Validity and Reliability. Edgar Degas: Portraits in a New Orleans Cotton Office, 1873
|
|
|
- Tiffany Knight
- 7 years ago
- Views:
Transcription
1 Validity and Reliability Edgar Degas: Portraits in a New Orleans Cotton Office, 1873
2 Validity and Reliability A more complete explanation of validity and reliability is provided at the accompanying web page for this topic. See: Validity and Reliability
3 Validity and Reliability 1. Validity The extent to which a test measures what it is supposed to measure. Non-empirical evaluations. Empirical evaluations. 2. Reliability The extent to which a test provides consistent measurement. Negatively affected by measurement error.
4 Validity and Reliability 3. Importance Without validity and reliability one cannot test an hypothesis. Without hypothesis testing, one cannot support a theory. Without a supported theory one cannot explain why events occur. Without adequate explanation one cannot develop effective material and non-material technologies, including programs designed for positive social change.
5 Validity 1. Non-Empirical Validity Does the concept seem to measure what it is supposed to measure? This evaluation depends entirely upon the intersubjective opinion of the community of scholars. It is not entirely subjective because it represents the consensus opinion of many subjective individual opinions.
6 Validity 2. Empirical Data analysis evaluation of validity. Does the concept predict another concept that it is supposed to predict? This evaluation depends upon empirical evaluation, using either quantitative or qualitative data. Empirical validity does not imply content validity.
7 Validity 3. Outcomes of Content Validity Assessment If the community of scholars approves the content validity of a measure, then it is accepted for further use. If the community of scholars rejects the content validity of a measure, then it must be redesigned by the researcher(s).
8 Validity 4. Outcomes of Empirical Validity Assessment Assessments of construct validity imply three types of hypotheses: 1. Do the items used to measure the construct have a statistically significant correlation with the construct? [Construct Validity] 2. Does the construct have a statistically significant correlation with related constructs? [Concurrent Validity] 3. Does the construct statistically predict another construct? [Predictive Validity]
9 Validity 5. Outcomes of Empirical Validity Assessment If the null hypotheses are rejected, then the empirical results lend support for the empirical validity of the measure. If one or more null hypotheses are not rejected, then: 1. The measure of the construct might be invalid. 2. The measure of the predicted construct might be invalid. 3. The theory linking the two constructs might be flawed.
10 Reliability 1. Measurement Error Measurement errors are random events that distort the true measurement of a concept. The average of all measurement errors is equal to zero. The distribution of measurement error is incorporated within the standard error. This distribution has the form of a bell-shaped curve, identical to the distribution of the standard deviation about a mean.
11 Reliability 2. Measurement Error and Hypothesis Testing With a small standard error, even a weak relationship between the independent and dependent variables can be judged as statistically significant. With a large standard error, even a strong relationship between the independent and dependent variables can be judged as not statistically significant. Therefore, it is important to reduce measurement error as much as possible.
12 Reliability 3. Achieving Reliability Concepts must be defined as precisely as possible. Researchers must develop good indicators of these concepts. This task sometimes requires much work and time to create a valid and reliable measuring instrument. Data must be collected with as much care as possible.
13 Reliability 4. Assessing Reliability Test-Retest Procedure. Advantages: Intuitive appeal. Disadvantages: History, Maturation, Cueing. Alternative Forms Procedure. Advantages: Little cueing. Disadvantages: History, Maturation.
14 Reliability 4. Assessing Reliability (Continued) Split-Halves Procedure. Advantages: No History, Maturation, or Cueing. Disadvantages: Different splits yield different assessments of reliability. Internal Consistency Procedure. Advantages: No History, Maturation, or Cueing. Disadvantages: Number of items can affect assessment of reliability.
15 Errors that Affect Validity and Reliability 1. Measurement Error Random, but can be reduced with care. 2. Sampling Error Errors in selecting a sample for study. 3. Random Error Things that are unknown, unanticipated, uncontrollable. 4. Data Analysis Errors Type-I: False assumption of causality. Type-II: False assumption of no causality.
16 Questions?
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
Pearson's Correlation Tests
Chapter 800 Pearson's Correlation Tests Introduction The correlation coefficient, ρ (rho), is a popular statistic for describing the strength of the relationship between two variables. The correlation
Sample Size and Power in Clinical Trials
Sample Size and Power in Clinical Trials Version 1.0 May 011 1. Power of a Test. Factors affecting Power 3. Required Sample Size RELATED ISSUES 1. Effect Size. Test Statistics 3. Variation 4. Significance
Non-Inferiority Tests for One Mean
Chapter 45 Non-Inferiority ests for One Mean Introduction his module computes power and sample size for non-inferiority tests in one-sample designs in which the outcome is distributed as a normal random
1.5 Oneway Analysis of Variance
Statistics: Rosie Cornish. 200. 1.5 Oneway Analysis of Variance 1 Introduction Oneway analysis of variance (ANOVA) is used to compare several means. This method is often used in scientific or medical experiments
Unit 26 Estimation with Confidence Intervals
Unit 26 Estimation with Confidence Intervals Objectives: To see how confidence intervals are used to estimate a population proportion, a population mean, a difference in population proportions, or a difference
Forward Contracts and Forward Rates
Forward Contracts and Forward Rates Outline and Readings Outline Forward Contracts Forward Prices Forward Rates Information in Forward Rates Reading Veronesi, Chapters 5 and 7 Tuckman, Chapters 2 and 16
BA 275 Review Problems - Week 6 (10/30/06-11/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394-398, 404-408, 410-420
BA 275 Review Problems - Week 6 (10/30/06-11/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394-398, 404-408, 410-420 1. Which of the following will increase the value of the power in a statistical test
Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression
Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Objectives: To perform a hypothesis test concerning the slope of a least squares line To recognize that testing for a
Non-Parametric Tests (I)
Lecture 5: Non-Parametric Tests (I) KimHuat LIM lim@stats.ox.ac.uk http://www.stats.ox.ac.uk/~lim/teaching.html Slide 1 5.1 Outline (i) Overview of Distribution-Free Tests (ii) Median Test for Two Independent
Lecture Notes Module 1
Lecture Notes Module 1 Study Populations A study population is a clearly defined collection of people, animals, plants, or objects. In psychological research, a study population usually consists of a specific
MULTIPLE REGRESSION AND ISSUES IN REGRESSION ANALYSIS
MULTIPLE REGRESSION AND ISSUES IN REGRESSION ANALYSIS MSR = Mean Regression Sum of Squares MSE = Mean Squared Error RSS = Regression Sum of Squares SSE = Sum of Squared Errors/Residuals α = Level of Significance
Point Biserial Correlation Tests
Chapter 807 Point Biserial Correlation Tests Introduction The point biserial correlation coefficient (ρ in this chapter) is the product-moment correlation calculated between a continuous random variable
A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
CHAPTER 5. A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING 5.1 Concepts When a number of animals or plots are exposed to a certain treatment, we usually estimate the effect of the treatment
Non Parametric Inference
Maura Department of Economics and Finance Università Tor Vergata Outline 1 2 3 Inverse distribution function Theorem: Let U be a uniform random variable on (0, 1). Let X be a continuous random variable
RESEARCH METHODS IN I/O PSYCHOLOGY
RESEARCH METHODS IN I/O PSYCHOLOGY Objectives Understand Empirical Research Cycle Knowledge of Research Methods Conceptual Understanding of Basic Statistics PSYC 353 11A rsch methods 01/17/11 [Arthur]
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,
Non-Inferiority Tests for Two Means using Differences
Chapter 450 on-inferiority Tests for Two Means using Differences Introduction This procedure computes power and sample size for non-inferiority tests in two-sample designs in which the outcome is a continuous
STEPS IN SCIENTIFIC RESEARCH:
STEPS IN SCIENTIFIC RESEARCH: ARCHITECTURAL RESEARCH: AN INTERDISCIPLINARY REALITY Hypothesis is a tentative explanation that accounts for a set of facts and can be tested by further investigation. Generation
1 von 91 RMS WiSe 2014/15/Academic Working/Seiten/Startseite
1 von 91 RMS WiSe 2014/15/Academic Working/Seiten/Startseite 2 von 91 RMS WiSe 2014/15/Academic Working/Seiten/Abstract 3 von 91 RMS WiSe 2014/15/Academic Working/Seiten/LernBar 4 von 91 RMS WiSe 2014/15/Academic
RESEARCH METHODS IN I/O PSYCHOLOGY
RESEARCH METHODS IN I/O PSYCHOLOGY Objectives Understand Empirical Research Cycle Knowledge of Research Methods Conceptual Understanding of Basic Statistics PSYC 353 11A rsch methods 09/01/11 [Arthur]
Association Between Variables
Contents 11 Association Between Variables 767 11.1 Introduction............................ 767 11.1.1 Measure of Association................. 768 11.1.2 Chapter Summary.................... 769 11.2 Chi
HYPOTHESIS TESTING WITH SPSS:
HYPOTHESIS TESTING WITH SPSS: A NON-STATISTICIAN S GUIDE & TUTORIAL by Dr. Jim Mirabella SPSS 14.0 screenshots reprinted with permission from SPSS Inc. Published June 2006 Copyright Dr. Jim Mirabella CHAPTER
Randomized Block Analysis of Variance
Chapter 565 Randomized Block Analysis of Variance Introduction This module analyzes a randomized block analysis of variance with up to two treatment factors and their interaction. It provides tables of
E10: Controlled Experiments
E10: Controlled Experiments Quantitative, empirical method Used to identify the cause of a situation or set of events X is responsible for Y Directly manipulate and control variables Correlation does not
Roadmap to Data Analysis. Introduction to the Series, and I. Introduction to Statistical Thinking-A (Very) Short Introductory Course for Agencies
Roadmap to Data Analysis Introduction to the Series, and I. Introduction to Statistical Thinking-A (Very) Short Introductory Course for Agencies Objectives of the Series Roadmap to Data Analysis Provide
STUDENT THESIS PROPOSAL GUIDELINES
STUDENT THESIS PROPOSAL GUIDELINES Thesis Proposal Students must work closely with their advisor to develop the proposal. Proposal Form The research proposal is expected to be completed during the normal
HYPOTHESIS TESTING: POWER OF THE TEST
HYPOTHESIS TESTING: POWER OF THE TEST The first 6 steps of the 9-step test of hypothesis are called "the test". These steps are not dependent on the observed data values. When planning a research project,
Why Use Net Present Value? The Payback Period Method The Discounted Payback Period Method The Average Accounting Return Method The Internal Rate of
1 Why Use Net Present Value? The Payback Period Method The Discounted Payback Period Method The Average Accounting Return Method The Internal Rate of Return Problems with the IRR Approach The Profitability
General Method: Difference of Means. 3. Calculate df: either Welch-Satterthwaite formula or simpler df = min(n 1, n 2 ) 1.
General Method: Difference of Means 1. Calculate x 1, x 2, SE 1, SE 2. 2. Combined SE = SE1 2 + SE2 2. ASSUMES INDEPENDENT SAMPLES. 3. Calculate df: either Welch-Satterthwaite formula or simpler df = min(n
Introduction to Hypothesis Testing OPRE 6301
Introduction to Hypothesis Testing OPRE 6301 Motivation... The purpose of hypothesis testing is to determine whether there is enough statistical evidence in favor of a certain belief, or hypothesis, about
ch12 practice test SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.
ch12 practice test 1) The null hypothesis that x and y are is H0: = 0. 1) 2) When a two-sided significance test about a population slope has a P-value below 0.05, the 95% confidence interval for A) does
Topic #6: Hypothesis. Usage
Topic #6: Hypothesis A hypothesis is a suggested explanation of a phenomenon or reasoned proposal suggesting a possible correlation between multiple phenomena. The term derives from the ancient Greek,
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.................
Regression Analysis: A Complete Example
Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc, Inc./Getty
Software Development Methodologies in Industry. By: Ahmad Deeb
Software Development Methodologies in Industry By: Ahmad Deeb Methodologies Software Development Methodologies in Industry Presentation outline SDM definition Project and analysis approach Research methods
Statistical tests for SPSS
Statistical tests for SPSS Paolo Coletti A.Y. 2010/11 Free University of Bolzano Bozen Premise This book is a very quick, rough and fast description of statistical tests and their usage. It is explicitly
Hypothesis testing - Steps
Hypothesis testing - Steps Steps to do a two-tailed test of the hypothesis that β 1 0: 1. Set up the hypotheses: H 0 : β 1 = 0 H a : β 1 0. 2. Compute the test statistic: t = b 1 0 Std. error of b 1 =
Introduction to Hypothesis Testing
I. Terms, Concepts. Introduction to Hypothesis Testing A. In general, we do not know the true value of population parameters - they must be estimated. However, we do have hypotheses about what the true
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
Independent samples t-test. Dr. Tom Pierce Radford University
Independent samples t-test Dr. Tom Pierce Radford University The logic behind drawing causal conclusions from experiments The sampling distribution of the difference between means The standard error of
Correlation key concepts:
CORRELATION Correlation key concepts: Types of correlation Methods of studying correlation a) Scatter diagram b) Karl pearson s coefficient of correlation c) Spearman s Rank correlation coefficient d)
Hypothesis Testing --- One Mean
Hypothesis Testing --- One Mean A hypothesis is simply a statement that something is true. Typically, there are two hypotheses in a hypothesis test: the null, and the alternative. Null Hypothesis The hypothesis
QUANTITATIVE METHODS BIOLOGY FINAL HONOUR SCHOOL NON-PARAMETRIC TESTS
QUANTITATIVE METHODS BIOLOGY FINAL HONOUR SCHOOL NON-PARAMETRIC TESTS This booklet contains lecture notes for the nonparametric work in the QM course. This booklet may be online at http://users.ox.ac.uk/~grafen/qmnotes/index.html.
Clinical Study Design and Methods Terminology
Home College of Veterinary Medicine Washington State University WSU Faculty &Staff Page Page 1 of 5 John Gay, DVM PhD DACVPM AAHP FDIU VCS Clinical Epidemiology & Evidence-Based Medicine Glossary: Clinical
Indexes, Scales, and Typologies. Edgar Degas: The Absinthe Drinker (detail), 1875-76
Indexes, Scales, and Typologies Edgar Degas: The Absinthe Drinker (detail), 1875-76 Indexes versus Scales 1. Index A composite measure based upon multiple nominal-level indicators. This composite might
Nonparametric tests these test hypotheses that are not statements about population parameters (e.g.,
CHAPTER 13 Nonparametric and Distribution-Free Statistics Nonparametric tests these test hypotheses that are not statements about population parameters (e.g., 2 tests for goodness of fit and independence).
MULTIPLE REGRESSION ANALYSIS OF MAIN ECONOMIC INDICATORS IN TOURISM. R, analysis of variance, Student test, multivariate analysis
Journal of tourism [No. 8] MULTIPLE REGRESSION ANALYSIS OF MAIN ECONOMIC INDICATORS IN TOURISM Assistant Ph.D. Erika KULCSÁR Babeş Bolyai University of Cluj Napoca, Romania Abstract This paper analysis
Introduction to. Hypothesis Testing CHAPTER LEARNING OBJECTIVES. 1 Identify the four steps of hypothesis testing.
Introduction to Hypothesis Testing CHAPTER 8 LEARNING OBJECTIVES After reading this chapter, you should be able to: 1 Identify the four steps of hypothesis testing. 2 Define null hypothesis, alternative
Survey Research: Choice of Instrument, Sample. Lynda Burton, ScD Johns Hopkins University
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this
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
Lesson 1: Comparison of Population Means Part c: Comparison of Two- Means
Lesson : Comparison of Population Means Part c: Comparison of Two- Means Welcome to lesson c. This third lesson of lesson will discuss hypothesis testing for two independent means. Steps in Hypothesis
LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING In this lab you will explore the concept of a confidence interval and hypothesis testing through a simulation problem in engineering setting.
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
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
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
An Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10- TWO-SAMPLE TESTS
The Islamic University of Gaza Faculty of Commerce Department of Economics and Political Sciences An Introduction to Statistics Course (ECOE 130) Spring Semester 011 Chapter 10- TWO-SAMPLE TESTS Practice
A Primer on Forecasting Business Performance
A Primer on Forecasting Business Performance There are two common approaches to forecasting: qualitative and quantitative. Qualitative forecasting methods are important when historical data is not available.
APPENDIX N. Data Validation Using Data Descriptors
APPENDIX N Data Validation Using Data Descriptors Data validation is often defined by six data descriptors: 1) reports to decision maker 2) documentation 3) data sources 4) analytical method and detection
Planning sample size for randomized evaluations
TRANSLATING RESEARCH INTO ACTION Planning sample size for randomized evaluations Simone Schaner Dartmouth College povertyactionlab.org 1 Course Overview Why evaluate? What is evaluation? Outcomes, indicators
Fairfield Public Schools
Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity
Data Mining Techniques Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools
Data Mining Techniques Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools Occam s razor.......................................................... 2 A look at data I.........................................................
Descriptive Statistics
Descriptive Statistics Suppose following data have been collected (heights of 99 five-year-old boys) 117.9 11.2 112.9 115.9 18. 14.6 17.1 117.9 111.8 16.3 111. 1.4 112.1 19.2 11. 15.4 99.4 11.1 13.3 16.9
Chapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing
Chapter 8 Hypothesis Testing 1 Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing 8-3 Testing a Claim About a Proportion 8-5 Testing a Claim About a Mean: s Not Known 8-6 Testing
CHAPTER 13 SIMPLE LINEAR REGRESSION. Opening Example. Simple Regression. Linear Regression
Opening Example CHAPTER 13 SIMPLE LINEAR REGREION SIMPLE LINEAR REGREION! Simple Regression! Linear Regression Simple Regression Definition A regression model is a mathematical equation that descries the
Basic research methods. Basic research methods. Question: BRM.2. Question: BRM.1
BRM.1 The proportion of individuals with a particular disease who die from that condition is called... BRM.2 This study design examines factors that may contribute to a condition by comparing subjects
Stat 411/511 THE RANDOMIZATION TEST. Charlotte Wickham. stat511.cwick.co.nz. Oct 16 2015
Stat 411/511 THE RANDOMIZATION TEST Oct 16 2015 Charlotte Wickham stat511.cwick.co.nz Today Review randomization model Conduct randomization test What about CIs? Using a t-distribution as an approximation
Practical Research. Paul D. Leedy Jeanne Ellis Ormrod. Planning and Design. Tenth Edition
Practical Research Planning and Design Tenth Edition Paul D. Leedy Jeanne Ellis Ormrod 2013, 2010, 2005, 2001, 1997 Pearson Education, Inc. All rights reserved. Chapter 1 The Nature and Tools of Research
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
Psychodynamic Workbook
Psychodynamic Workbook Name: Group: Exam Dates: King Edward VI Psychology Department 1 Contents Specification... 3 Psychodynamic Approach... 5 Content Personality... 8 Content Psychosexual development...
Section 7.1. Introduction to Hypothesis Testing. Schrodinger s cat quantum mechanics thought experiment (1935)
Section 7.1 Introduction to Hypothesis Testing Schrodinger s cat quantum mechanics thought experiment (1935) Statistical Hypotheses A statistical hypothesis is a claim about a population. Null hypothesis
Effects of CEO turnover on company performance
Headlight International Effects of CEO turnover on company performance CEO turnover in listed companies has increased over the past decades. This paper explores whether or not changing CEO has a significant
p ˆ (sample mean and sample
Chapter 6: Confidence Intervals and Hypothesis Testing When analyzing data, we can t just accept the sample mean or sample proportion as the official mean or proportion. When we estimate the statistics
MONT 107N Understanding Randomness Solutions For Final Examination May 11, 2010
MONT 07N Understanding Randomness Solutions For Final Examination May, 00 Short Answer (a) (0) How are the EV and SE for the sum of n draws with replacement from a box computed? Solution: The EV is n times
$2 4 40 + ( $1) = 40
THE EXPECTED VALUE FOR THE SUM OF THE DRAWS In the game of Keno there are 80 balls, numbered 1 through 80. On each play, the casino chooses 20 balls at random without replacement. Suppose you bet on the
SECURITY METRICS: MEASUREMENTS TO SUPPORT THE CONTINUED DEVELOPMENT OF INFORMATION SECURITY TECHNOLOGY
SECURITY METRICS: MEASUREMENTS TO SUPPORT THE CONTINUED DEVELOPMENT OF INFORMATION SECURITY TECHNOLOGY Shirley Radack, Editor Computer Security Division Information Technology Laboratory National Institute
STAT 350 Practice Final Exam Solution (Spring 2015)
PART 1: Multiple Choice Questions: 1) A study was conducted to compare five different training programs for improving endurance. Forty subjects were randomly divided into five groups of eight subjects
WISE Power Tutorial All Exercises
ame Date Class WISE Power Tutorial All Exercises Power: The B.E.A.. Mnemonic Four interrelated features of power can be summarized using BEA B Beta Error (Power = 1 Beta Error): Beta error (or Type II
12.5: CHI-SQUARE GOODNESS OF FIT TESTS
125: Chi-Square Goodness of Fit Tests CD12-1 125: CHI-SQUARE GOODNESS OF FIT TESTS In this section, the χ 2 distribution is used for testing the goodness of fit of a set of data to a specific probability
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
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
1. How different is the t distribution from the normal?
Statistics 101 106 Lecture 7 (20 October 98) c David Pollard Page 1 Read M&M 7.1 and 7.2, ignoring starred parts. Reread M&M 3.2. The effects of estimated variances on normal approximations. t-distributions.
Quantitative (wrapup) and Qualitative Evaluation. CS160: User Interfaces John Canny
Quantitative (wrapup) and Qualitative Evaluation CS160: User Interfaces John Canny Null Hypothesis We really want to test if interface A is faster than interface B however, the probabilistic model for
2013 MBA Jump Start Program. Statistics Module Part 3
2013 MBA Jump Start Program Module 1: Statistics Thomas Gilbert Part 3 Statistics Module Part 3 Hypothesis Testing (Inference) Regressions 2 1 Making an Investment Decision A researcher in your firm just
Two-Sample T-Tests Assuming Equal Variance (Enter Means)
Chapter 4 Two-Sample T-Tests Assuming Equal Variance (Enter Means) Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when the variances of
The Effect of Dropping a Ball from Different Heights on the Number of Times the Ball Bounces
The Effect of Dropping a Ball from Different Heights on the Number of Times the Ball Bounces Or: How I Learned to Stop Worrying and Love the Ball Comment [DP1]: Titles, headings, and figure/table captions
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Final Exam Review MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) A researcher for an airline interviews all of the passengers on five randomly
2 Precision-based sample size calculations
Statistics: An introduction to sample size calculations Rosie Cornish. 2006. 1 Introduction One crucial aspect of study design is deciding how big your sample should be. If you increase your sample size
Descriptive Statistics
Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize
Options Pricing. This is sometimes referred to as the intrinsic value of the option.
Options Pricing We will use the example of a call option in discussing the pricing issue. Later, we will turn our attention to the Put-Call Parity Relationship. I. Preliminary Material Recall the payoff
Money and Banking Prof. Yamin Ahmad ECON 354 Spring 2006
Money and Banking Prof. Yamin Ahmad ECON 354 Spring 2006 Final Exam Name Id # Instructions: There are 30 questions on this exam. Please circle the correct solution on the exam paper and fill in the relevant
IAB Evaluation Study of Methods Used to Assess the Effectiveness of Advertising on the Internet
IAB Evaluation Study of Methods Used to Assess the Effectiveness of Advertising on the Internet ARF Research Quality Council Paul J. Lavrakas, Ph.D. November 15, 2010 IAB Study of IAE The effectiveness
Statistics 2014 Scoring Guidelines
AP Statistics 2014 Scoring Guidelines College Board, Advanced Placement Program, AP, AP Central, and the acorn logo are registered trademarks of the College Board. AP Central is the official online home
Part 2: Analysis of Relationship Between Two Variables
Part 2: Analysis of Relationship Between Two Variables Linear Regression Linear correlation Significance Tests Multiple regression Linear Regression Y = a X + b Dependent Variable Independent Variable
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....................
X X X a) perfect linear correlation b) no correlation c) positive correlation (r = 1) (r = 0) (0 < r < 1)
CORRELATION AND REGRESSION / 47 CHAPTER EIGHT CORRELATION AND REGRESSION Correlation and regression are statistical methods that are commonly used in the medical literature to compare two or more variables.
Single and Multiple-Case Study Designs IS493
1 2 Research Strategies Basic oppositions Survey research versus Case study quantitative versus qualitative The whole gamut Experiment Survey Archival analysis Historical research Case study 3 Basic Conditions
Recall this chart that showed how most of our course would be organized:
Chapter 4 One-Way ANOVA Recall this chart that showed how most of our course would be organized: Explanatory Variable(s) Response Variable Methods Categorical Categorical Contingency Tables Categorical
Hypothesis Testing for Beginners
Hypothesis Testing for Beginners Michele Piffer LSE August, 2011 Michele Piffer (LSE) Hypothesis Testing for Beginners August, 2011 1 / 53 One year ago a friend asked me to put down some easy-to-read notes