves
Histograms and density curves What s in our toolkit so far? Plot the data: histogram (or stemplot) Look for the overall pattern and identify deviations and outliers Numerical summary to briefly describe
More informationAP Statistics Semester Exam Review Chapters 13
AP Statistics Semester Exam Review Chapters 13 1. Here are the IQ test scores of 10 randomly chosen fifthgrade students: 145 139 126 122 125 130 96 110 118 118 To make a stemplot of these scores, you
More informationData Analysis: Describing Data  Descriptive Statistics
WHAT IT IS Return to Table of ontents Descriptive statistics include the numbers, tables, charts, and graphs used to describe, organize, summarize, and present raw data. Descriptive statistics are most
More informationChapter 3: Central Tendency
Chapter 3: Central Tendency Central Tendency In general terms, central tendency is a statistical measure that determines a single value that accurately describes the center of the distribution and represents
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 informationOrganizing & Graphing Data
AGSC 320 Statistical Methods Organizing & Graphing Data 1 DATA Numerical representation of reality Raw data: Data recorded in the sequence in which they are collected and before any processing Qualitative
More informationSection 1.3 Exercises (Solutions)
Section 1.3 Exercises (s) 1.109, 1.110, 1.111, 1.114*, 1.115, 1.119*, 1.122, 1.125, 1.127*, 1.128*, 1.131*, 1.133*, 1.135*, 1.137*, 1.139*, 1.145*, 1.146148. 1.109 Sketch some normal curves. (a) Sketch
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 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 informationMethods for Describing Data Sets
1 Methods for Describing Data Sets.1 Describing Data Graphically In this section, we will work on organizing data into a special table called a frequency table. First, we will classify the data into categories.
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 information9 Descriptive and Multivariate Statistics
9 Descriptive and Multivariate Statistics Jamie Price Donald W. Chamberlayne * S tatistics is the science of collecting and organizing data and then drawing conclusions based on data. There are essentially
More informationThe Normal Distribution
Chapter 6 The Normal Distribution 6.1 The Normal Distribution 1 6.1.1 Student Learning Objectives By the end of this chapter, the student should be able to: Recognize the normal probability distribution
More informationDescriptive Statistics
Y520 Robert S Michael Goal: Learn to calculate indicators and construct graphs that summarize and describe a large quantity of values. Using the textbook readings and other resources listed on the web
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 informationCentral Tendency and Variation
Contents 5 Central Tendency and Variation 161 5.1 Introduction............................ 161 5.2 The Mode............................. 163 5.2.1 Mode for Ungrouped Data................ 163 5.2.2 Mode
More informationLecture 1: Review and Exploratory Data Analysis (EDA)
Lecture 1: Review and Exploratory Data Analysis (EDA) Sandy Eckel seckel@jhsph.edu Department of Biostatistics, The Johns Hopkins University, Baltimore USA 21 April 2008 1 / 40 Course Information I Course
More information2. A is a subset of the population. 3. Construct a frequency distribution for the data of the grades of 25 students taking Math 11 last
Math 111 Chapter 12 Practice Test 1. If I wanted to survey 50 Cabrini College students about where they prefer to eat on campus, which would be the most appropriate way to conduct my survey? a. Find 50
More informationFootball Player Weight Analysis Computer Lab Canon City High School vs. Pueblo County High School. Mark Heinen September 20, 2014
Football Player Weight Analysis Computer Lab Canon City High School vs. Pueblo County High School Mark Heinen September 20, 2014 Table of Contents I. Problem Statement.. Page 3 II. Solution Technique..
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 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 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 informationStats Review Chapters 34
Stats Review Chapters 34 Created by Teri Johnson Math Coordinator, Mary Stangler Center for Academic Success Examples are taken from Statistics 4 E by Michael Sullivan, III And the corresponding Test
More informationSession 1.6 Measures of Central Tendency
Session 1.6 Measures of Central Tendency Measures of location (Indices of central tendency) These indices locate the center of the frequency distribution curve. The mode, median, and mean are three indices
More informationUsing SPSS, Chapter 2: Descriptive Statistics
1 Using SPSS, Chapter 2: Descriptive Statistics Chapters 2.1 & 2.2 Descriptive Statistics 2 Mean, Standard Deviation, Variance, Range, Minimum, Maximum 2 Mean, Median, Mode, Standard Deviation, Variance,
More informationConstructing and Interpreting Confidence Intervals
Constructing and Interpreting Confidence Intervals Confidence Intervals In this power point, you will learn: Why confidence intervals are important in evaluation research How to interpret a confidence
More informationMBA 611 STATISTICS AND QUANTITATIVE METHODS
MBA 611 STATISTICS AND QUANTITATIVE METHODS Part I. Review of Basic Statistics (Chapters 111) A. Introduction (Chapter 1) Uncertainty: Decisions are often based on incomplete information from uncertain
More information22 Frequency Distributions
22 Distributions 39 22 Distributions When working with large data sets, it is often helpful to organize and summarize the data by constructing a table that lists the different possible data values (either
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 informationSTAT 155 Introductory Statistics. Lecture 5: Density Curves and Normal Distributions (I)
The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL STAT 155 Introductory Statistics Lecture 5: Density Curves and Normal Distributions (I) 9/12/06 Lecture 5 1 A problem about Standard Deviation A variable
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 informationEach exam covers lectures from since the previous exam and up to the exam date.
Sociology 301 Exam Review Liying Luo 03.22 Exam Review: Logistics Exams must be taken at the scheduled date and time unless 1. You provide verifiable documents of unforeseen illness or family emergency,
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 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 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 informationQuantitative Data Analysis: Choosing a statistical test Prepared by the Office of Planning, Assessment, Research and Quality
Quantitative Data Analysis: Choosing a statistical test Prepared by the Office of Planning, Assessment, Research and Quality 1 To help choose which type of quantitative data analysis to use either before
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 informationAP * Statistics Review. Descriptive Statistics
AP * Statistics Review Descriptive Statistics Teacher Packet Advanced Placement and AP are registered trademark of the College Entrance Examination Board. The College Board was not involved in the production
More information18.2. STATISTICS 2 (Measures of central tendency) A.J.Hobson
JUST THE MATHS SLIDES NUMBER 18.2 STATISTICS 2 (Measures of central tendency) by A.J.Hobson 18.2.1 Introduction 18.2.2 The arithmetic mean (by coding) 18.2.3 The median 18.2.4 The mode 18.2.5 Quantiles
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 informationIntroduction to Statistics for Psychology. Quantitative Methods for Human Sciences
Introduction to Statistics for Psychology and Quantitative Methods for Human Sciences Jonathan Marchini Course Information There is website devoted to the course at http://www.stats.ox.ac.uk/ marchini/phs.html
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 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 informationResearch Variables. Measurement. Scales of Measurement. Chapter 4: Data & the Nature of Measurement
Chapter 4: Data & the Nature of Graziano, Raulin. Research Methods, a Process of Inquiry Presented by Dustin Adams Research Variables Variable Any characteristic that can take more than one form or value.
More informationNominal Scaling. Measures of Central Tendency, Spread, and Shape. Interval Scaling. Ordinal Scaling
Nominal Scaling Measures of, Spread, and Shape Dr. J. Kyle Roberts Southern Methodist University Simmons School of Education and Human Development Department of Teaching and Learning The lowest level of
More informationChapter 2: Frequency Distributions and Graphs (or making pretty tables and pretty pictures)
Chapter 2: Frequency Distributions and Graphs (or making pretty tables and pretty pictures) Example: Titanic passenger data is available for 1310 individuals for 14 variables, though not all variables
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 informationIntroduction to Environmental Statistics. The Big Picture. Populations and Samples. Sample Data. Examples of sample data
A Few Sources for Data Examples Used Introduction to Environmental Statistics Professor Jessica Utts University of California, Irvine jutts@uci.edu 1. Statistical Methods in Water Resources by D.R. Helsel
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 informationChapter 7 What to do when you have the data
Chapter 7 What to do when you have the data We saw in the previous chapters how to collect data. We will spend the rest of this course looking at how to analyse the data that we have collected. Stem and
More informationCHOSUN UNIVERSITY SEOKGANG,PARK CHAPTER 2 SECTION 1: GRAPHICAL AND TABULAR DESCRIPTIVE TECHNIQUES
CHAPTER 2 SECTION 1: GRAPHICAL AND TABULAR DESCRIPTIVE TECHNIQUES MULTIPLE CHOICE 1. The classification of student major (accounting, economics, management, marketing, other) is an example of a(n) a. nominal
More informationChapter 3. The Normal Distribution
Chapter 3. The Normal Distribution Topics covered in this chapter: Zscores Normal Probabilities Normal Percentiles Zscores Example 3.6: The standard normal table The Problem: What proportion of observations
More informationChapter 3 Central Tendency
Chapter 3 Central Tendency PowerPoint Lecture Slides Essentials of Statistics for the Behavioral Sciences Seventh Edition by Frederick J Gravetter and Larry B. Wallnau Learning Outcomes 1 2 3 4 5 6 Understand
More informationTable 21. Sucrose concentration (% fresh wt.) of 100 sugar beet roots. Beet No. % Sucrose. Beet No.
Chapter 2. DATA EXPLORATION AND SUMMARIZATION 2.1 Frequency Distributions Commonly, people refer to a population as the number of individuals in a city or county, for example, all the people in California.
More informationMathematical goals. Starting points. Materials required. Time needed
Level S6 of challenge: B/C S6 Interpreting frequency graphs, cumulative cumulative frequency frequency graphs, graphs, box and box whisker and plots whisker plots Mathematical goals Starting points Materials
More informationAP Statistics Chapter 1 Test  Multiple Choice
AP Statistics Chapter 1 Test  Multiple Choice Name: 1. The following bar graph gives the percent of owners of three brands of trucks who are satisfied with their truck. From this graph, we may conclude
More information! x sum of the entries
3.1 Measures of Central Tendency (Page 1 of 16) 3.1 Measures of Central Tendency Mean, Median and Mode! x sum of the entries a. mean, x = = n number of entries Example 1 Find the mean of 26, 18, 12, 31,
More informationEXAM #1 (Example) Instructor: Ela Jackiewicz. Relax and good luck!
STP 231 EXAM #1 (Example) Instructor: Ela Jackiewicz Honor Statement: I have neither given nor received information regarding this exam, and I will not do so until all exams have been graded and returned.
More informationCHAPTER 5 PERCENTILES AND PERCENTILE RANKS
CHAPTER 5 PERCENTILES AND PERCENTILE RANKS Percentiles and percentile ranks are frequently used as indicators of performance in bo e academic and corporate worlds. Percentiles and percentile ranks provide
More informationStatistics Revision Sheet Question 6 of Paper 2
Statistics Revision Sheet Question 6 of Paper The Statistics question is concerned mainly with the following terms. The Mean and the Median and are two ways of measuring the average. sumof values no. of
More informationData Analysis: Displaying Data  Graphs
Accountability Modules WHAT IT IS Return to Table of Contents WHEN TO USE IT TYPES OF GRAPHS Bar Graphs Data Analysis: Displaying Data  Graphs Graphs are pictorial representations of the relationships
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 information