Save this PDF as:

Size: px
Start display at page:

## Transcription

1 There are three kinds of people in the world those who are good at math and those who are not. PSY 511: Advanced Statistics for Psychological and Behavioral Research 1 Positive Views The record of a month s roulette playing at Monte Carlo can afford us material for discussing the foundations of knowledge. --Karl Pearson Not-so-positive views I know too well that these arguments from probabilities are imposters, and unless great caution is observed in the use of them, they are apt to be deceptive. --Plato There are three kinds of lies: lies, damned lies, and statistics. --Benjamin Disraeli (British Prime Minister) popularized by Mark Twain Statistics: a set of mathematical procedures for summarizing and interpreting observations Allows us to find order in apparent chaos Data: observations made about the environment Numbers that we wish to understand and summarize Descriptive Statistics: a branch of statistics used to summarize or describe a set of observations a branch of statistics used to interpret or draw inferences about a set of observations 1

2 Why does measurement matter in statistics? Statistics deal only with numbers, and thus, we must understand what these numbers actually represent Statistics Data (numbers/measurements) Knowledge (inferences made from data about underlying processes using probability) Measurement: the application of any rule by which numbers are assigned to cases in order to represent the presence/absence or quantity of some attribute possessed by each case Nominal: a set of mutually exclusive categories according to their characteristics -each is assigned an arbitrary numerical code which conveys qualitative information -IDENTITY -ex. gender, species, political party, religious affiliation Ordinal: reflects the ordering of cases on the attribute being measured -gives a rough indication of qualitative differences -equal score differences DO NOT necessarily reflect equal differences in the amount of the attribute being measured -IDENTITY & ORDER -ex. finishing positions in a race (e.g., 1st & 2nd) & class rank 2

3 Interval: equal score differences DO reflect equal differences in the amount of the attribute being measured -scores reflect the number of fixed-sized units of the attribute possessed by each case -positioning of the zero-point is entirely arbitrary a score of zero does NOT mean the case possesses none of the attribute which means it is NOT possible to say how many times higher one score is than another -IDENTITY, ORDER, & EQUAL DISTANCE -ex. IQ, SAT score, Celsius scale & Fahrenheit scale Ratio: possesses all the characteristics of interval scale but has a non-arbitrary zeropoint. Thus, a case scored as zero on a ratio scale possesses none of the attribute being measured -IDENTITY, ORDER, EQUAL DISTANCE, & TRUE ZERO POINT -ex. age, volume, Kelvin temperature scale Many of the most commonly used statistical methods (e.g., t-test, ANOVA, correlation, regression) assume that data are measured at least on an interval scale Some nonparametric methods can be used for data measured on an ordinal scale or even a nominal scale (e.g., chi-square test) 3

4 Central Tendency: refers to the "middle" value or most typical value Measures include the mean, median, and mode Dispersion (or Variability): describes the spread or clustering of a set of data Measures include the variance, standard deviation, and range Rectangular Distribution Normal Distribution Bimodal Distribution 4

5 Population Target group for inference Examples (all women, all 4 th graders, & everyone who has experienced emotional maltreatment) Parameter: numerical characteristic of population. Example: population mean is µ (mu). Sample Subgroup of the population Examples (women in this class, 4 th graders at a local elementary school, & USM students who report emotional maltreatment during mass testing) Statistic: numerical characteristic of sample. Example: sample mean is (X-bar). POPULATION: All of the individuals of interest The results from the sample are generalized to the population The sample is selected from the population SAMPLE: The individuals selected to participate in the research study Sampling: Process of selecting the sample from the population Random sampling: Independent selection As contrasted to evenness Descriptive vs. Inferential Statistics Descriptive: primary purpose is to describe some aspect of the data Inferential: primary purpose is to infer (to estimate or to make a decision, test a hypothesis) Sample Infer Population Statistic Infer Parameter 5

6 Population Parameters Sample Statistics Mean µ Variance σ 2 s 2, s* 2 Standard Deviation σ s, s* Correlation ρ r All inferential statistics have the following in common: Use of some descriptive statistic Use of probability Potential for estimation Sampling variability Sampling distributions Use of a theoretical distribution Two hypotheses, two decisions, & two types of error Use of Some Descriptive Statistic Video Delay of gratification (Walter Mischel) Results: EI 517s, EN 365s, OI 585s, ON 590s The sample mean, a descriptive statistic, has value 365 for group EN Coping Ideas Ideas None Rewards Exposed Obscured

7 Use of Probability Coin toss example Fair coin? p(head)=.5 What if I toss the coin 10 times and get 10 heads? p(10 H fair coin)=1/1024 = Reject hypothesis of fair coin What if I toss the coin 10 times and get 6 heads? p(6 or more H fair coin) =386/1024=.377 Retain hypothesis of fair coin Potential for Estimation The sample mean ( ) is a descriptive statistic that has the value 365 for group EN and it is an estimate of the population mean (µ) which is a population parameter for population EN. Coping Ideas Ideas None Rewards Exposed Obscured Sampling Variability and Sampling Distributions If we ran the delay of gratification study again, we probably would not get exactly 365 for the mean of the EN group Sampling Distribution of The value of the new mean might be close, like 355 A third study might yield 375, etc. Sampling distribution is a distribution of statistics rather than scores 1,000 Samples 7

8 Use of a Theoretical Distribution Normal Distribution Two Hypotheses, Two Decisions, and Two Types of Error Two hypotheses Coin is fair OR coin is not fair Kids in the EN group score lower OR they do not Null Hypothesis (H 0 ) Alternative Hypothesis (H 1 ) Two decisions Reject or retain the null hypothesis These decisions always concern the null hypothesis Two types of error Type I error: reject H 0 when H 0 is true Type II error: retain H 0 when H 0 if false (H 1 is true) All inferential statistics have the following in common: Use of some descriptive statistic Use of probability Potential for estimation Sampling variability Sampling distributions Use of a theoretical distribution Two hypotheses, two decisions, & two types of error 8

9 Null hypothesis significance testing begins with researchers assuming that their predictions are wrong Simple two-group experimental design would assume no real difference between control group and experimental group The null hypothesis is being tested Statistical significance focuses on the probability that a statistic of a particular magnitude would emerge by chance alone A statistically significant result is one that is extreme enough that it is unlikely to have occurred by chance alone A number of factors can influence whether results are statistically significant Greater effect size Higher alpha (α) level (willingness to mistakenly reject H 0 when H 0 is true [Type I error]) The more willing you are to risk making a Type I error, then the more likely you are to find statistical significance Decrease measurement error (e.g., use within-subject designs) Greater sample size Avoid restriction of range Use of directional hypotheses These have greater power than non-directional hypotheses if you are correct in predicting the direction of the effect Effect Size: an estimate of the magnitude or meaningfulness of an effect For example, Cohen s d is a measure of effect size that captures how different two means are in terms of their standard deviation Meta-Analysis: a set of statistical techniques that are used to summarize and evaluate entire sets of research These approaches analyze the results of studies rather than the responses of participants 9

### II. DISTRIBUTIONS distribution normal distribution. standard scores

Appendix D Basic Measurement And Statistics The following information was developed by Steven Rothke, PhD, Department of Psychology, Rehabilitation Institute of Chicago (RIC) and expanded by Mary F. Schmidt,

### Research 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.

### Descriptive Statistics

Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize

### Statistics Review PSY379

Statistics Review PSY379 Basic concepts Measurement scales Populations vs. samples Continuous vs. discrete variable Independent vs. dependent variable Descriptive vs. inferential stats Common analyses

### Variables and Data A variable contains data about anything we measure. For example; age or gender of the participants or their score on a test.

The Analysis of Research Data The design of any project will determine what sort of statistical tests you should perform on your data and how successful the data analysis will be. For example if you decide

### 1. Why the hell do we need statistics?

1. Why the hell do we need statistics? There are three kind of lies: lies, damned lies, and statistics, British Prime Minister Benjamin Disraeli (as credited by Mark Twain): It is easy to lie with statistics,

### DATA ANALYSIS. QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University

DATA ANALYSIS QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University Quantitative Research What is Statistics? Statistics (as a subject) is the science

### Inferential Statistics

Inferential Statistics Sampling and the normal distribution Z-scores Confidence levels and intervals Hypothesis testing Commonly used statistical methods Inferential Statistics Descriptive statistics are

### DATA COLLECTION AND ANALYSIS

DATA COLLECTION AND ANALYSIS Quality Education for Minorities (QEM) Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. August 23, 2013 Objectives of the Discussion 2 Discuss

### Basic Concepts in Research and Data Analysis

Basic Concepts in Research and Data Analysis Introduction: A Common Language for Researchers...2 Steps to Follow When Conducting Research...3 The Research Question... 3 The Hypothesis... 4 Defining the

### WHAT IS A JOURNAL CLUB?

WHAT IS A JOURNAL CLUB? With its September 2002 issue, the American Journal of Critical Care debuts a new feature, the AJCC Journal Club. Each issue of the journal will now feature an AJCC Journal Club

### Statistical basics for Biology: p s, alphas, and measurement scales.

334 Volume 25: Mini Workshops Statistical basics for Biology: p s, alphas, and measurement scales. Catherine Teare Ketter School of Marine Programs University of Georgia Athens Georgia 30602-3636 (706)

### Inferential Statistics. Probability. From Samples to Populations. Katie Rommel-Esham Education 504

Inferential Statistics Katie Rommel-Esham Education 504 Probability Probability is the scientific way of stating the degree of confidence we have in predicting something Tossing coins and rolling dice

### DESCRIPTIVE 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,

### Chapter 16 Multiple Choice Questions (The answers are provided after the last question.)

Chapter 16 Multiple Choice Questions (The answers are provided after the last question.) 1. Which of the following symbols represents a population parameter? a. SD b. σ c. r d. 0 2. If you drew all possible

### Hypothesis Testing & Data Analysis. Statistics. Descriptive Statistics. What is the difference between descriptive and inferential statistics?

2 Hypothesis Testing & Data Analysis 5 What is the difference between descriptive and inferential statistics? Statistics 8 Tools to help us understand our data. Makes a complicated mess simple to understand.

### Introduction to Statistics and Quantitative Research Methods

Introduction to Statistics and Quantitative Research Methods Purpose of Presentation To aid in the understanding of basic statistics, including terminology, common terms, and common statistical methods.

### Content 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

### Measurement & Data Analysis. On the importance of math & measurement. Steps Involved in Doing Scientific Research. Measurement

Measurement & Data Analysis Overview of Measurement. Variability & Measurement Error.. Descriptive vs. Inferential Statistics. Descriptive Statistics. Distributions. Standardized Scores. Graphing Data.

### Module 9: Nonparametric Tests. The Applied Research Center

Module 9: Nonparametric Tests The Applied Research Center Module 9 Overview } Nonparametric Tests } Parametric vs. Nonparametric Tests } Restrictions of Nonparametric Tests } One-Sample Chi-Square Test

### Outline of Topics. Statistical Methods I. Types of Data. Descriptive Statistics

Statistical Methods I Tamekia L. Jones, Ph.D. (tjones@cog.ufl.edu) Research Assistant Professor Children s Oncology Group Statistics & Data Center Department of Biostatistics Colleges of Medicine and Public

### Study Guide for the Final Exam

Study Guide for the Final Exam When studying, remember that the computational portion of the exam will only involve new material (covered after the second midterm), that material from Exam 1 will make

### Dr. Peter Tröger Hasso Plattner Institute, University of Potsdam. Software Profiling Seminar, Statistics 101

Dr. Peter Tröger Hasso Plattner Institute, University of Potsdam Software Profiling Seminar, 2013 Statistics 101 Descriptive Statistics Population Object Object Object Sample numerical description Object

### Tutorial 5: Hypothesis Testing

Tutorial 5: Hypothesis Testing Rob Nicholls nicholls@mrc-lmb.cam.ac.uk MRC LMB Statistics Course 2014 Contents 1 Introduction................................ 1 2 Testing distributional assumptions....................

### STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance

Principles of Statistics STA-201-TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis

### Introduction to Hypothesis Testing. Hypothesis Testing. Step 1: State the Hypotheses

Introduction to Hypothesis Testing 1 Hypothesis Testing A hypothesis test is a statistical procedure that uses sample data to evaluate a hypothesis about a population Hypothesis is stated in terms of the

### Introduction to Quantitative Methods

Introduction to Quantitative Methods October 15, 2009 Contents 1 Definition of Key Terms 2 2 Descriptive Statistics 3 2.1 Frequency Tables......................... 4 2.2 Measures of Central Tendencies.................

### Using Excel for inferential statistics

FACT SHEET Using Excel for inferential statistics Introduction When you collect data, you expect a certain amount of variation, just caused by chance. A wide variety of statistical tests can be applied

### Answer keys for Assignment 10: Measurement of study variables

Answer keys for Assignment 10: Measurement of study variables (The correct answer is underlined in bold text) 1. In a study, participants are asked to indicate the type of pet they have at home (ex: dog,

### Chapter 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

### Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association

Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association This information is adapted from and draws heavily on: Sheskin, David J. 2000. Handbook of Parametric and

### Chapter 1: The Nature of Probability and Statistics

Chapter 1: The Nature of Probability and Statistics Learning Objectives Upon successful completion of Chapter 1, you will have applicable knowledge of the following concepts: Statistics: An Overview and

### Tests of relationships between variables Chi-square Test Binomial Test Run Test for Randomness One-Sample Kolmogorov-Smirnov Test.

N. Uttam Singh, Aniruddha Roy & A. K. Tripathi ICAR Research Complex for NEH Region, Umiam, Meghalaya uttamba@gmail.com, aniruddhaubkv@gmail.com, aktripathi2020@yahoo.co.in Non Parametric Tests: Hands

### Elementary Statistics

Elementary Statistics Chapter 1 Dr. Ghamsary Page 1 Elementary Statistics M. Ghamsary, Ph.D. Chap 01 1 Elementary Statistics Chapter 1 Dr. Ghamsary Page 2 Statistics: Statistics is the science of collecting,

### Levels of measurement in psychological research:

Research Skills: Levels of Measurement. Graham Hole, February 2011 Page 1 Levels of measurement in psychological research: Psychology is a science. As such it generally involves objective measurement of

### Basic Statistical Concepts, Research Design, & Notation

, Research Design, & Notation Variables, Scores, & Data A variable is a characteristic or condition that can change or take on different values. Most research begins with a general question about the relationship

### EBM Cheat Sheet- Measurements Card

EBM Cheat Sheet- Measurements Card Basic terms: Prevalence = Number of existing cases of disease at a point in time / Total population. Notes: Numerator includes old and new cases Prevalence is cross-sectional

### Data 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

### Analysis of Data. Organizing Data Files in SPSS. Descriptive Statistics

Analysis of Data Claudia J. Stanny PSY 67 Research Design Organizing Data Files in SPSS All data for one subject entered on the same line Identification data Between-subjects manipulations: variable to

### Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind 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

### Research Design Concepts. Independent and dependent variables Data types Sampling Validity and reliability

Research Design Concepts Independent and dependent variables Data types Sampling Validity and reliability Research Design Action plan for carrying out research How the research will be conducted to investigate

### Descriptive Statistics and Measurement Scales

Descriptive Statistics 1 Descriptive Statistics and Measurement Scales Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample

### Correlational Research. Correlational Research. Stephen E. Brock, Ph.D., NCSP EDS 250. Descriptive Research 1. Correlational Research: Scatter Plots

Correlational Research Stephen E. Brock, Ph.D., NCSP California State University, Sacramento 1 Correlational Research A quantitative methodology used to determine whether, and to what degree, a relationship

### Hypothesis Testing. Chapter 7

Hypothesis Testing Chapter 7 Hypothesis Testing Time to make the educated guess after answering: What the population is, how to extract the sample, what characteristics to measure in the sample, After

### DDBA 8438: Introduction to Hypothesis Testing Video Podcast Transcript

DDBA 8438: Introduction to Hypothesis Testing Video Podcast Transcript JENNIFER ANN MORROW: Welcome to "Introduction to Hypothesis Testing." My name is Dr. Jennifer Ann Morrow. In today's demonstration,

### Statistical Foundations:

Statistical Foundations: Hypothesis Testing Psychology 790 Lecture #9 9/19/2006 Today sclass Hypothesis Testing. General terms and philosophy. Specific Examples Hypothesis Testing Rules of the NHST Game

### Section Format Day Begin End Building Rm# Instructor. 001 Lecture Tue 6:45 PM 8:40 PM Silver 401 Ballerini

NEW YORK UNIVERSITY ROBERT F. WAGNER GRADUATE SCHOOL OF PUBLIC SERVICE Course Syllabus Spring 2016 Statistical Methods for Public, Nonprofit, and Health Management Section Format Day Begin End Building

### CHAPTER 11 CHI-SQUARE: NON-PARAMETRIC COMPARISONS OF FREQUENCY

CHAPTER 11 CHI-SQUARE: NON-PARAMETRIC COMPARISONS OF FREQUENCY The hypothesis testing statistics detailed thus far in this text have all been designed to allow comparison of the means of two or more samples

### TABLE OF CONTENTS. About Chi Squares... 1. What is a CHI SQUARE?... 1. Chi Squares... 1. Hypothesis Testing with Chi Squares... 2

About Chi Squares TABLE OF CONTENTS About Chi Squares... 1 What is a CHI SQUARE?... 1 Chi Squares... 1 Goodness of fit test (One-way χ 2 )... 1 Test of Independence (Two-way χ 2 )... 2 Hypothesis Testing

### Foundation of Quantitative Data Analysis

Foundation of Quantitative Data Analysis Part 1: Data manipulation and descriptive statistics with SPSS/Excel HSRS #10 - October 17, 2013 Reference : A. Aczel, Complete Business Statistics. Chapters 1

### Nonparametric Statistics

1 14.1 Using the Binomial Table Nonparametric Statistics In this chapter, we will survey several methods of inference from Nonparametric Statistics. These methods will introduce us to several new tables

### Lecture 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

### Biodiversity Data Analysis: Testing Statistical Hypotheses By Joanna Weremijewicz, Simeon Yurek, Steven Green, Ph. D. and Dana Krempels, Ph. D.

Biodiversity Data Analysis: Testing Statistical Hypotheses By Joanna Weremijewicz, Simeon Yurek, Steven Green, Ph. D. and Dana Krempels, Ph. D. In biological science, investigators often collect biological

### Measures of Central Tendency

Measures of Central Tendency TABLE OF CONTENTS Measures of Central Tendency... 1 What are MEASURES OF CENTRAL TENDENCY?... 1 Measures of Central Tendency... 1 Measures of Central Tendency... 1 Mode...

### fifty Fathoms Statistics Demonstrations for Deeper Understanding Tim Erickson

fifty Fathoms Statistics Demonstrations for Deeper Understanding Tim Erickson Contents What Are These Demos About? How to Use These Demos If This Is Your First Time Using Fathom Tutorial: An Extended Example

### Statistics. Measurement. Scales of Measurement 7/18/2012

Statistics Measurement Measurement is defined as a set of rules for assigning numbers to represent objects, traits, attributes, or behaviors A variableis something that varies (eye color), a constant does

### 4.1 Exploratory Analysis: Once the data is collected and entered, the first question is: "What do the data look like?"

Data Analysis Plan The appropriate methods of data analysis are determined by your data types and variables of interest, the actual distribution of the variables, and the number of cases. Different analyses

### Develop hypothesis and then research to find out if it is true. Derived from theory or primary question/research questions

Chapter 12 Hypothesis Testing Learning Objectives Examine the process of hypothesis testing Evaluate research and null hypothesis Determine one- or two-tailed tests Understand obtained values, significance,

### Biostatistics: Types of Data Analysis

Biostatistics: Types of Data Analysis Theresa A Scott, MS Vanderbilt University Department of Biostatistics theresa.scott@vanderbilt.edu http://biostat.mc.vanderbilt.edu/theresascott Theresa A Scott, MS

### Quantitative 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

### Statistics and research

Statistics and research Usaneya Perngparn Chitlada Areesantichai Drug Dependence Research Center (WHOCC for Research and Training in Drug Dependence) College of Public Health Sciences Chulolongkorn University,

### Module 10: Data Analysis and Interpretation

IPDET Module 10: Data Analysis and Interpretation Intervention or Policy Subevaluations Qualitative vs. Quantitative Qualitative Quantitative Introduction Data Analysis Strategy Analyzing Qualitative Data

About Hypothesis Testing TABLE OF CONTENTS About Hypothesis Testing... 1 What is a HYPOTHESIS TEST?... 1 Hypothesis Testing... 1 Hypothesis Testing... 1 Steps in Hypothesis Testing... 2 Steps in Hypothesis

### THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013

THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING 1 COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS Fall 2013 & Danice B. Greer, Ph.D., RN, BC dgreer@uttyler.edu Office BRB 1115 (903) 565-5766

### Homework 3. Part 1. Name: Score: / null

Name: Score: / Homework 3 Part 1 null 1 For the following sample of scores, the standard deviation is. Scores: 7, 2, 4, 6, 4, 7, 3, 7 Answer Key: 2 2 For any set of data, the sum of the deviation scores

### Business 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, McGraw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Required Computing

### Simple Linear Regression Inference

Simple Linear Regression Inference 1 Inference requirements The Normality assumption of the stochastic term e is needed for inference even if it is not a OLS requirement. Therefore we have: Interpretation

### THE KRUSKAL WALLLIS TEST

THE KRUSKAL WALLLIS TEST TEODORA H. MEHOTCHEVA Wednesday, 23 rd April 08 THE KRUSKAL-WALLIS TEST: The non-parametric alternative to ANOVA: testing for difference between several independent groups 2 NON

### Central 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

### This chapter discusses some of the basic concepts in inferential statistics.

Research Skills for Psychology Majors: Everything You Need to Know to Get Started Inferential Statistics: Basic Concepts This chapter discusses some of the basic concepts in inferential statistics. Details

### Mathematics within the Psychology Curriculum

Mathematics within the Psychology Curriculum Statistical Theory and Data Handling Statistical theory and data handling as studied on the GCSE Mathematics syllabus You may have learnt about statistics and

### Homework #3 is due Friday by 5pm. Homework #4 will be posted to the class website later this week. It will be due Friday, March 7 th, at 5pm.

Homework #3 is due Friday by 5pm. Homework #4 will be posted to the class website later this week. It will be due Friday, March 7 th, at 5pm. Political Science 15 Lecture 12: Hypothesis Testing Sampling

### Mathematics. 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

### UNDERSTANDING THE DEPENDENT-SAMPLES t TEST

UNDERSTANDING THE DEPENDENT-SAMPLES t TEST A dependent-samples t test (a.k.a. matched or paired-samples, matched-pairs, samples, or subjects, simple repeated-measures or within-groups, or correlated groups)

### SAMPLING & INFERENTIAL STATISTICS. Sampling is necessary to make inferences about a population.

SAMPLING & INFERENTIAL STATISTICS Sampling is necessary to make inferences about a population. SAMPLING The group that you observe or collect data from is the sample. The group that you make generalizations

### Introduction to Statistics

1 Introduction to Statistics LEARNING OBJECTIVES After reading this chapter, you should be able to: 1. Distinguish between descriptive and inferential statistics. 2. Explain how samples and populations,

### Session 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

### SOCIOLOGY 7702 FALL, 2014 INTRODUCTION TO STATISTICS AND DATA ANALYSIS

SOCIOLOGY 7702 FALL, 2014 INTRODUCTION TO STATISTICS AND DATA ANALYSIS Professor Michael A. Malec Mailbox is in McGuinn 426 Office: McGuinn 427 Phone: 617-552-4131 Office Hours: TBA E-mail: malec@bc.edu

### Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013

Statistics I for QBIC Text Book: Biostatistics, 10 th edition, by Daniel & Cross Contents and Objectives Chapters 1 7 Revised: August 2013 Chapter 1: Nature of Statistics (sections 1.1-1.6) Objectives

### Research Methods & Experimental Design

Research Methods & Experimental Design 16.422 Human Supervisory Control April 2004 Research Methods Qualitative vs. quantitative Understanding the relationship between objectives (research question) and

### Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization. Learning Goals. GENOME 560, Spring 2012

Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization GENOME 560, Spring 2012 Data are interesting because they help us understand the world Genomics: Massive Amounts

### Chapter 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

### Statistical Foundations:

Statistical Foundations: Hypothesis Testing Psychology 790 Lecture #10 9/26/2006 Today sclass Hypothesis Testing. An Example. Types of errors illustrated. Misconceptions about hypothesis testing. Upcoming

### CHAPTER 12 TESTING DIFFERENCES WITH ORDINAL DATA: MANN WHITNEY U

CHAPTER 12 TESTING DIFFERENCES WITH ORDINAL DATA: MANN WHITNEY U Previous chapters of this text have explained the procedures used to test hypotheses using interval data (t-tests and ANOVA s) and nominal

### Name: Date: Use the following to answer questions 3-4:

Name: Date: 1. Determine whether each of the following statements is true or false. A) The margin of error for a 95% confidence interval for the mean increases as the sample size increases. B) The margin

### How to Conduct a Hypothesis Test

How to Conduct a Hypothesis Test The idea of hypothesis testing is relatively straightforward. In various studies we observe certain events. We must ask, is the event due to chance alone, or is there some

### Introduction to Statistics for Computer Science Projects

Introduction Introduction to Statistics for Computer Science Projects Peter Coxhead Whole modules are devoted to statistics and related topics in many degree programmes, so in this short session all I

### DESCRIPTIVE 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

### Testing Group Differences using T-tests, ANOVA, and Nonparametric Measures

Testing Group Differences using T-tests, ANOVA, and Nonparametric Measures Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone:

### What is Statistics? Statistics is about Collecting data Organizing data Analyzing data Presenting data

Introduction What is Statistics? Statistics is about Collecting data Organizing data Analyzing data Presenting data What is Statistics? Statistics is divided into two areas: descriptive statistics and

### research/scientific includes the following: statistical hypotheses: you have a null and alternative you accept one and reject the other

1 Hypothesis Testing Richard S. Balkin, Ph.D., LPC-S, NCC 2 Overview When we have questions about the effect of a treatment or intervention or wish to compare groups, we use hypothesis testing Parametric

### Guided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity.

Guided Reading Educational Research: Competencies for Analysis and Applications 9th Edition EDFS 635: Educational Research Chapter 1: Introduction to Educational Research 1. List and briefly describe the

### Sample Size Determination

Sample Size Determination Population A: 10,000 Population B: 5,000 Sample 10% Sample 15% Sample size 1000 Sample size 750 The process of obtaining information from a subset (sample) of a larger group (population)

### Topic #1: Introduction to measurement and statistics

Topic #1: Introduction to measurement and statistics "Statistics can be fun or at least they don't need to be feared." Many folks have trouble believing this premise. Often, individuals walk into their

### Analysis and Interpretation of Clinical Trials. How to conclude?

www.eurordis.org Analysis and Interpretation of Clinical Trials How to conclude? Statistical Issues Dr Ferran Torres Unitat de Suport en Estadística i Metodología - USEM Statistics and Methodology Support

### STATISTICS FOR PSYCHOLOGISTS

STATISTICS FOR PSYCHOLOGISTS SECTION: STATISTICAL METHODS CHAPTER: REPORTING STATISTICS Abstract: This chapter describes basic rules for presenting statistical results in APA style. All rules come from

### Statistics for Management II-STAT 362-Final Review

Statistics for Management II-STAT 362-Final Review Multiple Choice Identify the letter of the choice that best completes the statement or answers the question. 1. The ability of an interval estimate to