Odds vs. Probabilities Odds ratio in SPSS (Exp(B)) is an odds rather than a probability Odds = success/failure Probability = Likelihood of success for.

Slides:



Advertisements
Similar presentations
ODDS vs. PROBABILITY Odds are a little different than probability. When we calculate probability, we look at the ratio of favorable outcomes to the total.
Advertisements

Lahore University of Management Sciences, Lahore, Pakistan Dr. M.M. Awais- Computer Science Department 1 Lecture 12 Dealing With Uncertainty Probabilistic.
Logistic Regression and Odds Ratios
Chapter 6 Section 1 Introduction. Probability of an Event The probability of an event is a number that expresses the long run likelihood that an event.
Week 5 – PART I POWER AND SAMPLE SIZE. Terminology : Normal Samples Power is the probability of rejecting a false null hypothesis. Power should be close.
Mean for sample of n=10 n = 10: t = 1.361df = 9Critical value = Conclusion: accept the null hypothesis; no difference between this sample.
Basic Statistical Concepts Donald E. Mercante, Ph.D. Biostatistics School of Public Health L S U - H S C.
(a) (b) (c) (d). What is (1,2,3)  (3,4,2)? (a) (1, 2, 3, 4) (b) (1,2)  (3,4) (c) (1,3,4,2) (d) (3,1)  (4,2)
Basic Concepts and Approaches
10.1 & 10.2 Probability & Permutations. WARM UP:
Categorical Data Prof. Andy Field.
Education 795 Class Notes Applied Research Logistic Regression Note set 10.
Dr Laura Bonnett Department of Biostatistics. UNDERSTANDING SURVIVAL ANALYSIS.
Poisson Random Variable Provides model for data that represent the number of occurrences of a specified event in a given unit of time X represents the.
Logistic Regression.
Proc freq: Five secrets* *Okay, well, lesser known facts.
R Programming Odds & Odds Ratios 1. Session 3 Overview 1.Odds 2.Odds Ratio (OR) 3.Confidence Intervals for OR’s 4.Inference based on OR’s 2.
Section 10.1 Introduction to Probability. Probability Probability is the overall likelihood that an event can occur. A trial is a systematic opportunity.
Review B.Ramamurthy 7/11/2014CSE651, B. Ramamurthy1.
University of Warwick, Department of Sociology, 2014/15 SO 201: SSAASS (Surveys and Statistics) (Richard Lampard) Week 7 Logistic Regression I.
LOGISTIC REGRESSION A statistical procedure to relate the probability of an event to explanatory variables Used in epidemiology to describe and evaluate.
Logistic Regression. Conceptual Framework - LR Dependent variable: two categories with underlying propensity (yes/no) (absent/present) Independent variables:
APPLIED DATA ANALYSIS IN CRIMINAL JUSTICE CJ 525 MONMOUTH UNIVERSITY Juan P. Rodriguez.
Bayes Theorem Thomas R. Stewart, Ph.D. Center for Policy Research Rockefeller College of Public Affairs and Policy University at Albany State University.
SW318 Social Work Statistics Slide 1 One-way Analysis of Variance  1. Satisfy level of measurement requirements  Dependent variable is interval (ordinal)
SW318 Social Work Statistics Slide 1 Logistic Regression and Odds Ratios Example of Odds Ratio Using Relationship between Death Penalty and Race.
Section 3.2 Notes Conditional Probability. Conditional probability is the probability of an event occurring, given that another event has already occurred.
Journal: 1)Suppose you guessed on a multiple choice question (4 answers). What was the chance that you marked the correct answer? Explain. 2)What is the.
The Wonderful World… of Probability. When do we use Probability?
Digression - Hypotheses Many research designs involve statistical tests – involve accepting or rejecting a hypothesis Null (statistical) hypotheses assume.
EXAMPLE 1 Find the probability of A or B
Lesson 8.7 Page #1-29 (ODD), 33, 35, 41, 43, 47, 49, (ODD) Pick up the handout on the table.
Logistic Regression. Linear Regression Purchases vs. Income.
LOGISTIC REGRESSION Binary dependent variable (pass-fail) Odds ratio: p/(1-p) eg. 1/9 means 1 time in 10 pass, 9 times fail Log-odds ratio: y = ln[p/(1-p)]
Dates Presentations Wed / Fri Ex. 4, logistic regression, Monday Dec 7 th Final Tues. Dec 8 th, 3:30.
10.5 Independent Events Objective: Find the probability of 2 or more independent events.
Diagnosis Examination(MMSE) in detecting dementia among elderly patients living in the community. Excel.
Chapter 13 Understanding research results: statistical inference.
Odds and Relative Risk Note: this PowerPoint presentation is unfinished.
Copyright ©2004 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 4-1 Probability and Counting Rules CHAPTER 4.
1 Probability- Basic Concepts and Approaches Dr. Jerrell T. Stracener, SAE Fellow Leadership in Engineering EMIS 7370/5370 STAT 5340 : PROBABILITY AND.
13.3 Arithmetic and Geometric Series and Their Sums Finite Series.
网上报账系统包括以下业务: 日常报销 差旅费报销 借款业务 1. 填写报销内容 2. 选择支付方式 (或冲销借款) 3. 提交预约单 4. 打印预约单并同分类粘 贴好的发票一起送至财务 处 预约报销步骤: 网上报账系统 薪酬发放管理系统 财务查询系统 1.
 Students will be able to find theoretical and experimental probabilities.
9.4 Odds and Long-Term Behavior Remember to Silence Your Cell Phone and Put It In Your Bag!
LOGISTIC REGRESSION. Purpose  Logistical regression is regularly used when there are only two categories of the dependent variable and there is a mixture.
BINARY LOGISTIC REGRESSION
University of Warwick, Department of Sociology, 2014/15 SO 201: SSAASS (Surveys and Statistics) (Richard Lampard) Logistic Regression II/ (Hierarchical)
Probability and Counting Rules
LOGISTIC REGRESSION 1.
Tips Need to Consider When Organizing a College Event
Understanding How Hypothesis Testing Works
Probability and Statistics
Solve: 1. 4<
Experimental vs. Theoretical Probability
ماجستير إدارة المعارض من بريطانيا
75 Has 7 in the tens place Odd Number Less than 100
I. Statistical Tests: Why do we use them? What do they involve?
Schedules of Reinforcement
Introduction to Logistic Regression
Week 4 POWER AND SAMPLE SIZE.
Theoretical and Experimental Probability
Experimental vs. Theoretical Probability
12 Has 1 in the tens place Even Number Less than 20
Unit 6: Application of Probability
Chapter 2: Rational Numbers
9J Conditional Probability, 9K Independent Events
Chapter 12 Vocabulary.
Kaplan-Meier survival curves and the log rank test
Presentation transcript:

Odds vs. Probabilities Odds ratio in SPSS (Exp(B)) is an odds rather than a probability Odds = success/failure Probability = Likelihood of success for any one person

Null vs. Specified Model Null model Odds Ratio = 26/24 = 1.0833 Specified Model Odds Ratio = 1.7313 (e .549 where e = 2.718) What are a single person’s odds of passing given a one unit change in Aptitude? = Prior odds of passing x increase due to 1 point aptitude = 1.0833 x 1.7313 = 1.8758

Probability Odds = x/(1-x) where x = probability of occurrence of event (i.e., passing) 1.8758 = x/(1-x) Solve for x, x = .652 Conclusion: A one unit increase in aptitude, increases the probability of being successful from 52% to 65.2%