1 Statistical Inference: A Review of Chapters 12 and 13 Chapter 14.

Slides:



Advertisements
Similar presentations
CHAPTER 21 Inferential Statistical Analysis. Understanding probability The idea of probability is central to inferential statistics. It means the chance.
Advertisements

1 Chapter 12 Inference About One Population Introduction In this chapter we utilize the approach developed before to describe a population.In.
6-1 Introduction To Empirical Models 6-1 Introduction To Empirical Models.
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc Chapter 14 Statistical Inference: Review of Chapters 12 & 13.
BINF 702 Spring 2014 Practice Problems Practice Problems BINF 702 Practice Problems.
Chapter 10 Comparisons Involving Means Part A Estimation of the Difference between the Means of Two Populations: Independent Samples Hypothesis Tests about.
Business and Economics 9th Edition
Statistics for Managers Using Microsoft Excel, 5e © 2008 Prentice-Hall, Inc.Chap 10-1 Statistics for Managers Using Microsoft® Excel 5th Edition Chapter.
Chapter 10 Two-Sample Tests
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 7 th Edition Chapter 10 Hypothesis Testing:
PSY 307 – Statistics for the Behavioral Sciences
Statistics Sample: Descriptive Statistics Population: Inferential Statistics.
Lesson #22 Inference for Two Independent Means. Two independent samples: Again interested in (  1 –  2 ) n1n1 n2n2 Use to estimate (  1 –  2 )
Chap 11-1 Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chapter 11 Hypothesis Testing II Statistics for Business and Economics.
1 Inference about Comparing Two Populations Chapter 13.
Lecture Inference for a population mean when the stdev is unknown; one more example 12.3 Testing a population variance 12.4 Testing a population.
1/45 Chapter 11 Hypothesis Testing II EF 507 QUANTITATIVE METHODS FOR ECONOMICS AND FINANCE FALL 2008.
1 Inference about Comparing Two Populations Chapter 13.
Chapter 19 Data Analysis Overview
A Decision-Making Approach
Lecture 9 Inference about the ratio of two variances (Chapter 13.5)
Business Statistics: A Decision-Making Approach, 7e © 2008 Prentice-Hall, Inc. Chap 10-1 Business Statistics: A Decision-Making Approach 7 th Edition Chapter.
Chapter 2 Simple Comparative Experiments
Testing the Difference Between Means (Small Independent Samples)
1 Inference About a Population Variance Sometimes we are interested in making inference about the variability of processes. Examples: –Investors use variance.
Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall 18-1 Chapter 18 Data Analysis Overview Statistics for Managers using Microsoft Excel.
Hypothesis Testing Using The One-Sample t-Test
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 10-1 Chapter 10 Two-Sample Tests Basic Business Statistics 10 th Edition.
Economics 173 Business Statistics Lecture 8 Fall, 2001 Professor J. Petry
Hypothesis Testing and T-Tests. Hypothesis Tests Related to Differences Copyright © 2009 Pearson Education, Inc. Chapter Tests of Differences One.
Chapter 9 Two-Sample Tests Part II: Introduction to Hypothesis Testing Renee R. Ha, Ph.D. James C. Ha, Ph.D Integrative Statistics for the Social & Behavioral.
Overview of Statistical Hypothesis Testing: The z-Test
5-1 Introduction 5-2 Inference on the Means of Two Populations, Variances Known Assumptions.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 11 Section 2 – Slide 1 of 25 Chapter 11 Section 2 Inference about Two Means: Independent.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Chapter 9 Hypothesis Testing and Estimation for Two Population Parameters.
Hypothesis Testing Using the Two-Sample t-Test
Economics 173 Business Statistics Lecture 7 Fall, 2001 Professor J. Petry
Chapter 13 Inference About Comparing Two Populations.
1 Inference about Two Populations Chapter Introduction Variety of techniques are presented to compare two populations. We are interested in:
© 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
Industrial Statistics 2
Chapter 13 Inference About Comparing Two Populations.
Example (which tire lasts longer?) To determine whether a new steel-belted radial tire lasts longer than a current model, the manufacturer designs the.
Economics 173 Business Statistics Lecture 10b © Spring 2002, Professor J. Petry
1 Nonparametric Statistical Techniques Chapter 17.
Lecture 8 Matched Pairs Review –Summary –The Flow approach to problem solving –Example.
1 Inference about Two Populations Chapter Introduction Variety of techniques are presented whose objective is to compare two populations. We.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 14 Comparing Groups: Analysis of Variance Methods Section 14.1 One-Way ANOVA: Comparing.
AP Statistics Chapter 24 Comparing Means.
Chapter Twelve The Two-Sample t-Test. Copyright © Houghton Mifflin Company. All rights reserved.Chapter is the mean of the first sample is the.
Inferential Statistics. The Logic of Inferential Statistics Makes inferences about a population from a sample Makes inferences about a population from.
to accompany Introduction to Business Statistics
Chap 18-1 Copyright ©2012 Pearson Education, Inc. publishing as Prentice Hall Chap 18-1 Chapter 18 A Roadmap for Analyzing Data Basic Business Statistics.
Statistical Inference Drawing conclusions (“to infer”) about a population based upon data from a sample. Drawing conclusions (“to infer”) about a population.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 11 Section 1 – Slide 1 of 26 Chapter 11 Section 1 Inference about Two Means: Dependent Samples.
1 Economics 173 Business Statistics Lectures 5 & 6 Summer, 2001 Professor J. Petry.
Chapter 9 Inferences Based on Two Samples: Confidence Intervals and Tests of Hypothesis.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 11 Section 3 – Slide 1 of 27 Chapter 11 Section 3 Inference about Two Population Proportions.
Lecture 8 Estimation and Hypothesis Testing for Two Population Parameters.
10-1 Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall Chapter 10 Two-Sample Tests Statistics for Managers using Microsoft Excel 6 th.
Chapter 12 Inference About One Population. We shall develop techniques to estimate and test three population parameters.  Population mean   Population.
1 Nonparametric Statistical Techniques Chapter 18.
Chapter 18 Data Analysis Overview Yandell – Econ 216 Chap 18-1.
One-Sample Inference for Proportions
Inference about Two Populations
Inference about Comparing Two Populations
Lecture Slides Elementary Statistics Twelfth Edition
Towson University - J. Jung
PARAMETRIC TESTS t-tests (parametric, interval and ratio data)
Presentation transcript:

1 Statistical Inference: A Review of Chapters 12 and 13 Chapter 14

Introduction In this chapter we build a framework that helps decide which technique (or techniques) should be used in solving a problem. Logical flow chart of techniques for Chapters 12 and 13 is presented next.

3 Problem objective? Describe a populationCompare two populations Data type? Interval Nominal Interval Nominal Type of descriptive measurement? Type of descriptive measurement? Z test & estimator of p Z test & estimator of p Z test & estimator of p 1 -p 2 Z test & estimator of p 1 -p 2 Central location Variability Central location Variability t- test & estimator of  t- test & estimator of    - test & estimator of  2   - test & estimator of  2 F- test & estimator of   2 /   2 F- test & estimator of   2 /   2 Experimental design? Continue Summary

4 Continue t- test & estimator of  1 -  2 (Unequal variances) t- test & estimator of  1 -  2 (Unequal variances) Population variances? t- test & estimator of  D t- test & estimator of  D t- test & estimator of  1 -  2 (Equal variances) t- test & estimator of  1 -  2 (Equal variances) Independent samplesMatched pairs Experimental design? Unequal Equal

5 Identifying the appropriate technique Example 14.1 –Is the antilock braking system (ABS) really effective? –Two aspects of the effectiveness were examined: The number of accidents. Cost of repair when accidents do occur. –An experiment was conducted as follows: 500 cars with ABS and 500 cars without ABS were randomly selected. For each car it was recorded whether the car was involved in an accident. If a car was involved with an accident, the cost of repair was recorded.

6 Example – continued –Data 42 cars without ABS had an accident, 38 cars equipped with ABS had an accident The costs of repairs were recorded (see Xm14-01).Xm14-01 –Can we conclude that ABS is effective? Identifying the appropriate technique

7 Solution – Question 1: Is there sufficient evidence to infer that the accident rate is lower in ABS equipped cars than in cars without ABS? – Question 2: Is there sufficient evidence to infer that the cost of repairing accident damage in ABS equipped cars is less than that of cars without ABS? – Question 3: How much cheaper is it to repair ABS equipped cars than cars without ABS? Identifying the appropriate technique

8 Question 1: Compare the accident rates Solution – continued Problem objective? Describing a single populationCompare two populations Data type? Interval Nominal Z test & estimator of p 1 -p 2 Z test & estimator of p 1 -p 2 A car had an accident: Yes / No

9 Solution – continued –p 1 = proportion of cars without ABS involved with an accident p 2 = proportion of cars with ABS involved with an accident –The hypotheses test H 0 : p 1 – p 2 = 0 H 1 : p 1 – p 2 > 0 Use case 1 test statistic Question 1: Compare the accident rates

10 Solution – continued –Use Test Statistics workbook: z-Test_2 Proportions(Case 1) worksheet 42   500 Do not reject H 0. Question 1: Compare the accident rates

11 Question 2: Compare the mean repair costs per accident Solution - continued Problem objective? Describing a single populationCompare two populations Data type? Interval Nominal Type of descriptive measurements? Central location Variability Cost of repair per accident

12 Equal Solution - continued Population variances equal? Independent samplesMatched pairs Unequal Experimental design? Central location t- test & estimator of  1 -  2 (Equal variances) t- test & estimator of  1 -  2 (Equal variances) Run the F test for the ratio of two variances. Equal Question 2: Compare the mean repair costs per accident

13 Solution – continued –  1 = mean cost of repairing cars without ABS  2 = mean cost of repairing cars with ABS –The hypotheses tested H 0 :  1 –  2 = 0 H 1 :  1 –  2 > 0 –For the equal variance case we use Question 2: Compare the mean repair costs per accident

14 Solution – continued –To determine whether the population variances differ we apply the F test –From Excel Data Analysis we have (Xm14-01)Xm14-01 Do not reject H 0. There is insufficient evidence to conclude that the two variances are unequal. Question 2: Compare the mean repair costs per accident

15 Solution – continued –Assuming the variances are really equal we run the equal-variances t-test of the difference between two means At 5% significance level there is sufficient evidence to infer that the cost of repairs after accidents for cars with ABS is smaller than the cost of repairs for cars without ABS. Question 2: Compare the mean repair costs per accident

16 Checking required conditions The two populations should be normal (or at least not extremely nonnormal)

17 Question 3: Estimate the difference in repair costs Solution –Use Estimators Workbook: t-Test_2 Means (Eq-Var) worksheet We estimate that the cost of repairing a car not equipped with ABS is between $71 and $651 more expensive than to repair an ABS equipped car.