MADAM SITI AISYAH ZAKARIA EQT 271 SEM 2 2014/2015 CHAPTER 3 ANOVA (EXTRA NOTE & EXERCISE)

Slides:



Advertisements
Similar presentations
INFERENCE: SIGNIFICANCE TESTS ABOUT HYPOTHESES Chapter 9.
Advertisements

Copyright © 2014 by McGraw-Hill Higher Education. All rights reserved.
CHAPTER 23: Two Categorical Variables: The Chi-Square Test
Significance Tests About
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 9-1 Chapter 9 Fundamentals of Hypothesis Testing: One-Sample Tests Basic Business Statistics.
8-4 Testing a Claim About a Mean
Chapter 9 Hypothesis Testing.
BCOR 1020 Business Statistics Lecture 20 – April 3, 2008.
Lecture 13: Tues., Feb. 24 Comparisons Among Several Groups – Introduction (Case Study 5.1.1) Comparing Any Two of the Several Means (Chapter 5.2) The.
Significance Tests for Proportions Presentation 9.2.
Chapter 12: Analysis of Variance
How tired are students in the morning ? Jose Almanza Period
Unit 7b Statistical Inference - 2 Hypothesis Testing Using Data to Make Decisions FPP Chapters 27, 27, possibly 27 &/or 29 Z-tests for means Z-tests.
Confidence Intervals and Hypothesis Testing - II
Hypothesis Testing – Examples and Case Studies
Fundamentals of Hypothesis Testing: One-Sample Tests
Section 9.1 Introduction to Statistical Tests 9.1 / 1 Hypothesis testing is used to make decisions concerning the value of a parameter.
Section 10.1 ~ t Distribution for Inferences about a Mean Introduction to Probability and Statistics Ms. Young.
Agresti/Franklin Statistics, 1 of 82 Chapter 13 Comparing Groups: Analysis of Variance Methods Learn …. How to use Statistical inference To Compare Several.
More About Significance Tests
Lecture 20 Dustin Lueker.  The p-value for testing H 1 : µ≠100 is p=.001. This indicates that… 1.There is strong evidence that μ=100 2.There is strong.
Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.
Copyright © 2008 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 22 Using Inferential Statistics to Test Hypotheses.
Section 9.2 Testing the Mean  9.2 / 1. Testing the Mean  When  is Known Let x be the appropriate random variable. Obtain a simple random sample (of.
Chapter 9 Testing the Difference Between Two Means, Two Proportions, and Two Variances Copyright © 2012 The McGraw-Hill Companies, Inc. Permission required.
Section Inference for Experiments Objectives: 1.To understand how randomization differs in surveys and experiments when comparing two populations.
McGraw-Hill, Bluman, 7th ed., Chapter 8
© Copyright McGraw-Hill CHAPTER 12 Analysis of Variance (ANOVA)
Gabriela Gonzalez Alyssa Vasquez Elizabeth Carlos Columba Nava Period
SUMMARY FOR EQT271 Semester /2015 Maz Jamilah Masnan, Inst. of Engineering Mathematics, Univ. Malaysia Perlis.
Chapter 10: Comparing Two Populations or Groups
Agresti/Franklin Statistics, 1 of 122 Chapter 8 Statistical inference: Significance Tests About Hypotheses Learn …. To use an inferential method called.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Testing the Difference Between Two Means: Dependent Samples Sec 9.3 Bluman, Chapter 91.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 13 Multiple Regression Section 13.3 Using Multiple Regression to Make Inferences.
Introduction to Inferece BPS chapter 14 © 2010 W.H. Freeman and Company.
Chapter 221 What Is a Test of Significance?. Chapter 222 Thought Question 1 The defendant in a court case is either guilty or innocent. Which of these.
Lecture 9 Chap 9-1 Chapter 2b Fundamentals of Hypothesis Testing: One-Sample Tests.
Section 10.1 Estimating with Confidence AP Statistics February 11 th, 2011.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Overview.
Tests of Significance: The Basics BPS chapter 15 © 2006 W.H. Freeman and Company.
Slide Slide 1 Section 8-4 Testing a Claim About a Mean:  Known.
Chap 8-1 Fundamentals of Hypothesis Testing: One-Sample Tests.
Agresti/Franklin Statistics, 1 of 88 Chapter 11 Analyzing Association Between Quantitative Variables: Regression Analysis Learn…. To use regression analysis.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 14 Comparing Groups: Analysis of Variance Methods Section 14.3 Two-Way ANOVA.
Simple examples of the Bayesian approach For proportions and means.
2 sample interval proportions sample Shown with two examples.
© Copyright McGraw-Hill 2004
Exercise - 1 A package-filling process at a Cement company fills bags of cement to an average weight of µ but µ changes from time to time. The standard.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 10 Comparing Two Groups Section 10.1 Categorical Response: Comparing Two Proportions.
* Chapter 8 – we were estimating with confidence about a population * Chapter 9 – we were testing a claim about a population * Chapter 10 – we are comparing.
McGraw-Hill, Bluman, 7th ed., Chapter 12
McGraw-Hill, Bluman, 7th ed., Chapter 12
AP Process Test of Significance for Population Proportion.
Mariana Lopez Carlos Aguilar Alex Rodriguez Period Commute time for senior student’s high school experience.
Understanding Basic Statistics Fourth Edition By Brase and Brase Prepared by: Lynn Smith Gloucester County College Chapter Nine Hypothesis Testing.
Testing a Single Mean Module 16. Tests of Significance Confidence intervals are used to estimate a population parameter. Tests of Significance or Hypothesis.
Created by Erin Hodgess, Houston, Texas Section 7-1 & 7-2 Overview and Basics of Hypothesis Testing.
THE MORE T-DISTRIBUTION & SIGNIFICANCE TESTING FOR QUANTITATIVE DATA CHAPTER 23.
SUMMARY EQT 271 MADAM SITI AISYAH ZAKARIA SEMESTER /2015.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Lecture Slides Elementary Statistics Tenth Edition and the.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 14 Comparing Groups: Analysis of Variance Methods Section 14.1 One-Way ANOVA: Comparing.
Chapter 13 Comparing Groups: Analysis of Variance Methods
Chapter 9 Hypothesis Testing
Tests of Significance: The Basics
For the single mean & proportion Confidence Interval vs Hypothesis Testing At the same level in confidence interval and hypothesis testing,
Introduction to Inference
Introduction to Inference
Additional Topics Regarding Hypothesis Testing
Presentation transcript:

MADAM SITI AISYAH ZAKARIA EQT 271 SEM /2015 CHAPTER 3 ANOVA (EXTRA NOTE & EXERCISE)

REFRESH YOUR MIND

Agresti/Franklin Statistics, 3 of 82 The 1998 General Social Survey asked subjects how many friend they have. Is this associated with the respondent’s astrological sign (the 13 symbols of the Zodiac)? The ANOVA table for the data reports F=0.61 State the null hypothesis a.The population means for all 12 Zodiac signs are the same. b.At least two population means are different.

Agresti/Franklin Statistics, 4 of 82 The 1998 General Social Survey asked subjects how many friend they have. Is this associated with the respondent’s astrological sign (the 13 symbols of the Zodiac)? The ANOVA table for the data reports F=0.61 State the alternative hypothesis a.The population means for all 12 Zodiac signs are the same. b.At least two population means are different.

Agresti/Franklin Statistics, 5 of 82 The 1998 General Social Survey asked subjects how many friend they have. Is this associated with the respondent’s astrological sign (the 13 symbols of the Zodiac)? The ANOVA table for the data reports F=0.61 Based on what you know about the F distribution would you guess that the test value of 0.61 provides strong evidence against the null hypothesis? a.No b.Yes

Agresti/Franklin Statistics, 6 of 82 The 1998 General Social Survey asked subjects how many friend they have. Is this associated with the respondent’s astrological sign (the 13 symbols of the Zodiac)? The ANOVA table for the data reports F=0.61 The P-value associated with the F-statistic is At a significance level of 0.05, what is the correct decision? a.Reject H o b.Fail to Reject H o c.Reject H a d.Fail to Reject H a

CONTINUE FROM PART 3 (FACTORIAL EXPERIMENT) INTERACTION FACTOR

Agresti/Franklin Statistics, 8 of 82 Exploring Interaction between Factors in Two-Way ANOVA No interaction between two factors means that the effect of either factor on the response variable is the same at each category of the other factor. [Factor A and Factor B] Do not Reject H 0

Graphical No interaction or have interaction

Agresti/Franklin Statistics, 10 of 82 Exploring Interaction between Factors in Two-Way ANOVA  The lines in the graph is parallel or approximately parallel.  There is no significant interaction effect between the factor.  The difference in estimated means between the two fertilizer levels is the same for each manure level.  The effect of two factor is same

Agresti/Franklin Statistics, 11 of 82 Exploring Interaction between Factors in Two-Way ANOVA A graph showing interaction:  Intersection occur – disordinal interaction (SOME INTERACTION) - Not more effect  No intersection – ordinal interaction (SIGNIFICANT INTERACTION) - have more effect

Agresti/Franklin Statistics, 12 of 82 Testing for Interaction In conducting a two-way ANOVA, before testing the main effects, it is customary to test a third null hypothesis stating that their is no interaction between the factors in their effects on the response

Agresti/Franklin Statistics, 13 of 82 Testing for Interaction The test statistic providing the sample evidence of interaction is: When H 0 is false (reject H 0 ), the F-statistic tends to be large

Agresti/Franklin Statistics, 14 of 82 Example: Testing for Interaction with Corn Yield Data ANOVA table for a model that allows interaction:

Agresti/Franklin Statistics, 15 of 82 Example: Testing for Interaction with Corn Yield Data The test statistic for H 0 : no interaction is F = 1.10 with a corresponding P-value of There is not much evidence of interaction We would not reject H 0 at the usual significance levels, such as 0.05

Agresti/Franklin Statistics, 16 of 82 Check Interaction before Main Effects In practice, in two-way ANOVA, you should first test the hypothesis of no interaction

Agresti/Franklin Statistics, 17 of 82 Check Interaction before Main Effects If the evidence of interaction is not strong (that is, if the P-value is not small), then test the main effects (factor A and factor B) hypotheses and/or construct confidence intervals for those effects

Agresti/Franklin Statistics, 18 of 82 Check Interaction before Main Effects If important evidence of interaction exists (have interaction in your hypothesis), plot and compare the cell means for a factor separately at each category of the other factor

REFRESH YOUR MIND

Agresti/Franklin Statistics, 20 of 82 An experiment randomly assigns 100 subjects suffering from high cholesterol to one of four groups: low-dose Lipitor, high-dose Lipitor, low- dose Pravachol and high-dose Pravachol. After three months of treatment, the change in cholesterol level is measured. What is the response variable? a.Cholesterol level b.Drug dosage c.Drug type

Agresti/Franklin Statistics, 21 of 82 An experiment randomly assigns 100 subjects suffering from high cholesterol to one of four groups: low-dose Lipitor, high-dose Lipitor, low- dose Pravachol and high-dose Pravachol. After three months of treatment, the change in cholesterol level is measured. What are the factors? a.Cholesterol level and drug type b.Drug dosage and cholesterol level c.Drug type and drug dosage

ANOVA ONE-WAY or TWO WAY CONCLUSION  Reject H 0  There is difference (which one is difference???)

RELATIONSHIP BETWEEN HYPOTHESIS TESTING AND CONFIDENT INTERVAL

Agresti/Franklin Statistics, 24 of 82 For the single mean & proportion Confidence Interval vs Hypothesis Testing At the same level in confidence interval and hypothesis testing, when the null hypothesis is rejected, the confidence interval for the mean and proportion will not contain the hypothesized mean/proportion. Likewise, when we do not reject null hypothesis the confidence interval will contain the hypothesized mean/ proportion. ** Applies only for two-tailed test. Allan Bluman, pg. 458

Agresti/Franklin Statistics, 25 of 82 For the difference of means & proportions Confidence Interval vs Hypothesis Testing [-8.5, 8.5] Contains zero = If the CI contains zero, we do not reject H 0 (Means that the there is NO DIFFERENCE in population means or proportions) [5.45, 12.45] No zero = If the CI does not contain zero, we reject H 0 (Mean/proportion for population 1 is GREATER than the mean/proportion for population 2) There is difference in population means [-7.3, -3.3] No zero = If the CI does not contain zero, we reject H 0 (Mean/proportion for population 1 is LESS than the mean/proportion for population 2) There is difference in population means ** Applies only for two-tailed test. Eg. in Allan Bluman, pg

EXAMPLE HYPOTHESIS TESTING & CONFIDENT INTERVAL

Agresti/Franklin Statistics, 27 of 82 Hog Weights A researcher claims that adult hogs fed a special diet will have an average weight of 200 pounds. A sample of 10 hogs has an average weight of pounds and a standard deviation of 3.3 pounds. At a 0.05, can the claim be rejected? Also, find the 95% confidence interval of the true mean. 27

Agresti/Franklin Statistics, 28 of 82 28

Agresti/Franklin Statistics, 29 of 82 Sugar Production Sugar is packed in 5-pound bags. An inspector suspects the bags may not contain 5 pounds. A sample of 50 bags produces a mean of 4.6 pounds and a standard deviation of 0.7 pound. Is there enough evidence to conclude that the bags do not contain 5 pounds as stated at a 0.05? Also, find the 95% confidence interval of the true mean. Answer: Reject H 0 and 95% confidence interval of μ does not contain the hypothesized value μ = 5. Z = CI =[4.46, 4.79] 29

GOOD LUCK… THE END….