MATHEMATICS LW Quantitative Methods II Martin Huard Friday April 26, 2013 TEST # 4 SOLUTIONS
|
|
- Amos Roberts
- 5 years ago
- Views:
Transcription
1 ATHATICS L Quatitative ethod II arti Huard Friday April 6, 013 TST # 4 SOLUTIONS Name: Awer all quetio ad how all your work. Quetio 1 (10 poit) To oberve the effect drikig a Red Bull ha o cocetratio, a pychologit gave a tet that meaure cocetratio to a radom group of 5 adult (with reult o a cale of 1 to 0, where a higher core idicate a higher level of cocetratio) before ad after drikig a Red Bull. Here are the reult. Before After d = A - B 3-6 Ca you coclude, at the 5% level of igificace, that drikig a Red Bull improve cocetratio? Ue the p-value approach. Aume that cocetratio core are ormally ditributed. Step 1 Aumptio: XB NB, B XA NA, A = 0.05 Step H : 0 0 d H A: d 0 Right-tailed tet d d. 0 t d p value Step 4 p-value > > 0.05 d d thu t Fail to reject H 0. There i ot ufficiet evidece at the 5% level of igificace to coclude that drikig Red Bull improve cocetratio. d t 4
2 Tet 4 - Solutio Quetio (10 poit) I order to look ito the tudy habit of CGP tudet, a ociologit took a radom ample of 15 tudet i their firt emeter ad aother radom ample of 16 tudet i their lat emeter, to oberve the differece i the umber of hour pet tudyig durig a week. I the ample with firt emeter tudet, the mea umber of hour tudied wa 7.3 with a tadard deviatio of 3.7 ad for the ample with the lat emeter tudet, the mea wa 9.5 hour with a tadard deviatio of 4.1 hour. Cotruct a 95% cofidece iterval for the differece i the mea umber of hour tudied i a week by firt ad lat emeter tudet. Aume that the umber of hour tudied durig a week i ormally ditributed. Step 1 Aumptio: The ample are idepedet 1 X X N N,, thu t Level of cofidece: , 0.05 Step Poit etimate: xl xf hour a) t t, 9, df Step 4 b) p x x 1 1 p 1 L 1 L F 1 F L F t , p df c) x x x x The 95% cofidece iterval for the differece i the mea umber of hour tudied i a week by firt ad lat emeter tudet i hour to 5.08 hour. t 9 iter 013 arti Huard
3 Tet 4 - Solutio Quetio 3 (10 poit) I a urvey of 900 me ad 600 wome, 45 me ad 50 wome aid they will watch at leat oe game of the hockey playoff. At the % level of igificace, ca you coclude that the proportio of me who watch at leat oe game of the playoff i differet tha the proportio of wome? Ue the claical approach. Step 1 Aumptio: pˆ 45 5 qˆ ˆ 50 5 ˆ p q Sample are idepedet. Thu pˆ ˆ p N 0, pq 1 = 0.0 Step H : 0 p p 0 Step 4 H A : p p 0 Two-tailed tet z z pˆ p pˆ ˆ p z pq ˆ ˆ p p a) z i ot i the critical regio b) Fail to reject H o. There i iufficiet evidece at the % level of igificace to coclude that the proportio of me who watch at leat oe game of the otreal Caadia agait the Boto Brui durig the playoff i differet tha the proportio of wome. iter 013 arti Huard 3
4 Tet 4 - Solutio Quetio 4 (10 poit) A radom ample of 100 CGP tudet wa elected where each wa aked for hi mother togue ad whether they are plaig to go to a Frech or a glih uiverity. Ca you coclude, at the 5% level of igificace, the uiverity a CGP tudet goe to i ot idepedet of hi mother togue? Ue the claical approach. Laguage of Uiverity other Togue Frech glih Frech (30) (0) glih (18) (1) Other (1) (8) Step 1 Step Aumptio: The clae are all icluive ad mutually excluive O i, j 5 Thu = 0.05 H o : The uiverity a CGP tudet goe to i idepedet of hi mother togue. H A : The uiverity a CGP tudet goe to i ot idepedet of hi mother togue. Step 4 a) Right-tailed tet df,, O i ot i the critical regio b) Fail to reject H o. There i iufficiet evidece at the 5% level of igificace to coclude that the uiverity a CGP tudet goe to i depedet of hi mother togue. iter 013 arti Huard 4
5 Tet 4 - Solutio Quetio 5 (10 poit) The ower of a pychotherapy cliic i tudyig the ometime large pread i waitig time for patiet to obtai a appoitmet for coultatio. I a radom ample of 5 patiet, the tadard deviatio for the waitig time wa 3.4 day. Aumig that the waitig time are ormally ditributed, fid a 95% cofidece iterval for the variace ad for the tadard deviatio of the waitig time for patiet to obtai a appoitmet for coultatio. 1 Step 1 Aumptio: X N, thu 4 Level of cofidece: or 0.05 Step Poit timate: 3.4 day a),1 4, df, 4, df b) day df, df, The 95% cofidece iterval for the variace of waitig time i 7.05 day to.37 day, ad the tadard deviatio i.65 day to 4.73 day. iter 013 arti Huard 5
6 Tet 4 - Solutio Formula d d t d t 1 1 X1 X N 1, 1 x x 1 1 t t 1 p 1 pˆ1 pˆ N p1 p, p q p q 1 pˆ1 pˆ N 0, pq 1 pˆ p p r1 r O O R 1C 1 row total colum total 1 1 df, df,1 grad total iter 013 arti Huard 6
M227 Chapter 9 Section 1 Testing Two Parameters: Means, Variances, Proportions
M7 Chapter 9 Sectio 1 OBJECTIVES Tet two mea with idepedet ample whe populatio variace are kow. Tet two variace with idepedet ample. Tet two mea with idepedet ample whe populatio variace are equal Tet
More informationChapter 9. Key Ideas Hypothesis Test (Two Populations)
Chapter 9 Key Idea Hypothei Tet (Two Populatio) Sectio 9-: Overview I Chapter 8, dicuio cetered aroud hypothei tet for the proportio, mea, ad tadard deviatio/variace of a igle populatio. However, ofte
More informationx z Increasing the size of the sample increases the power (reduces the probability of a Type II error) when the significance level remains fixed.
] z-tet for the mea, μ If the P-value i a mall or maller tha a pecified value, the data are tatitically igificat at igificace level. Sigificace tet for the hypothei H 0: = 0 cocerig the ukow mea of a populatio
More informationTESTS OF SIGNIFICANCE
TESTS OF SIGNIFICANCE Seema Jaggi I.A.S.R.I., Library Aveue, New Delhi eema@iari.re.i I applied ivetigatio, oe i ofte itereted i comparig ome characteritic (uch a the mea, the variace or a meaure of aociatio
More informationComments on Discussion Sheet 18 and Worksheet 18 ( ) An Introduction to Hypothesis Testing
Commet o Dicuio Sheet 18 ad Workheet 18 ( 9.5-9.7) A Itroductio to Hypothei Tetig Dicuio Sheet 18 A Itroductio to Hypothei Tetig We have tudied cofidece iterval for a while ow. Thee are method that allow
More informationS T A T R a c h e l L. W e b b, P o r t l a n d S t a t e U n i v e r s i t y P a g e 1. = Population Variance
S T A T 4 - R a c h e l L. W e b b, P o r t l a d S t a t e U i v e r i t y P a g e Commo Symbol = Sample Size x = Sample Mea = Sample Stadard Deviatio = Sample Variace pˆ = Sample Proportio r = Sample
More informationStatistical Inference Procedures
Statitical Iferece Procedure Cofidece Iterval Hypothei Tet Statitical iferece produce awer to pecific quetio about the populatio of iteret baed o the iformatio i a ample. Iferece procedure mut iclude a
More informationTools Hypothesis Tests
Tool Hypothei Tet The Tool meu provide acce to a Hypothei Tet procedure that calculate cofidece iterval ad perform hypothei tet for mea, variace, rate ad proportio. It i cotrolled by the dialog box how
More informationUNIVERSITY OF CALICUT
Samplig Ditributio 1 UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION BSc. MATHEMATICS COMPLEMENTARY COURSE CUCBCSS 2014 Admiio oward III Semeter STATISTICAL INFERENCE Quetio Bak 1. The umber of poible
More informationVIII. Interval Estimation A. A Few Important Definitions (Including Some Reminders)
VIII. Iterval Etimatio A. A Few Importat Defiitio (Icludig Some Remider) 1. Poit Etimate - a igle umerical value ued a a etimate of a parameter.. Poit Etimator - the ample tatitic that provide the poit
More informationCommon Large/Small Sample Tests 1/55
Commo Large/Small Sample Tests 1/55 Test of Hypothesis for the Mea (σ Kow) Covert sample result ( x) to a z value Hypothesis Tests for µ Cosider the test H :μ = μ H 1 :μ > μ σ Kow (Assume the populatio
More informationStatistical Inference for Two Samples. Applied Statistics and Probability for Engineers. Chapter 10 Statistical Inference for Two Samples
4/3/6 Applied Statitic ad Probability for Egieer Sixth Editio Dougla C. Motgomery George C. Ruger Chapter Statitical Iferece for Two Sample Copyright 4 Joh Wiley & So, Ic. All right reerved. CHAPTER OUTLINE
More informationOverview. p 2. Chapter 9. Pooled Estimate of. q = 1 p. Notation for Two Proportions. Inferences about Two Proportions. Assumptions
Chapter 9 Slide Ifereces from Two Samples 9- Overview 9- Ifereces about Two Proportios 9- Ifereces about Two Meas: Idepedet Samples 9-4 Ifereces about Matched Pairs 9-5 Comparig Variatio i Two Samples
More informationIntroEcono. Discrete RV. Continuous RV s
ItroEcoo Aoc. Prof. Poga Porchaiwiekul, Ph.D... ก ก e-mail: Poga.P@chula.ac.th Homepage: http://pioeer.chula.ac.th/~ppoga (c) Poga Porchaiwiekul, Chulalogkor Uiverity Quatitative, e.g., icome, raifall
More informationStat 3411 Spring 2011 Assignment 6 Answers
Stat 3411 Sprig 2011 Aigmet 6 Awer (A) Awer are give i 10 3 cycle (a) 149.1 to 187.5 Sice 150 i i the 90% 2-ided cofidece iterval, we do ot reject H 0 : µ 150 v i favor of the 2-ided alterative H a : µ
More informationChapter 9: Hypothesis Testing
Chapter 9: Hypothei Tetig Chapter 5 dicued the cocept of amplig ditributio ad Chapter 8 dicued how populatio parameter ca be etimated from a ample. 9. Baic cocept Hypothei Tetig We begi by makig a tatemet,
More informationChapter 8.2. Interval Estimation
Chapter 8.2. Iterval Etimatio Baic of Cofidece Iterval ad Large Sample Cofidece Iterval 1 Baic Propertie of Cofidece Iterval Aumptio: X 1, X 2,, X are from Normal ditributio with a mea of µ ad tadard deviatio.
More informationMathacle PSet Stats, Confidence Intervals and Estimation Level Number Name: Date: Unbiased Estimators So we don t have favorite.
PSet ----- Stat, Cofidece Iterval ad Etimatio Ubiaed Etimator So we do t have favorite. IV. CONFIDENCE INTERVAL AND ESTIMATION 4.1. Sigificat Level ad Critical Value z ad The igificat level, ofte deoted
More information18.05 Problem Set 9, Spring 2014 Solutions
18.05 Problem Set 9, Sprig 2014 Solutio Problem 1. (10 pt.) (a) We have x biomial(, θ), o E(X) =θ ad Var(X) = θ(1 θ). The rule-of-thumb variace i jut 4. So the ditributio beig plotted are biomial(250,
More informationSOLUTION: The 95% confidence interval for the population mean µ is x ± t 0.025; 49
C22.0103 Sprig 2011 Homework 7 olutio 1. Baed o a ample of 50 x-value havig mea 35.36 ad tadard deviatio 4.26, fid a 95% cofidece iterval for the populatio mea. SOLUTION: The 95% cofidece iterval for the
More informationStatistics. Chapter 10 Two-Sample Tests. Copyright 2013 Pearson Education, Inc. publishing as Prentice Hall. Chap 10-1
Statistics Chapter 0 Two-Sample Tests Copyright 03 Pearso Educatio, Ic. publishig as Pretice Hall Chap 0- Learig Objectives I this chapter, you lear How to use hypothesis testig for comparig the differece
More informationSTA 4032 Final Exam Formula Sheet
Chapter 2. Probability STA 4032 Fial Eam Formula Sheet Some Baic Probability Formula: (1) P (A B) = P (A) + P (B) P (A B). (2) P (A ) = 1 P (A) ( A i the complemet of A). (3) If S i a fiite ample pace
More information- E < p. ˆ p q ˆ E = q ˆ = 1 - p ˆ = sample proportion of x failures in a sample size of n. where. x n sample proportion. population proportion
1 Chapter 7 ad 8 Review for Exam Chapter 7 Estimates ad Sample Sizes 2 Defiitio Cofidece Iterval (or Iterval Estimate) a rage (or a iterval) of values used to estimate the true value of the populatio parameter
More information20. CONFIDENCE INTERVALS FOR THE MEAN, UNKNOWN VARIANCE
20. CONFIDENCE INTERVALS FOR THE MEAN, UNKNOWN VARIANCE If the populatio tadard deviatio σ i ukow, a it uually will be i practice, we will have to etimate it by the ample tadard deviatio. Sice σ i ukow,
More informationSTUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN ( )
STUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN Suppoe that we have a ample of meaured value x1, x, x3,, x of a igle uow quatity. Aumig that the meauremet are draw from a ormal ditributio
More informationStatistical Equations
Statitical Equatio You are permitted to ue the iformatio o thee page durig your eam. Thee page are ot guarateed to cotai all the iformatio you will eed. If you fid iformatio which you believe hould be
More information100(1 α)% confidence interval: ( x z ( sample size needed to construct a 100(1 α)% confidence interval with a margin of error of w:
Stat 400, ectio 7. Large Sample Cofidece Iterval ote by Tim Pilachowki a Large-Sample Two-ided Cofidece Iterval for a Populatio Mea ectio 7.1 redux The poit etimate for a populatio mea µ will be a ample
More informationChapter 10: H at alpha of.05. Hypothesis Testing: Additional Topics
Chapter 10: pothei Tetig: Additioal Topic 10.1 = 5 paired obervatio with ample mea of 50 ad 60 for populatio 1 ad. Ca ou reject the ull hpothei at a alpha of.05 if a. d = 0, : 0 1 0; : 1 1 0; 10 0 t =
More informationSection 18: confidence interval & hypothesis testing using sample means (sigma unknown)
Sectio 18: cofidece iterval & hypothei tetig uig ample mea (igma ukow) 1. A imple radom ample of 40 package of Chip Ahoy cookie reveal a average of 1261.6 chocolate chip per package, with a tadard deviatio
More informationConfidence Intervals. Confidence Intervals
A overview Mot probability ditributio are idexed by oe me parameter. F example, N(µ,σ 2 ) B(, p). I igificace tet, we have ued poit etimat f parameter. F example, f iid Y 1,Y 2,...,Y N(µ,σ 2 ), Ȳ i a poit
More informationStatistics Problem Set - modified July 25, _. d Q w. i n
Statitic Problem Set - modified July 5, 04 x i x i i x i _ x x _ t d Q w F x x t pooled calculated pooled. f d x x t calculated / /.. f d Kow cocept of Gauia Curve Sytematic Error Idetermiate Error t-tet
More informationChapter 8 Part 2. Unpaired t-test With Equal Variances With Unequal Variances
Chapter 8 Part Upaired t-tet With Equal Variace With Uequal Variace December, 008 Goal: To eplai that the choice of the two ample t-tet deped o whether the ample are depedet or idepedet ad for the idepedet
More informationEstimation Theory. goavendaño. Estimation Theory
Etimatio Theory Statitical Iferece method by which geeralizatio are made about a populatio Two Major Area of Statitical Iferece. Etimatio a parameter i etablihed baed o the amplig ditributio of a proportio,
More informationWorking with Two Populations. Comparing Two Means
Workig with Two Populatios Comparig Two Meas Coditios for Two-Sample Iferece The data are from two radom samples from two distict idepedet populatios. Normality. Two sample t procedures are more robust
More informationStat 200 -Testing Summary Page 1
Stat 00 -Testig Summary Page 1 Mathematicias are like Frechme; whatever you say to them, they traslate it ito their ow laguage ad forthwith it is somethig etirely differet Goethe 1 Large Sample Cofidece
More informationClass 27. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700
Class 7 Daiel B. Rowe, Ph.D. Departmet of Mathematics, Statistics, ad Computer Sciece Copyright 013 by D.B. Rowe 1 Ageda: Skip Recap Chapter 10.5 ad 10.6 Lecture Chapter 11.1-11. Review Chapters 9 ad 10
More informationGrant MacEwan University STAT 151 Formula Sheet Final Exam Dr. Karen Buro
Grat MacEwa Uiverity STAT 151 Formula Sheet Fial Exam Dr. Kare Buro Decriptive Statitic Sample Variace: = i=1 (x i x) 1 = Σ i=1x i (Σ i=1 x i) 1 Sample Stadard Deviatio: = Sample Variace = Media: Order
More informationSTA Learning Objectives. Population Proportions. Module 10 Comparing Two Proportions. Upon completing this module, you should be able to:
STA 2023 Module 10 Comparig Two Proportios Learig Objectives Upo completig this module, you should be able to: 1. Perform large-sample ifereces (hypothesis test ad cofidece itervals) to compare two populatio
More informationThis chapter focuses on two experimental designs that are crucial to comparative studies: (1) independent samples and (2) matched pair samples.
Chapter 9 & : Comparig Two Treatmets: This chapter focuses o two eperimetal desigs that are crucial to comparative studies: () idepedet samples ad () matched pair samples Idepedet Radom amples from Two
More information(7 One- and Two-Sample Estimation Problem )
34 Stat Lecture Notes (7 Oe- ad Two-Sample Estimatio Problem ) ( Book*: Chapter 8,pg65) Probability& Statistics for Egieers & Scietists By Walpole, Myers, Myers, Ye Estimatio 1 ) ( ˆ S P i i Poit estimate:
More informationTables and Formulas for Sullivan, Fundamentals of Statistics, 2e Pearson Education, Inc.
Table ad Formula for Sulliva, Fudametal of Statitic, e. 008 Pearo Educatio, Ic. CHAPTER Orgaizig ad Summarizig Data Relative frequecy frequecy um of all frequecie Cla midpoit: The um of coecutive lower
More informationSection II. Free-Response Questions -46-
Sectio II Free-Repoe Quetio -46- Formula begi o page 48. Quetio begi o page 51. Table begi o page 60. -47- Formula (I) Decriptive Statitic x = Â x i ( ) 2 1 x = Â x x - 1 i - p = ( - 1) + ( -1 1 2 ) (
More informationChapter 22. Comparing Two Proportions. Copyright 2010, 2007, 2004 Pearson Education, Inc.
Chapter 22 Comparig Two Proportios Copyright 2010, 2007, 2004 Pearso Educatio, Ic. Comparig Two Proportios Read the first two paragraphs of pg 504. Comparisos betwee two percetages are much more commo
More informationInterval Estimation (Confidence Interval = C.I.): An interval estimate of some population parameter is an interval of the form (, ),
Cofidece Iterval Estimatio Problems Suppose we have a populatio with some ukow parameter(s). Example: Normal(,) ad are parameters. We eed to draw coclusios (make ifereces) about the ukow parameters. We
More informationClass 23. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700
Class 23 Daiel B. Rowe, Ph.D. Departmet of Mathematics, Statistics, ad Computer Sciece Copyright 2017 by D.B. Rowe 1 Ageda: Recap Chapter 9.1 Lecture Chapter 9.2 Review Exam 6 Problem Solvig Sessio. 2
More informationMATH/STAT 352: Lecture 15
MATH/STAT 352: Lecture 15 Sectios 5.2 ad 5.3. Large sample CI for a proportio ad small sample CI for a mea. 1 5.2: Cofidece Iterval for a Proportio Estimatig proportio of successes i a biomial experimet
More information11/19/ Chapter 10 Overview. Chapter 10: Two-Sample Inference. + The Big Picture : Inference for Mean Difference Dependent Samples
/9/0 + + Chapter 0 Overview Dicoverig Statitic Eitio Daiel T. Laroe Chapter 0: Two-Sample Iferece 0. Iferece for Mea Differece Depeet Sample 0. Iferece for Two Iepeet Mea 0.3 Iferece for Two Iepeet Proportio
More informationDifference tests (1): parametric
NST B Eperimetal Pychology Statitic practical Differece tet (): parametric Rudolf Cardial & Mike Aitke / 3 December 003; Departmet of Eperimetal Pychology Uiverity of Cambridge Hadout: Awer to Eample (from
More informationChapter 22. Comparing Two Proportions. Copyright 2010 Pearson Education, Inc.
Chapter 22 Comparig Two Proportios Copyright 2010 Pearso Educatio, Ic. Comparig Two Proportios Comparisos betwee two percetages are much more commo tha questios about isolated percetages. Ad they are more
More informationConfidence Intervals: Three Views Class 23, Jeremy Orloff and Jonathan Bloom
Cofidece Iterval: Three View Cla 23, 18.05 Jeremy Orloff ad Joatha Bloom 1 Learig Goal 1. Be able to produce z, t ad χ 2 cofidece iterval baed o the correpodig tadardized tatitic. 2. Be able to ue a hypothei
More informationREVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION
REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION I liear regreio, we coider the frequecy ditributio of oe variable (Y) at each of everal level of a ecod variable (X). Y i kow a the depedet variable.
More informationChem Exam 1-9/14/16. Frequency. Grade Average = 72, Median = 72, s = 20
0 4 8 6 0 4 8 3 36 40 44 48 5 56 60 64 68 7 76 80 84 88 9 96 00 Chem 53 - Exam - 9/4/6 8 7 6 5 4 3 Frequecy 0 Grade Average = 7, Media = 7, = 0 Exam Chem 53 September 4, 065 Quetio, 7 poit each for quetio
More informationConfidence Interval for one population mean or one population proportion, continued. 1. Sample size estimation based on the large sample C.I.
Cofidece Iterval for oe populatio mea or oe populatio proportio, cotiued 1. ample size estimatio based o the large sample C.I. for p ˆ(1 ˆ) ˆ(1 ˆ) From the iterval ˆ p p Z p ˆ, p Z p p L legh of your 100(1
More informationStatistical Inference About Means and Proportions With Two Populations
Departmet of Quatitative Methods & Iformatio Systems Itroductio to Busiess Statistics QM 220 Chapter 10 Statistical Iferece About Meas ad Proportios With Two Populatios Fall 2010 Dr. Mohammad Zaial 1 Chapter
More informationHypothesis Testing (2) Barrow, Statistics for Economics, Accounting and Business Studies, 4 th edition Pearson Education Limited 2006
Hypothesis Testig () Lecture 8 Barrow, Statistics for Ecoomics, Accoutig ad Busiess Studies, 4 th editio Pearso Educatio Limited 006 Hypothesis Testig () So far we have looked at hypothesis testig about
More informationSection 9.2. Tests About a Population Proportion 12/17/2014. Carrying Out a Significance Test H A N T. Parameters & Hypothesis
Sectio 9.2 Tests About a Populatio Proportio P H A N T O M S Parameters Hypothesis Assess Coditios Name the Test Test Statistic (Calculate) Obtai P value Make a decisio State coclusio Sectio 9.2 Tests
More information2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2
Chapter 8 Comparig Two Treatmets Iferece about Two Populatio Meas We wat to compare the meas of two populatios to see whether they differ. There are two situatios to cosider, as show i the followig examples:
More informationON THE SCALE PARAMETER OF EXPONENTIAL DISTRIBUTION
Review of the Air Force Academy No. (34)/7 ON THE SCALE PARAMETER OF EXPONENTIAL DISTRIBUTION Aca Ileaa LUPAŞ Military Techical Academy, Bucharet, Romaia (lua_a@yahoo.com) DOI:.96/84-938.7.5..6 Abtract:
More informationENGI 4421 Confidence Intervals (Two Samples) Page 12-01
ENGI 44 Cofidece Itervals (Two Samples) Page -0 Two Sample Cofidece Iterval for a Differece i Populatio Meas [Navidi sectios 5.4-5.7; Devore chapter 9] From the cetral limit theorem, we kow that, for sufficietly
More informationElementary Statistics
Two Samle Mea Cha08 Dr. Ghamary Page Elemetary Statitic M. Ghamary, Ph.D. Chater 8 Tet of Hyothei a Cofiece Iterval for Two Samle Two Samle Mea Cha08 Dr. Ghamary Page Tet of Hyothei for Two amle: A Statitical
More informationCOMPARISONS INVOLVING TWO SAMPLE MEANS. Two-tail tests have these types of hypotheses: H A : 1 2
Tetig Hypothee COMPARISONS INVOLVING TWO SAMPLE MEANS Two type of hypothee:. H o : Null Hypothei - hypothei of o differece. or 0. H A : Alterate Hypothei hypothei of differece. or 0 Two-tail v. Oe-tail
More informationChapter 8: Estimating with Confidence
Chapter 8: Estimatig with Cofidece Sectio 8.2 The Practice of Statistics, 4 th editio For AP* STARNES, YATES, MOORE Chapter 8 Estimatig with Cofidece 8.1 Cofidece Itervals: The Basics 8.2 8.3 Estimatig
More informationChapter 5: Hypothesis testing
Slide 5. Chapter 5: Hypothesis testig Hypothesis testig is about makig decisios Is a hypothesis true or false? Are wome paid less, o average, tha me? Barrow, Statistics for Ecoomics, Accoutig ad Busiess
More informationImportant Formulas. Expectation: E (X) = Σ [X P(X)] = n p q σ = n p q. P(X) = n! X1! X 2! X 3! X k! p X. Chapter 6 The Normal Distribution.
Importat Formulas Chapter 3 Data Descriptio Mea for idividual data: X = _ ΣX Mea for grouped data: X= _ Σf X m Stadard deviatio for a sample: _ s = Σ(X _ X ) or s = 1 (Σ X ) (Σ X ) ( 1) Stadard deviatio
More informationSOLUTIONS y n. n 1 = 605, y 1 = 351. y1. p y n. n 2 = 195, y 2 = 41. y p H 0 : p 1 = p 2 vs. H 1 : p 1 p 2.
STAT 400 UIUC Practice Problems # SOLUTIONS Stepaov Dalpiaz The followig are a umber of practice problems that may be helpful for completig the homework, ad will likely be very useful for studyig for exams..
More informationCHAPTER 6. Confidence Intervals. 6.1 (a) y = 1269; s = 145; n = 8. The standard error of the mean is = s n = = 51.3 ng/gm.
} CHAPTER 6 Cofidece Iterval 6.1 (a) y = 1269; = 145; = 8. The tadard error of the mea i SE ȳ = = 145 8 = 51.3 g/gm. (b) y = 1269; = 145; = 30. The tadard error of the mea i ȳ = 145 = 26.5 g/gm. 30 6.2
More informationLecture 5. Materials Covered: Chapter 6 Suggested Exercises: 6.7, 6.9, 6.17, 6.20, 6.21, 6.41, 6.49, 6.52, 6.53, 6.62, 6.63.
STT 315, Summer 006 Lecture 5 Materials Covered: Chapter 6 Suggested Exercises: 67, 69, 617, 60, 61, 641, 649, 65, 653, 66, 663 1 Defiitios Cofidece Iterval: A cofidece iterval is a iterval believed to
More informationStatistics and Chemical Measurements: Quantifying Uncertainty. Normal or Gaussian Distribution The Bell Curve
Statitic ad Chemical Meauremet: Quatifyig Ucertaity The bottom lie: Do we trut our reult? Should we (or ayoe ele)? Why? What i Quality Aurace? What i Quality Cotrol? Normal or Gauia Ditributio The Bell
More informationFinal Examination Solutions 17/6/2010
The Islamic Uiversity of Gaza Faculty of Commerce epartmet of Ecoomics ad Political Scieces A Itroductio to Statistics Course (ECOE 30) Sprig Semester 009-00 Fial Eamiatio Solutios 7/6/00 Name: I: Istructor:
More informationThe Hong Kong University of Science & Technology ISOM551 Introductory Statistics for Business Assignment 3 Suggested Solution
The Hog Kog Uiversity of ciece & Techology IOM55 Itroductory tatistics for Busiess Assigmet 3 uggested olutio Note All values of statistics i Q ad Q4 are obtaied by Excel. Qa. Let be the robability that
More informationChapters 5 and 13: REGRESSION AND CORRELATION. Univariate data: x, Bivariate data (x,y).
Chapters 5 ad 13: REGREION AND CORRELATION (ectios 5.5 ad 13.5 are omitted) Uivariate data: x, Bivariate data (x,y). Example: x: umber of years studets studied paish y: score o a proficiecy test For each
More informationTI-83/84 Calculator Instructions for Math Elementary Statistics
TI-83/84 Calculator Itructio for Math 34- Elemetary Statitic. Eterig Data: Data oit are tored i Lit o the TI-83/84. If you have't ued the calculator before, you may wat to erae everythig that wa there.
More informationOn the Multivariate Analysis of the level of Use of Modern Methods of Family Planning between Northern and Southern Nigeria
Iteratioal Joural of Sciece: Baic ad Applied Reearch (IJSBAR) ISSN 307-453 (Prit & Olie) http://grr.org/idex.php?ouraljouralofbaicadapplied ---------------------------------------------------------------------------------------------------------------------------
More informationQuestions about the Assignment. Describing Data: Distributions and Relationships. Measures of Spread Standard Deviation. One Quantitative Variable
Quetio about the Aigmet Read the quetio ad awer the quetio that are aked Experimet elimiate cofoudig variable Decribig Data: Ditributio ad Relatiohip GSS people attitude veru their characteritic ad poue
More informationCE3502 Environmental Monitoring, Measurements, and Data Analysis (EMMA) Spring 2008 Final Review
CE35 Evirometal Moitorig, Meauremet, ad Data Aalyi (EMMA) Sprig 8 Fial Review I. Topic:. Decriptive tatitic: a. Mea, Stadard Deviatio, COV b. Bia (accuracy), preciio, Radom v. ytematic error c. Populatio
More informationGeneralized Likelihood Functions and Random Measures
Pure Mathematical Sciece, Vol. 3, 2014, o. 2, 87-95 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/pm.2014.437 Geeralized Likelihood Fuctio ad Radom Meaure Chrito E. Koutzaki Departmet of Mathematic
More informationMTH 212 Formulas page 1 out of 7. Sample variance: s = Sample standard deviation: s = s
MTH Formula age out of 7 DESCRIPTIVE TOOLS Poulatio ize = N Samle ize = x x+ x +... + x x Poulatio mea: µ = Samle mea: x = = N ( µ ) ( x x) Poulatio variace: = Samle variace: = N Poulatio tadard deviatio:
More information7-1. Chapter 4. Part I. Sampling Distributions and Confidence Intervals
7-1 Chapter 4 Part I. Samplig Distributios ad Cofidece Itervals 1 7- Sectio 1. Samplig Distributio 7-3 Usig Statistics Statistical Iferece: Predict ad forecast values of populatio parameters... Test hypotheses
More informationIntroduction to Econometrics (3 rd Updated Edition) Solutions to Odd- Numbered End- of- Chapter Exercises: Chapter 3
Itroductio to Ecoometrics (3 rd Updated Editio) by James H. Stock ad Mark W. Watso Solutios to Odd- Numbered Ed- of- Chapter Exercises: Chapter 3 (This versio August 17, 014) 015 Pearso Educatio, Ic. Stock/Watso
More informationSamples from Normal Populations with Known Variances
Samples from Normal Populatios with Kow Variaces If the populatio variaces are kow to be σ 2 1 adσ2, the the 2 two-sided cofidece iterval for the differece of the populatio meas µ 1 µ 2 with cofidece level
More informationHYPOTHESIS TESTS FOR ONE POPULATION MEAN WORKSHEET MTH 1210, FALL 2018
HYPOTHESIS TESTS FOR ONE POPULATION MEAN WORKSHEET MTH 1210, FALL 2018 We are resposible for 2 types of hypothesis tests that produce ifereces about the ukow populatio mea, µ, each of which has 3 possible
More information2. We can be 90% confident that the proportion of people in the city who know how to ski is between and 0.358
Fial Exam (sample) This particular sample covers sectios 10 19 iclusive. I. I a particular large Midwest city, a simple radom sample of 400 people reveals that 128 of them kow how to ski. 1. A 99.8% cofidece
More informationFormulas and Tables for Gerstman
Formulas ad Tables for Gerstma Measuremet ad Study Desig Biostatistics is more tha a compilatio of computatioal techiques! Measuremet scales: quatitative, ordial, categorical Iformatio quality is primary
More informationSTATISTICAL INFERENCE
STATISTICAL INFERENCE POPULATION AND SAMPLE Populatio = all elemets of iterest Characterized by a distributio F with some parameter θ Sample = the data X 1,..., X, selected subset of the populatio = sample
More informationInferential Statistics. Inference Process. Inferential Statistics and Probability a Holistic Approach. Inference Process.
Iferetial Statistics ad Probability a Holistic Approach Iferece Process Chapter 8 Poit Estimatio ad Cofidece Itervals This Course Material by Maurice Geraghty is licesed uder a Creative Commos Attributio-ShareAlike
More informationRegression, Inference, and Model Building
Regressio, Iferece, ad Model Buildig Scatter Plots ad Correlatio Correlatio coefficiet, r -1 r 1 If r is positive, the the scatter plot has a positive slope ad variables are said to have a positive relatioship
More informationTo make comparisons for two populations, consider whether the samples are independent or dependent.
Sociology 54 Testig for differeces betwee two samle meas Cocetually, comarig meas from two differet samles is the same as what we ve doe i oe-samle tests, ecet that ow the hyotheses focus o the arameters
More informationA quick activity - Central Limit Theorem and Proportions. Lecture 21: Testing Proportions. Results from the GSS. Statistics and the General Population
A quick activity - Cetral Limit Theorem ad Proportios Lecture 21: Testig Proportios Statistics 10 Coli Rudel Flip a coi 30 times this is goig to get loud! Record the umber of heads you obtaied ad calculate
More informationa.) If random samples of size n=16 are selected, can we say anything about the x~ distribution of sample means?
Sectio 7.5 4.) Suppose that x has a distributio with u=72 ad r=8. a.) If radom samples of size =16 are selected, ca we say aythig about the x~ distributio of sample meas? 8 X N 72, N 72, 2 16 b.) If the
More informationUCLA STAT 110B Applied Statistics for Engineering and the Sciences
UCLA TAT 110B Applied tatistics for Egieerig ad the cieces Istructor: Ivo Diov, Asst. Prof. I tatistics ad Neurology Teachig Assistats: Bria Ng, UCLA tatistics Uiversity of Califoria, Los Ageles, prig
More informationPSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 9
Hypothesis testig PSYCHOLOGICAL RESEARCH (PYC 34-C Lecture 9 Statistical iferece is that brach of Statistics i which oe typically makes a statemet about a populatio based upo the results of a sample. I
More informationWidely used? average out effect Discrete Prior. Examplep. More than one observation. using MVUE (sample mean) yy 1 = 3.2, y 2 =2.2, y 3 =3.6, y 4 =4.
Dicrete Prior for (μ Widely ued? average out effect Dicrete Prior populatio td i kow equally likely or ubjective weight π ( μ y ~ π ( μ l( y μ π ( μ e Examplep ( μ y Set a ubjective prior ad a gueig value
More informationMATH 320: Probability and Statistics 9. Estimation and Testing of Parameters. Readings: Pruim, Chapter 4
MATH 30: Probability ad Statistics 9. Estimatio ad Testig of Parameters Estimatio ad Testig of Parameters We have bee dealig situatios i which we have full kowledge of the distributio of a radom variable.
More informationOctober 25, 2018 BIM 105 Probability and Statistics for Biomedical Engineers 1
October 25, 2018 BIM 105 Probability ad Statistics for Biomedical Egieers 1 Populatio parameters ad Sample Statistics October 25, 2018 BIM 105 Probability ad Statistics for Biomedical Egieers 2 Ifereces
More informationhttp://www.xelca.l/articles/ufo_ladigsbaa_houte.aspx imulatio Output aalysis 3/4/06 This lecture Output: A simulatio determies the value of some performace measures, e.g. productio per hour, average queue
More informationChapter 4 Tests of Hypothesis
Dr. Moa Elwakeel [ 5 TAT] Chapter 4 Tests of Hypothesis 4. statistical hypothesis more. A statistical hypothesis is a statemet cocerig oe populatio or 4.. The Null ad The Alterative Hypothesis: The structure
More information(6) Fundamental Sampling Distribution and Data Discription
34 Stat Lecture Notes (6) Fudametal Samplig Distributio ad Data Discriptio ( Book*: Chapter 8,pg5) Probability& Statistics for Egieers & Scietists By Walpole, Myers, Myers, Ye 8.1 Radom Samplig: Populatio:
More informationStatistics Parameters
Saplig Ditributio & Cofidece Iterval Etiator Statitical Iferece Etiatio Tetig Hypothei Statitic Ued to Etiate Populatio Paraeter Statitic Saple Mea, Saple Variace, Saple Proportio, Paraeter populatio ea
More informationindependence of the random sample measurements, we have U = Z i ~ χ 2 (n) with σ / n 1. Now let W = σ 2. We then have σ 2 (x i µ + µ x ) 2 i =1 ( )
MATH 48 Chi-Square Aalysis of a Normal Stadard Deviatio Dr Neal, WKU We ow shall use the chi-square distriutios to aalyze the stadard deviatio of a measuremet that is kow to e ormally distriuted The proof
More information1036: Probability & Statistics
036: Probability & Statistics Lecture 0 Oe- ad Two-Sample Tests of Hypotheses 0- Statistical Hypotheses Decisio based o experimetal evidece whether Coffee drikig icreases the risk of cacer i humas. A perso
More information