Lecture 37 Sections 11.1, 11.2, Wed, Nov 4, HampdenSydney College. Paired Samples. Robb T. Koether. Homework Review.


 Dorcas Phelps
 6 days ago
 Views:
Transcription
1 Lecture 37 Sections 11.1, 11.2, 11.3 HampdenSydney College Wed, Nov 4, 2009
2 Outline
3 Outline
4 Exercise 10.21, page 648. The value reported as lost for a random sample of n = 20 pickpocket offenses occurring in a city is given here
5 Exercise 10.21, page 648. (a) Use the data to construct a 95% confidence interval for the mean value lost in all pickpocket offenses for this city. (b) What is the margin of error for the interval estimate in part (a)? (c) Give an interpretation of the interval and of the confidence level.
6 Solution (a) Use the TI83 to find the mean and standard deviation of the sample. x = s = Use the t table to find t 19,0.025 = The confidence interval is ( ) ( ) s x ± t = ± n 20 = ±
7 Solution (b) The margin of error is (c) The interpretation is that if we repeated this procedure many times, about 95% of our confidence intervals would contain the true value of µ.
8 Outline
9 In this chapter we will consider problems that compare two populations.
10 In this chapter we will consider problems that compare two populations. For example, we could compare
11 In this chapter we will consider problems that compare two populations. For example, we could compare The proportion of men who vote Republican the proportion of women who vote Republican. (p 1 p 2.)
12 In this chapter we will consider problems that compare two populations. For example, we could compare The proportion of men who vote Republican the proportion of women who vote Republican. (p 1 p 2.) The average age at which a male first marries the average age at which a female first marries. (µ 1 µ 2.)
13 In this chapter we will consider problems that compare two populations. For example, we could compare The proportion of men who vote Republican the proportion of women who vote Republican. (p 1 p 2.) The average age at which a male first marries the average age at which a female first marries. (µ 1 µ 2.) The bad news: Things will get a bit more complicated.
14 In this chapter we will consider problems that compare two populations. For example, we could compare The proportion of men who vote Republican the proportion of women who vote Republican. (p 1 p 2.) The average age at which a male first marries the average age at which a female first marries. (µ 1 µ 2.) The bad news: Things will get a bit more complicated. The good news: You will not need to memorize any more formulas.
15 Outline
16 Definition (Bivariate data, paired data) Bivariate data are data in which each datum is a pair of observations. These are also called paired data. Typically the two values are called x and y. Definition ( samples, dependent samples) If the data are paired, then the sample of x values and the sample of y values are called paired samples or dependent samples.
17 data are often before and after observations. By comparing the mean before treatment to the mean after treatment, we can determine whether the treatment had an effect. To make direct comparisons of the two samples, they must be measuring the same sort of thing. Clearly, paired samples must be of the same size.
18 Example (HighSchool Graduation Rates) Graduation Rate 2008 Graduation Rates for Richmondarea High Schools High School
19 Example (HighSchool Graduation Rates) Graduation Rate 2009 Graduation Rates for Richmondarea High Schools High School
20 Example (HighSchool Graduation Rates) Graduation Rate Graduation Rates for Richmondarea High Schools High School
21 Example (HighSchool Graduation Rates) Graduation Rate Graduation Rates for Richmondarea High Schools High School
22 Example (HighSchool Graduation Rates) Change in Graduation Rates for Richmondarea High Schools Change ingraduation Rate High School 15
23 Example (HighSchool Graduation Rates) Was there an overall improvement in the graduation rate? That is, is the average difference greater than 0? See the article Va. graduation, dropout rates improve over last year.
24 On the other hand, with independent samples, we simply take one sample from one population and another sample from another population. There is no logical way to pair the data. Furthermore, the independent samples could be of different sizes. In this chapter, we will first study paired data. Then we will study independent samples.
25 Outline
26 Let the pairs be denoted (x 1, x 2 ). Let d = x 2 x 1. We will study the case where d has a normal distribution. Let µ D denote the mean of this distribution and σ D denote the standard deviation.
27 Hypothesis Tests Concerning µ D The only null hypothesis for µ D that we will consider is H 0 : µ D = 0. We will consider any of the three alternatives H 1 : µ D < 0. H 1 : µ D > 0. H 1 : µ D 0.
28 Hypothesis Tests Concerning µ D For large samples, the test statistic is z = d 0 s D / n. For small samples it is necessary that d have a normal distribution. Then the test statistic is t = d 0 s D / n.
29 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) Suppose that a group of 10 students take a math placement test. Let the variable x 1 represent their scores on that test. Then they are given an Algebra refresher course and they retake the placement test. Let the variable x 2 represent their scores on the retest.
30 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) The following table shows the results Student 1st Score (x 1 ) 2nd Score (x 2 ) Difference (d)
31 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) The following table shows the results Student 1st Score (x 1 ) 2nd Score (x 2 ) Difference (d)
32 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) Test the hypothesis, at the 10% level, that the refresher course improved their grades on the placement test.
33 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) (1) Let x 1 be the first test score, let x 2 be the second test score, and let d = x 2 x 1. Then the hypotheses are H 0 : µ D = 0. H 1 : µ D > 0. (2) α = (3) Let t = d 0 s D / n.
34 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) (4) Compute the value of the test statistic. Enter the x 1 values into L 1 and the x 2 values into L 2. Evaluate the difference L 2 L 1 and store it in L 3. Use 1Var Stats L 1 to get d and s D. We find that d = 3 and s D = Then 3 t = 5.354/ 10 = =
35 Hypothesis Tests Concerning µ D Example (Hypothesis Tests Concerning µ D ) (5) pvalue = tcdf(1.772,e99,9) = (6) Reject H 0. (7) Students scores on the placement test are higher after taking the Algebra refresher course.
36 Graduation Rates Example (Graduation Rates ) Test whether there has been a significant change in the graduation rates of the Richmondarea schools from 2008 to 2009.
37 Outline
38 Read Sections 11.1, 11.2, 11.3, pages Let s Do It! 11.1, 11.2, Exercises 18, page 676. Exercises 914, page 689.
39 Answers 2. (a) samples. The was no attempt to pair each male with a female. (b) Perhaps males are more likely to drop courses in which they are having difficulty. (That is pure speculation.) 4. Dogs 2, 7, 8, 9, 10 in one group. The rest in the other group.
40 Answers 6. (a) Collect a sample of sophomores and an independent sample of freshmen. Find the average number of times the members of each sample sought the advice of their advisor. (b) Collect a sample of individuals who have not taken the Kaplan SAT prep course administer to them the SAT test to get their scores. Then have them take the Kaplan prep course. Then readminister the SAT test and see if their scores increased. This would be a paired sample (each person paired with himself, before and after). (c) Collect a sample of males and an independent sample of females. Find the average number of hours per week that each group studies.
41 Answers 8. (a) The placebo effect is the phenomenon of patients improving because they believe they are being given a drug when in fact they are being given a placebo. (b) To eliminate the confounding variable that one group knew it was being given the medication and, without the placebo, the other group would know that it was not being given the medication. (c) samples. There would be no logical way to pair the members. (d) The pvalue would be larger than The report says that the medication had no clinical advantage over a placebo. That is, the results were not significant at the 5% level. (e) H 0 : µ 1 = µ 2. H 1 : µ 1 > µ 2.
42 Answers 10. (a) 12. (a) 14. (a)
Chapter 23 Inferences About Means
Chapter 23 Inferences About Means Chapter 23  Inferences About Means 391 Chapter 23 Solutions to Class Examples 1. See Class Example 1. 2. We want to know if the mean battery lifespan exceeds the 300minute
More informationName: Date: Use the following to answer questions 34:
Name: Date: 1. Determine whether each of the following statements is true or false. A) The margin of error for a 95% confidence interval for the mean increases as the sample size increases. B) The margin
More informationChapter 7 Section 7.1: Inference for the Mean of a Population
Chapter 7 Section 7.1: Inference for the Mean of a Population Now let s look at a similar situation Take an SRS of size n Normal Population : N(, ). Both and are unknown parameters. Unlike what we used
More information1. My placement in calculus was determined by (Mark all that apply): 2. Did you take the SAT exam? 3. My SAT scores were: Page 1
You have been selected to be part of a national survey of calculus instruction in colleges and universities across the United States. This research project is conducted by the Mathematical Association
More informationMath 58. Rumbos Fall 2008 1. Solutions to Review Problems for Exam 2
Math 58. Rumbos Fall 2008 1 Solutions to Review Problems for Exam 2 1. For each of the following scenarios, determine whether the binomial distribution is the appropriate distribution for the random variable
More informationAP * Statistics Review. Designing a Study
AP * Statistics Review Designing a Study Teacher Packet Advanced Placement and AP are registered trademark of the College Entrance Examination Board. The College Board was not involved in the production
More informationSTATISTICS 8, FINAL EXAM. Last six digits of Student ID#: Circle your Discussion Section: 1 2 3 4
STATISTICS 8, FINAL EXAM NAME: KEY Seat Number: Last six digits of Student ID#: Circle your Discussion Section: 1 2 3 4 Make sure you have 8 pages. You will be provided with a table as well, as a separate
More informationFixedEffect Versus RandomEffects Models
CHAPTER 13 FixedEffect Versus RandomEffects Models Introduction Definition of a summary effect Estimating the summary effect Extreme effect size in a large study or a small study Confidence interval
More informationOnline 12  Sections 9.1 and 9.2Doug Ensley
Student: Date: Instructor: Doug Ensley Course: MAT117 01 Applied Statistics  Ensley Assignment: Online 12  Sections 9.1 and 9.2 1. Does a Pvalue of 0.001 give strong evidence or not especially strong
More informationHypothesis Test for Mean Using Given Data (Standard Deviation Knownztest)
Hypothesis Test for Mean Using Given Data (Standard Deviation Knownztest) A hypothesis test is conducted when trying to find out if a claim is true or not. And if the claim is true, is it significant.
More informationMATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS
MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS Instructor: Mark Schilling Email: mark.schilling@csun.edu (Note: If your CSUN email address is not one you use regularly, be sure to set up automatic
More informationStatistics 100A Homework 2 Solutions
Statistics Homework Solutions Ryan Rosario Chapter 9. retail establishment accepts either the merican Express or the VIS credit card. total of percent of its customers carry an merican Express card, 6
More informationSPSS Resources. 1. See website (readings) for SPSS tutorial & Stats handout
Analyzing Data SPSS Resources 1. See website (readings) for SPSS tutorial & Stats handout Don t have your own copy of SPSS? 1. Use the libraries to analyze your data 2. Download a trial version of SPSS
More informationChi Square Distribution
17. Chi Square A. Chi Square Distribution B. OneWay Tables C. Contingency Tables D. Exercises Chi Square is a distribution that has proven to be particularly useful in statistics. The first section describes
More informationUniversity of Chicago Graduate School of Business. Business 41000: Business Statistics Solution Key
Name: OUTLINE SOLUTIONS University of Chicago Graduate School of Business Business 41000: Business Statistics Solution Key Special Notes: 1. This is a closedbook exam. You may use an 8 11 piece of paper
More informationIn the past, the increase in the price of gasoline could be attributed to major national or global
Chapter 7 Testing Hypotheses Chapter Learning Objectives Understanding the assumptions of statistical hypothesis testing Defining and applying the components in hypothesis testing: the research and null
More informationHypothesis Testing. Steps for a hypothesis test:
Hypothesis Testing Steps for a hypothesis test: 1. State the claim H 0 and the alternative, H a 2. Choose a significance level or use the given one. 3. Draw the sampling distribution based on the assumption
More informationCHAPTER IV FINDINGS AND CONCURRENT DISCUSSIONS
CHAPTER IV FINDINGS AND CONCURRENT DISCUSSIONS Hypothesis 1: People are resistant to the technological change in the security system of the organization. Hypothesis 2: information hacked and misused. Lack
More informationSTAT 145 (Notes) Al Nosedal anosedal@unm.edu Department of Mathematics and Statistics University of New Mexico. Fall 2013
STAT 145 (Notes) Al Nosedal anosedal@unm.edu Department of Mathematics and Statistics University of New Mexico Fall 2013 CHAPTER 18 INFERENCE ABOUT A POPULATION MEAN. Conditions for Inference about mean
More informationSTAT 360 Probability and Statistics. Fall 2012
STAT 360 Probability and Statistics Fall 2012 1) General information: Crosslisted course offered as STAT 360, MATH 360 Semester: Fall 2012, Aug 20Dec 07 Course name: Probability and Statistics Number
More informationAttitudes Toward Science of Students Enrolled in Introductory Level Science Courses at UWLa Crosse
Attitudes Toward Science of Students Enrolled in Introductory Level Science Courses at UWLa Crosse Dana E. Craker Faculty Sponsor: Abdulaziz Elfessi, Department of Mathematics ABSTRACT Nearly fifty percent
More informationLAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE
LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre
More informationUnit 27: Comparing Two Means
Unit 27: Comparing Two Means Prerequisites Students should have experience with onesample tprocedures before they begin this unit. That material is covered in Unit 26, Small Sample Inference for One
More informationSTATISTICS 8: CHAPTERS 7 TO 10, SAMPLE MULTIPLE CHOICE QUESTIONS
STATISTICS 8: CHAPTERS 7 TO 10, SAMPLE MULTIPLE CHOICE QUESTIONS 1. If two events (both with probability greater than 0) are mutually exclusive, then: A. They also must be independent. B. They also could
More informationValidity of Selection Criteria in Predicting MBA Success
Validity of Selection Criteria in Predicting MBA Success Terry C. Truitt Anderson University Abstract GMAT scores are found to be a robust predictor of MBA academic performance. Very little support is
More informationSchool of Mathematics and Science MATH 153 Introduction to Statistical Methods Section: WE1 & WE2
CCBC Essex School of Mathematics and Science MATH 153 Introduction to Statistical Methods Section: WE1 & WE2 CLASSROOM LOCATION: SEMESTER: Fall 2009 INSTRUCTOR: DONNA TUPPER OFFICE LOCATION: F413 (or
More informationIntroduction to Statistics and Quantitative Research Methods
Introduction to Statistics and Quantitative Research Methods Purpose of Presentation To aid in the understanding of basic statistics, including terminology, common terms, and common statistical methods.
More informationCRITICAL THINKING ASSESSMENT
CRITICAL THINKING ASSESSMENT REPORT Prepared by Byron Javier Assistant Dean of Research and Planning 1 P a g e Critical Thinking Assessment at MXC As part of its assessment plan, the Assessment Committee
More informationCHAPTER 13 SIMPLE LINEAR REGRESSION. Opening Example. Simple Regression. Linear Regression
Opening Example CHAPTER 13 SIMPLE LINEAR REGREION SIMPLE LINEAR REGREION! Simple Regression! Linear Regression Simple Regression Definition A regression model is a mathematical equation that descries the
More informationBusiness Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.
Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationFew things are more feared than statistical analysis.
DATA ANALYSIS AND THE PRINCIPALSHIP Datadriven decision making is a hallmark of good instructional leadership. Principals and teachers can learn to maneuver through the statistcal data to help create
More informationReview. March 21, 2011. 155S7.1 2_3 Estimating a Population Proportion. Chapter 7 Estimates and Sample Sizes. Test 2 (Chapters 4, 5, & 6) Results
MAT 155 Statistical Analysis Dr. Claude Moore Cape Fear Community College Chapter 7 Estimates and Sample Sizes 7 1 Review and Preview 7 2 Estimating a Population Proportion 7 3 Estimating a Population
More informationADVICE FOR NEW COMPUTER SCIENCE MAJORS
ADVICE FOR NEW COMPUTER SCIENCE MAJORS This document contains advice to new computer science majors about what courses they should take in their first semester at CSU Stanislaus. The student should go
More informationTruman CollegeMathematics Department Math 125CD: Introductory Statistics Course Syllabus Fall 2012
Instructor: Dr. Abdallah Shuaibi Office #: 3816 Email: ashuaibi1@ccc.edu URL: http://faculty.ccc.edu/ashuaibi/ Phone #: (773)9074085 Office Hours: Truman CollegeMathematics Department Math 125CD: Introductory
More informationMultivariate Analysis of Variance (MANOVA): I. Theory
Gregory Carey, 1998 MANOVA: I  1 Multivariate Analysis of Variance (MANOVA): I. Theory Introduction The purpose of a t test is to assess the likelihood that the means for two groups are sampled from the
More informationUniversity of Chicago Graduate School of Business. Business 41000: Business Statistics
Name: University of Chicago Graduate School of Business Business 41000: Business Statistics Special Notes: 1. This is a closedbook exam. You may use an 8 11 piece of paper for the formulas. 2. Throughout
More informationChapter 13 Introduction to Linear Regression and Correlation Analysis
Chapter 3 Student Lecture Notes 3 Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing
More informationSTAT 2300: BUSINESS STATISTICS Section 002, Summer Semester 2009
STAT 2300: BUSINESS STATISTICS Section 002, Summer Semester 2009 Instructor: Bill Welbourn Office: Lund 117 Email: bill.welbourn@aggiemail.usu.edu Lectures: MWF 7:30AM 9:40AM in ENGR 104 Office Hours:
More informationSolutions to Homework 6 Statistics 302 Professor Larget
s to Homework 6 Statistics 302 Professor Larget Textbook Exercises 5.29 (Graded for Completeness) What Proportion Have College Degrees? According to the US Census Bureau, about 27.5% of US adults over
More informationCourse Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics
Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGrawHill/Irwin, 2010, ISBN: 9780077384470 [This
More informationChapter 9: TwoSample Inference
Chapter 9: TwoSample Inference Chapter 7 discussed methods of hypothesis testing about onepopulation parameters. Chapter 8 discussed methods of estimating population parameters from one sample using
More informationStatistics 151 Practice Midterm 1 Mike Kowalski
Statistics 151 Practice Midterm 1 Mike Kowalski Statistics 151 Practice Midterm 1 Multiple Choice (50 minutes) Instructions: 1. This is a closed book exam. 2. You may use the STAT 151 formula sheets and
More informationChapter 9. TwoSample Tests. Effect Sizes and Power Paired t Test Calculation
Chapter 9 TwoSample Tests Paired t Test (Correlated Groups t Test) Effect Sizes and Power Paired t Test Calculation Summary Independent t Test Chapter 9 Homework Power and TwoSample Tests: Paired Versus
More informationThe Math. P (x) = 5! = 1 2 3 4 5 = 120.
The Math Suppose there are n experiments, and the probability that someone gets the right answer on any given experiment is p. So in the first example above, n = 5 and p = 0.2. Let X be the number of correct
More informationHigh School Statistics and Probability Common Core Sample Test Version 2
High School Statistics and Probability Common Core Sample Test Version 2 Our High School Statistics and Probability sample test covers the twenty most common questions that we see targeted for this level.
More informationEvaluating a Retest Policy at a North American University
Journal of the National College Testing Association 2015/Volume 1/Issue 1 Evaluating a Retest Policy at a North American University CINDY L. JAMES, PhD Thompson Rivers University Retesting for admission
More informationBiostatistics: Types of Data Analysis
Biostatistics: Types of Data Analysis Theresa A Scott, MS Vanderbilt University Department of Biostatistics theresa.scott@vanderbilt.edu http://biostat.mc.vanderbilt.edu/theresascott Theresa A Scott, MS
More informationBest Practices for Helping All Students Get Ready for the SAT. Prepared for Idaho SDE January 2014
Best Practices for Helping All Students Get Ready for the SAT Prepared for Idaho SDE January 2014 SAT Readiness Program Agenda: SAT Introduction SAT Preparation The Official SAT Online Course PSAT Participation
More informationTEACHING PRINCIPLES OF ECONOMICS: INTERNET VS. TRADITIONAL CLASSROOM INSTRUCTION
21 TEACHING PRINCIPLES OF ECONOMICS: INTERNET VS. TRADITIONAL CLASSROOM INSTRUCTION Doris S. Bennett, Jacksonville State University Gene L. Padgham, Jacksonville State University Cynthia S. McCarty, Jacksonville
More informationChapter 8 Section 1. Homework A
Chapter 8 Section 1 Homework A 8.7 Can we use the largesample confidence interval? In each of the following circumstances state whether you would use the largesample confidence interval. The variable
More informationBIOM611 Biological Data Analysis
BIOM611 Biological Data Analysis Spring, 2015 Tentative Syllabus Introduction BIOMED611 is a ½ unit course required for all 1 st year BGS students (except GCB students). It will provide an introduction
More informationAugust 2012 EXAMINATIONS Solution Part I
August 01 EXAMINATIONS Solution Part I (1) In a random sample of 600 eligible voters, the probability that less than 38% will be in favour of this policy is closest to (B) () In a large random sample,
More informationUnderstanding Confidence Intervals and Hypothesis Testing Using Excel Data Table Simulation
Understanding Confidence Intervals and Hypothesis Testing Using Excel Data Table Simulation Leslie Chandrakantha lchandra@jjay.cuny.edu Department of Mathematics & Computer Science John Jay College of
More informationA POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
CHAPTER 5. A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING 5.1 Concepts When a number of animals or plots are exposed to a certain treatment, we usually estimate the effect of the treatment
More informationAmerican Views of Churches in Schools. Survey of Over 2,000 American Adults
American Views of Churches in Schools Survey of Over 2,000 American Adults 2 Methodology The online survey of adult Americans was conducted January 20 24, 2012 A sample of an online panel representing
More informationAP Statistics 2010 Scoring Guidelines
AP Statistics 2010 Scoring Guidelines The College Board The College Board is a notforprofit membership association whose mission is to connect students to college success and opportunity. Founded in
More informationCell Phone Impairment?
Cell Phone Impairment? Overview of Lesson This lesson is based upon data collected by researchers at the University of Utah (Strayer and Johnston, 2001). The researchers asked student volunteers (subjects)
More informationA HandsOn Exercise Improves Understanding of the Standard Error. of the Mean. Robert S. Ryan. Kutztown University
A HandsOn Exercise 1 Running head: UNDERSTANDING THE STANDARD ERROR A HandsOn Exercise Improves Understanding of the Standard Error of the Mean Robert S. Ryan Kutztown University A HandsOn Exercise
More informationSection 1.3 Exercises (Solutions)
Section 1.3 Exercises (s) 1.109, 1.110, 1.111, 1.114*, 1.115, 1.119*, 1.122, 1.125, 1.127*, 1.128*, 1.131*, 1.133*, 1.135*, 1.137*, 1.139*, 1.145*, 1.146148. 1.109 Sketch some normal curves. (a) Sketch
More informationBasic Probability Theory II
RECAP Basic Probability heory II Dr. om Ilvento FREC 408 We said the approach to establishing probabilities for events is to Define the experiment List the sample points Assign probabilities to the sample
More informationAn analysis method for a quantitative outcome and two categorical explanatory variables.
Chapter 11 TwoWay ANOVA An analysis method for a quantitative outcome and two categorical explanatory variables. If an experiment has a quantitative outcome and two categorical explanatory variables that
More information9 Testing the Difference
blu49076_ch09.qxd 5/1/2003 8:19 AM Page 431 c h a p t e r 9 9 Testing the Difference Between Two Means, Two Variances, and Two Proportions Outline 9 1 Introduction 9 2 Testing the Difference Between Two
More informationCOLLEGE PREPARATION QUESTIONNAIRE
COLLEGE PREPARATION QUESTIONNAIRE A. High School Attended: B. Month and year graduated from high school: C. I was enrolled in college track classes during high school (select one): Yes: No: D. Gender:
More informationChapter Study Guide. Chapter 11 Confidence Intervals and Hypothesis Testing for Means
OPRE504 Chapter Study Guide Chapter 11 Confidence Intervals and Hypothesis Testing for Means I. Calculate Probability for A Sample Mean When Population σ Is Known 1. First of all, we need to find out the
More informationUnit 26: Small Sample Inference for One Mean
Unit 26: Small Sample Inference for One Mean Prerequisites Students need the background on confidence intervals and significance tests covered in Units 24 and 25. Additional Topic Coverage Additional coverage
More informationDefinition: Suppose that two random variables, either continuous or discrete, X and Y have joint density
HW MATH 461/561 Lecture Notes 15 1 Definition: Suppose that two random variables, either continuous or discrete, X and Y have joint density and marginal densities f(x, y), (x, y) Λ X,Y f X (x), x Λ X,
More informationWhen to Use a Particular Statistical Test
When to Use a Particular Statistical Test Central Tendency Univariate Descriptive Mode the most commonly occurring value 6 people with ages 21, 22, 21, 23, 19, 21  mode = 21 Median the center value the
More informationa) Find the five point summary for the home runs of the National League teams. b) What is the mean number of home runs by the American League teams?
1. Phone surveys are sometimes used to rate TV shows. Such a survey records several variables listed below. Which ones of them are categorical and which are quantitative?  the number of people watching
More information3. There are three senior citizens in a room, ages 68, 70, and 72. If a seventyyearold person enters the room, the
TMTA Statistics Exam 2011 1. Last month, the mean and standard deviation of the paychecks of 10 employees of a small company were $1250 and $150, respectively. This month, each one of the 10 employees
More informationMINITAB ASSISTANT WHITE PAPER
MINITAB ASSISTANT WHITE PAPER This paper explains the research conducted by Minitab statisticians to develop the methods and data checks used in the Assistant in Minitab 17 Statistical Software. OneWay
More informationIntroduction to Statistics Using the TI83 Graphing Calculator. Dr. Robert Knight
Introduction to Statistics Using the TI83 Graphing Calculator By Dr. Robert Knight This document is a working text that is designed specifically for the course of Introductory Statistics that I teach.
More informationIntroduction to Linear Regression
14. Regression A. Introduction to Simple Linear Regression B. Partitioning Sums of Squares C. Standard Error of the Estimate D. Inferential Statistics for b and r E. Influential Observations F. Regression
More informationProceedings of the Annual Meeting of the American Statistical Association, August 59, 2001 WORK EXPERIENCE: DETERMINANT OF MBA ACADEMIC SUCCESS?
Proceedings of the Annual Meeting of the American Statistical Association, August 59, 2001 WORK EXPERIENCE: DETERMINANT OF MBA ACADEMIC SUCCESS? Andrew Braunstein, Iona College Hagan School of Business,
More informationOneWay Analysis of Variance
OneWay Analysis of Variance Note: Much of the math here is tedious but straightforward. We ll skim over it in class but you should be sure to ask questions if you don t understand it. I. Overview A. We
More informationLecture 14. Chapter 7: Probability. Rule 1: Rule 2: Rule 3: Nancy Pfenning Stats 1000
Lecture 4 Nancy Pfenning Stats 000 Chapter 7: Probability Last time we established some basic definitions and rules of probability: Rule : P (A C ) = P (A). Rule 2: In general, the probability of one event
More informationIntroduction to Estimation
10. Estimation A. Introduction B. Degrees of Freedom C. Characteristics of Estimators D. Confidence Intervals 1. Introduction 2. Confidence Interval for the Mean 3. t distribution 4. Confidence Interval
More informationTesting Group Differences using Ttests, ANOVA, and Nonparametric Measures
Testing Group Differences using Ttests, ANOVA, and Nonparametric Measures Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 354870348 Phone:
More informationInferential Statistics. What are they? When would you use them?
Inferential Statistics What are they? When would you use them? What are inferential statistics? Why learn about inferential statistics? Why use inferential statistics? When are inferential statistics utilized?
More informationPsychology 209 OnLine Measurement and Statistics Winter 2010
Page 1 of 13 Course Organization Psychology 209 OnLine Measurement and Statistics Winter 2010 Instructor Professor Hoffman Department of Psychology 213 Wolf Hall 3028312453 hoffman@udel.edu Web site:
More informationJohnson County Community College
Johnson County Community College Course Syllabus Mathematics Division Math 115: Elementary Algebra Section 450 (SelfPaced) Fall 2015 (CRN 80682) Instructor Information Primary Instructor: Mary Deas Campus
More informationCOLLEGE ALGEBRA IN CONTEXT: Redefining the College Algebra Experience
COLLEGE ALGEBRA IN CONTEXT: Redefining the College Algebra Experience Ronald J. HARSHBARGER, Ph.D. Lisa S. YOCCO University of South Carolina Beaufort Georgia Southern University 1 College Center P.O.
More informationWorking with SPSS. A StepbyStep Guide For Prof PJ s ComS 171 students
Working with SPSS A StepbyStep Guide For Prof PJ s ComS 171 students Contents Prep the Excel file for SPSS... 2 Prep the Excel file for the online survey:... 2 Make a master file... 2 Clean the data
More informationBinary Diagnostic Tests Two Independent Samples
Chapter 537 Binary Diagnostic Tests Two Independent Samples Introduction An important task in diagnostic medicine is to measure the accuracy of two diagnostic tests. This can be done by comparing summary
More informationFigure 1.1 Percentage of persons without health insurance coverage: all ages, United States, 19972001
Figure 1.1 Percentage of persons without health insurance coverage: all ages, United States, 19972001 DATA SOURCE: Family Core component of the 19972001 National Health Interview Surveys. The estimate
More informationOklahoma City Community College Academic Division of Business BUS 2023 BUSINESS STATISTICS
Oklahoma City Community College Academic Division of Business BUS 2023 BUSINESS STATISTICS Course/ Meeting information Semester: Fall 2014 Section: TR01F Meeting Times: 5:30 PM Thursdays Location: 2N5
More informationStats for Strategy Fall 2012 FirstDiscussion Handout: Stats Using Calculators and MINITAB
Stats for Strategy Fall 2012 FirstDiscussion Handout: Stats Using Calculators and MINITAB DIRECTIONS: Welcome! Your TA will help you apply your Calculator and MINITAB to review Business Stats, and will
More informationRecall this chart that showed how most of our course would be organized:
Chapter 4 OneWay ANOVA Recall this chart that showed how most of our course would be organized: Explanatory Variable(s) Response Variable Methods Categorical Categorical Contingency Tables Categorical
More informationStatistics in Retail Finance. Chapter 2: Statistical models of default
Statistics in Retail Finance 1 Overview > We consider how to build statistical models of default, or delinquency, and how such models are traditionally used for credit application scoring and decision
More informationTesting for College Admission
Chapter 4 Testing for College Admission S tandardized testing is an important factor in admission decisions, especially at most of the highly selective colleges and universities. A few institutions have
More informationHypothesis Tests for 1 sample Proportions
Hypothesis Tests for 1 sample Proportions 1. Hypotheses. Write the null and alternative hypotheses you would use to test each of the following situations. a) A governor is concerned about his "negatives"
More informationA 58% majority of voters also say they would favor allowing medical marijuana dispensaries to operate in the city or town where they live.
THE FIELD POLL THE INDEPENDENT AND NONPARTISAN SURVEY OF PUBLIC OPINION ESTABLISHED IN 1947 AS THE CALIFORNIA POLL BY MERVIN FIELD Field Research Corporation 601 California Street, Suite 900 San Francisco,
More informationSimple Linear Regression
STAT 101 Dr. Kari Lock Morgan Simple Linear Regression SECTIONS 9.3 Confidence and prediction intervals (9.3) Conditions for inference (9.1) Want More Stats??? If you have enjoyed learning how to analyze
More informationsocscimajor yes no TOTAL female 25 35 60 male 30 27 57 TOTAL 55 62 117
Review for Final Stat 10 (1) The table below shows data for a sample of students from UCLA. (a) What percent of the sampled students are male? 57/117 (b) What proportion of sampled students are social
More informationWhat High School Curricular Experience Tells Us About College Success *****
What High School Curricular Experience Tells Us About College Success ***** Serge Herzog, PhD Director, Institutional Analysis Consultant, CRDA Statlab University of Nevada, Reno Reno, NV 89557 Serge@unr.edu
More informationMath 58. Rumbos Fall 2008 1. Solutions to Assignment #3
Math 58. Rumbos Fall 2008 1 Solutions to Assignment #3 1. Use randomization to test the null hypothesis that there is no difference between calcium supplementation and a placebo for the experimental data
More informationTIME SERIES ANALYSIS
DEPARTMENT OF POLITICAL SCIENCE AND INTERNATIONAL RELATIONS Posc/Uapp 816 TIME SERIES ANALYSIS I. AGENDA: A. Correction B. Time series C. Reading: Agresti and Finlay Statistical Methods in the Social Sciences,
More informationObjectives Method Instrument Sample
As part of the process improvement initiative, the Office of Institutional Research & Assessment (OIRA) administered in October 2012 a survey that evaluates student satisfaction with the fall 201213 registration
More information11. Analysis of Casecontrol Studies Logistic Regression
Research methods II 113 11. Analysis of Casecontrol Studies Logistic Regression This chapter builds upon and further develops the concepts and strategies described in Ch.6 of Mother and Child Health:
More informationwww.rmsolutions.net R&M Solutons
Ahmed Hassouna, MD Professor of cardiovascular surgery, AinShams University, EGYPT. Diploma of medical statistics and clinical trial, Paris 6 university, Paris. 1A Choose the best answer The duration
More informationStat 704 Data Analysis I Probability Review
1 / 30 Stat 704 Data Analysis I Probability Review Timothy Hanson Department of Statistics, University of South Carolina Course information 2 / 30 Logistics: Tuesday/Thursday 11:40am to 12:55pm in LeConte
More information