Math 10 Chapter 9 Notes: Hypothesis Testing done constantly in medicine, business, polling, education, etc. to do: set up 2 contradictory statements first.

Slides:



Advertisements
Similar presentations
Our goal is to assess the evidence provided by the data in favor of some claim about the population. Section 6.2Tests of Significance.
Advertisements

© 2010 Pearson Prentice Hall. All rights reserved Hypothesis Testing Basics.
© 2010 Pearson Prentice Hall. All rights reserved Hypothesis Testing Using a Single Sample.
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Hypothesis Testing GTECH 201 Lecture 16.
1/55 EF 507 QUANTITATIVE METHODS FOR ECONOMICS AND FINANCE FALL 2008 Chapter 10 Hypothesis Testing.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 8-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter.
Chapter 3 Hypothesis Testing. Curriculum Object Specified the problem based the form of hypothesis Student can arrange for hypothesis step Analyze a problem.
State the null and alternative hypotheses.
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Hypothesis Tests Regarding a Parameter 10.
Mr. Mark Anthony Garcia, M.S. Mathematics Department De La Salle University.
BCOR 1020 Business Statistics
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 8-1 TUTORIAL 6 Chapter 10 Hypothesis Testing.
Probability Population:
Statistical Inference Decision Making (Hypothesis Testing) Decision Making (Hypothesis Testing) A formal method for decision making in the presence of.
Confidence Intervals Chapter 8 Objectives 1. The student will be able to  Calculate and interpret confidence intervals for one population average and.
Confidence Intervals and Hypothesis Testing - II
CHAPTER 2 Statistical Inference 2.1 Estimation  Confidence Interval Estimation for Mean and Proportion  Determining Sample Size 2.2 Hypothesis Testing:
Presented by Mohammad Adil Khan
Sections 8-1 and 8-2 Review and Preview and Basics of Hypothesis Testing.
Fundamentals of Hypothesis Testing: One-Sample Tests
HYPOTHESIS TESTING Fall 2013 Nov 14/15. HYPOTHESIS TESTING Test assumptions about population parameters using a sample. Example: The mean age of targeting.
Hypothesis Testing (Statistical Significance). Hypothesis Testing Goal: Make statement(s) regarding unknown population parameter values based on sample.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap th Lesson Introduction to Hypothesis Testing.
1 Chapter 10: Section 10.1: Vocabulary of Hypothesis Testing.
Overview Basics of Hypothesis Testing
1 Introduction to Hypothesis Testing. 2 What is a Hypothesis? A hypothesis is a claim A hypothesis is a claim (assumption) about a population parameter:
Hypothesis testing Chapter 9. Introduction to Statistical Tests.
STA Statistical Inference
McGraw-Hill, Bluman, 7th ed., Chapter 8
STATISTICAL INFERENCES
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Hypothesis Tests Regarding a Parameter 10.
Agresti/Franklin Statistics, 1 of 122 Chapter 8 Statistical inference: Significance Tests About Hypotheses Learn …. To use an inferential method called.
1 Statistics 300: Elementary Statistics Section 8-2.
Chapter 9 Fundamentals of Hypothesis Testing: One-Sample Tests.
Lesson The Language of Hypothesis Testing.
Statistical Hypotheses & Hypothesis Testing. Statistical Hypotheses There are two types of statistical hypotheses. Null Hypothesis The null hypothesis,
Hypothesis and Test Procedures A statistical test of hypothesis consist of : 1. The Null hypothesis, 2. The Alternative hypothesis, 3. The test statistic.
Lecture 17 Dustin Lueker.  A way of statistically testing a hypothesis by comparing the data to values predicted by the hypothesis ◦ Data that fall far.
9.1 – The Basics Ch 9 – Testing a Claim. Jack’s a candidate for mayor against 1 other person, so he must gain at least 50% of the votes. Based on a poll.
Introduction Hypothesis testing for one mean Hypothesis testing for one proportion Hypothesis testing for two mean (difference) Hypothesis testing for.
5.1 Chapter 5 Inference in the Simple Regression Model In this chapter we study how to construct confidence intervals and how to conduct hypothesis tests.
Correct decisions –The null hypothesis is true and it is accepted –The null hypothesis is false and it is rejected Incorrect decisions –Type I Error The.
Slide 4- 1 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Active Learning Lecture Slides For use with Classroom Response.
Chap 8-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition Chapter 8 Introduction to Hypothesis.
Copyright ©2013 Pearson Education, Inc. publishing as Prentice Hall 9-1 σ σ.
Hypothesis Testing with One Sample Chapter 7. § 7.1 Introduction to Hypothesis Testing.
Chap 8-1 Fundamentals of Hypothesis Testing: One-Sample Tests.
1 Where we are going : a graphic: Hypothesis Testing. 1 2 Paired 2 or more Means Variances Proportions Categories Slopes Ho: / CI Samples Ho: / CI Ho:
Chapter 9: Testing Hypotheses Overview Research and null hypotheses One and two-tailed tests Type I and II Errors Testing the difference between two means.
Logic and Vocabulary of Hypothesis Tests Chapter 13.
© Copyright McGraw-Hill 2004
Introduction to Hypothesis Testing
Tests of Significance: The Basics ESS chapter 15 © 2013 W.H. Freeman and Company.
Created by Erin Hodgess, Houston, Texas Section 7-1 & 7-2 Overview and Basics of Hypothesis Testing.
C HAPTER 2  Hypothesis Testing -Test for one means - Test for two means -Test for one and two proportions.
Level of Significance Level of significance Your maximum allowable probability of making a type I error. – Denoted by , the lowercase Greek letter alpha.
1 Where we are going : a graphic: Hypothesis Testing. 1 2 Paired 2 or more Means Variances Proportions Categories Slopes Ho: / CI Samples Ho: / CI / CI.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. 1 FINAL EXAMINATION STUDY MATERIAL III A ADDITIONAL READING MATERIAL – INTRO STATS 3 RD EDITION.
Chapter 9 Hypothesis Testing Understanding Basic Statistics Fifth Edition By Brase and Brase Prepared by Jon Booze.
Chapter 9: Hypothesis Tests for One Population Mean 9.1 The Nature of Hypothesis Testing.
© 2010 Pearson Prentice Hall. All rights reserved STA220: Formulating Hypotheses and Setting Up the Rejection Region.
Hypothesis Testing Chapter Hypothesis Testing  Developing Null and Alternative Hypotheses  Type I and Type II Errors  One-Tailed Tests About.
© 2010 Pearson Prentice Hall. All rights reserved Chapter Hypothesis Tests Regarding a Parameter 10.
Ex St 801 Statistical Methods Part 2 Inference about a Single Population Mean (HYP)
Learning Objectives Describe the hypothesis testing process Distinguish the types of hypotheses Explain hypothesis testing errors Solve hypothesis testing.
P-value Approach for Test Conclusion
Chapter 9: Hypothesis Testing
Statistical Test A test of significance is a formal procedure for comparing observed data with a claim (also called a hypothesis) whose truth we want to.
Presentation transcript:

Math 10 Chapter 9 Notes: Hypothesis Testing done constantly in medicine, business, polling, education, etc. to do: set up 2 contradictory statements first statement - often the accepted belief conduct a test to see whether our data supports or does not support the first hypothesis

Math 10 Chapter 9 Notes: Hypothesis Testing Null hypothesis:Ho: Alternate hypothesis:Ha: Example:Ho: John loves Marcia Ha: John does not love Marcia Example:Ho:  = 6 Ha:  < 6

Math 10 Chapter 9 Notes: Hypothesis Testing Decision:Ho is: TrueFalse Do not reject HoCorrectType II DecisionError Reject HoType ICorrect ErrorDecision

Math 10 Chapter 9 Notes: Hypothesis Testing Type I error: Reject the null hypothesis when the null is TRUE. P(Type I error) =  Type II error: Do not reject the null hypothesis when the null is FALSE. P(Type II error) =  Goal: Minimize  and 

Math 10 Chapter 9 Notes: Hypothesis Testing “ =, , or  ” are ALWAYS in the null hypothesis Ho. “ , >, or < ” are ALWAYS in the alternate hypothesis Ha.

Math 10 Chapter 9 Notes: Hypothesis Testing Examples: State the null hypothesis, Ho, and the alternative hypothesis, Ha, in terms of the appropriate parameter (  or p). At most 60% of Americans vote in presidential elections. (Right-Tailed) Ho:p  0.60 Ha:p > 0.60

Math 10 Chapter 9 Notes: Hypothesis Testing Fewer than 5% of adults ride the bus to work in New York City. (Left-tailed) Ho: p  Ha: p < 0.05

Math 10 Chapter 9 Notes: Hypothesis Testing The average number of cars a person owns in his/her lifetime is not more than 10. (Right-tailed) Ho:   10 Ha:  > 10

Math 10 Chapter 9 Notes: Hypothesis Testing Europeans have an average paid vacation each year of six weeks. (Two- tailed) Ho:   10 Ha:   10

Math 10 Chapter 9 Notes: Hypothesis Testing Private universities cost, on average, more than $20,000 per year for tuition, room, and board. (Right-tailed) Ho:   20,000 Ha:   20,000

Math 10 Chapter 9 Notes: Hypothesis Testing What are Type I and Type II errors for some of these problems? Ho:   20,000 Ha:   20,000 Type I: We believe that private universities cost, on average, more than $20,000 per year for tuition, room, and board when, in fact, the average cost is no more than $20,000.

Math 10 Chapter 9 Notes: Hypothesis Testing Ho:   20,000 Ha:   20,000 Type II: We believe that private universities cost, on average, no more than $20,000 per year for tuition, room, and board when, in fact, the average cost is more than $20,000. no more than = at most = less than or equal to

Math 10 Chapter 9 Notes: Hypothesis Testing To perform a hypothesis test: sample data is gathered data typically favors one of the hypotheses Decisions if data favors the null hypothesis (Ho), we “do not reject the null” if data favors the alternate hypothesis (Ha), we “reject the null”

Math 10 Chapter 9 Notes: Hypothesis Testing NOTE: We are ALWAYS testing the null hypothesis, never the alternate. Our conclusion is ALWAYS in regards to the null (Ho). after a decision is made, an appropriate CONCLUSION is made regarding the null hypothesis

Math 10 Chapter 9 Notes: Hypothesis Testing sometimes, data favors neither hypothesis (this implies an “inconclusive” test result) a test may be “left-tailed”, “right- tailed”, or “two-tailed” depending upon the null hypothesis associated with the null hypothesis is a “pre-conceived” . P(Type I error ) = 

Math 10 Chapter 9 Notes: Hypothesis Testing If no pre-conceived a is given, it is common practice to use  = A test may be “left-tailed”, “right-tailed”, or “two-tailed” depending upon the null hypothesis data is collected to calculate what is called the p-value, or level of significance, or calculated 

Math 10 Chapter 9 Notes: Hypothesis Testing p-value = P(the information/data will happen purely by chance GIVEN that the null hypothes is true) decision to reject or to not reject the null is based upon whether  > p-value or  < p-value Reject Ho if  > p-value Do not Reject Ho if  < p-value

Math 10 Chapter 9 Notes: Hypothesis Testing Random Variable: Xbar = average … P’ = proportion … Examples: Xbar = the average tuition for a private college P’ = the proportion of voters who voted for the winning candidate