Comparison of Two Univariate Means

Slides:



Advertisements
Similar presentations
Testing means, part III The two-sample t-test. Sample Null hypothesis The population mean is equal to  o One-sample t-test Test statistic Null distribution.
Advertisements

INDEPENDENT SAMPLES T Purpose: Test whether two means are significantly different Design: between subjects scores are unpaired between groups.
Probability & Statistical Inference Lecture 7 MSc in Computing (Data Analytics)
10-1 Introduction 10-2 Inference for a Difference in Means of Two Normal Distributions, Variances Known Figure 10-1 Two independent populations.
6.3 Two-Sample Inference for Means November 17, 2003.
Inferences About Means of Two Independent Samples Chapter 11 Homework: 1, 2, 4, 6, 7.
Experiments. Vocabulary  Response Variable – One that measures an outcome or result of study (dependent variable, y)  Explanatory Variable – One that.
1 Multivariate Normal Distribution Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
Choosing Statistical Procedures
Ch 10 Comparing Two Proportions Target Goal: I can determine the significance of a two sample proportion. 10.1b h.w: pg 623: 15, 17, 21, 23.
Two Sample Tests Nutan S. Mishra Department of Mathematics and Statistics University of South Alabama.
1 Repeated Measures ANOVA Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking and.
1 Comparison of Several Multivariate Means Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute.
Chapter 14 Nonparametric Statistics. 2 Introduction: Distribution-Free Tests Distribution-free tests – statistical tests that don’t rely on assumptions.
Pengujian Hipotesis Dua Populasi By. Nurvita Arumsari, Ssi, MSi.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Experimental Design and Analysis of Variance Chapter 10.
B AD 6243: Applied Univariate Statistics Hypothesis Testing and the T-test Professor Laku Chidambaram Price College of Business University of Oklahoma.
1 Multivariate Linear Regression Models Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of.
Agresti/Franklin Statistics, 1 of 56  Section 4.3 What Are Good Ways and Poor Ways to Experiment?
11 Comparison of Several Multivariate Means Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute.
1 Univariate Inferences about a Mean Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
One-way ANOVA: - Comparing the means IPS chapter 12.2 © 2006 W.H. Freeman and Company.
Producing Data (C11-13 BVD) C13: Experiments and Observational Studies.
Single-Factor Studies KNNL – Chapter 16. Single-Factor Models Independent Variable can be qualitative or quantitative If Quantitative, we typically assume.
1 Matrix Algebra and Random Vectors Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
1 Inferences about a Mean Vector Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
T tests comparing two means t tests comparing two means.
Medical Statistics Medical Statistics Tao Yuchun Tao Yuchun 7
Innovative Teaching Article (slides with auxiliary information: © 2014) James W. Grice Oklahoma State University Department of Psychology.
1 Two-Way ANOVA Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking and Multimedia.
Lecture 8 Estimation and Hypothesis Testing for Two Population Parameters.
1 Canonical Correlation Analysis Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
1 ANOVA: ANalysis Of VAriances Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking.
Statistical Inferences for Variance Objectives: Learn to compare variance of a sample with variance of a population Learn to compare variance of a sample.
Chapter 11 Inference for Distributions AP Statistics 11.2 – Inference for comparing TWO Means.
Chapter 11 Analysis of Variance
Experimental Design and Analysis of Variance
Principal Components Shyh-Kang Jeng
CHAPTER 10 Comparing Two Populations or Groups
Observational Study vs. Experimental Design
Hypothesis testing using contrasts
Psychology 202a Advanced Psychological Statistics
Topic 21—Comparison of Proportions
الفصل السادس: التعلم عن بعد (تال101ت)
Chapter 11 Analysis of Variance
Comparing Two Means.
Ten things about Experimental Design
Comparing Populations
Nested Designs and Repeated Measures with Treatment and Time Effects
Reasoning in Psychology Using Statistics
Statistics Experimental Design
Chapter 10: The t Test For Two Independent Samples
Matrix Algebra and Random Vectors
CHAPTER 10 Comparing Two Populations or Groups
CHAPTER 6 Statistical Inference & Hypothesis Testing
Multivariate Linear Regression Models
A special type of t-inference
Comparing Two Means.
Scientific Method.
One sample compared to population
CHAPTER 10 Comparing Two Populations or Groups
Psychological Experimentation
Experimental Design Statistics.
pairing data values (before-after, method1 vs
CHAPTER 10 Comparing Two Populations or Groups
Producing good data through sampling and experimentation
Chapter 9 Lecture 4 Section: 9.4.
Chapter 9 Lecture 3 Section: 9.3.
Unit 1: Science of Psychology
Chapter 22 – Comparing Two Proportions
Presentation transcript:

Comparison of Two Univariate Means Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking and Multimedia 1

Scenarios To test if the differences are significant between Teaching using Power Point vs. using chalks and blackboard only Drug vs. placebos Processing speed of MP3 player model I of brand A vs. model G of brand B Performance of students going to cram schools vs. those not

Experiment Design for Paired Comparisons 1 2 3 n . . . . . . Treatments 1 and 2 assigned at random Treatments 1 and 2 assigned at random Treatments 1 and 2 assigned at random Treatments 1 and 2 assigned at random 3

Single Response (Univariate) Case 4

Comparing Means from Two Populations Without explicitly controlling for unit-to-unit variability, as in the paired comparison case Experimental units are randomly assigned to populations Applicable to a more general collection of experimental units 5

Assumptions Concerning the Structure of Data 6

Pooled Estimate of Population Variance 7

t-Statistics for Comparing Two Populations 8

Test of Hypothesis 9