BASIC STATISTICS ECOE 1323

Similar documents
Inferential Statistics and Probability a Holistic Approach. Inference Process. Inference Process. Chapter 8 Slides. Maurice Geraghty,

point estimator a random variable (like P or X) whose values are used to estimate a population parameter

Chapter 8. Confidence Interval Estimation. Copyright 2015, 2012, 2009 Pearson Education, Inc. Chapter 8, Slide 1

Introduction to Probability and Statistics Chapter 7

A point estimate is the value of a statistic that estimates the value of a parameter.

1 Random Variables and Key Statistics

ST 305: Exam 2 Fall 2014

Statistics for Economics & Business

Chapter 10 - Lecture 2 The independent two sample t-test and. confidence interval

. (The calculated sample mean is symbolized by x.)

Chapter 8: Estimation of Mean & Proportion. Introduction

B = A x z

1. Find the area under the standard normal curve between z = 0 and z = 3. (a) (b) (c) (d)

CHAPTER 8 Estimating with Confidence

Sampling Distributions and Estimation

Basic formula for confidence intervals. Formulas for estimating population variance Normal Uniform Proportion

Lecture 4: Probability (continued)

Estimating Proportions with Confidence

Statistics for Business and Economics

ii. Interval estimation:

Topic-7. Large Sample Estimation

Today: Finish Chapter 9 (Sections 9.6 to 9.8 and 9.9 Lesson 3)

Exam 2. Instructor: Cynthia Rudin TA: Dimitrios Bisias. October 25, 2011

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.

Chapter 8 Interval Estimation. Estimation Concepts. General Form of a Confidence Interval

Standard Deviations for Normal Sampling Distributions are: For proportions For means _

AY Term 2 Mock Examination

18.S096 Problem Set 5 Fall 2013 Volatility Modeling Due Date: 10/29/2013

A random variable is a variable whose value is a numerical outcome of a random phenomenon.

1. Suppose X is a variable that follows the normal distribution with known standard deviation σ = 0.3 but unknown mean µ.

Sampling Distributions & Estimators

NOTES ON ESTIMATION AND CONFIDENCE INTERVALS. 1. Estimation

Confidence Intervals Introduction

Math 124: Lecture for Week 10 of 17

4.5 Generalized likelihood ratio test

5. Best Unbiased Estimators

Introduction to Statistical Inference

SCHOOL OF ACCOUNTING AND BUSINESS BSc. (APPLIED ACCOUNTING) GENERAL / SPECIAL DEGREE PROGRAMME

Lecture 5 Point Es/mator and Sampling Distribu/on

Quantitative Analysis

Parametric Density Estimation: Maximum Likelihood Estimation

Sampling Distributions and Estimation

Research Article The Probability That a Measurement Falls within a Range of n Standard Deviations from an Estimate of the Mean

Lecture 4: Parameter Estimation and Confidence Intervals. GENOME 560 Doug Fowler, GS

CAPITAL ASSET PRICING MODEL

Online appendices from Counterparty Risk and Credit Value Adjustment a continuing challenge for global financial markets by Jon Gregory

Lecture 5: Sampling Distribution


BIOSTATS 540 Fall Estimation Page 1 of 72. Unit 6. Estimation. Use at least twelve observations in constructing a confidence interval

CHAPTER 8 CONFIDENCE INTERVALS

x satisfying all regularity conditions. Then

14.30 Introduction to Statistical Methods in Economics Spring 2009

2. Find the annual percentage yield (APY), to the nearest hundredth of a %, for an account with an APR of 12% with daily compounding.

Outline. Populations. Defs: A (finite) population is a (finite) set P of elements e. A variable is a function v : P IR. Population and Characteristics

Exam 1 Spring 2015 Statistics for Applications 3/5/2015

Chapter 10 Statistical Inference About Means and Proportions With Two Populations. Learning objectives

Chpt 5. Discrete Probability Distributions. 5-3 Mean, Variance, Standard Deviation, and Expectation

The Idea of a Confidence Interval

5 Statistical Inference

MATH : EXAM 2 REVIEW. A = P 1 + AP R ) ny

Non-Inferiority Logrank Tests

1 Estimating the uncertainty attached to a sample mean: s 2 vs.

Combining imperfect data, and an introduction to data assimilation Ross Bannister, NCEO, September 2010

DOWLING COLLEGE: School of Education Department of Educational Administration, Leadership, and Technology

These characteristics are expressed in terms of statistical properties which are estimated from the sample data.

Bayes Estimator for Coefficient of Variation and Inverse Coefficient of Variation for the Normal Distribution

FOUNDATION ACTED COURSE (FAC)

SOLUTION QUANTITATIVE TOOLS IN BUSINESS NOV 2011

Question 1 (4 points) A restaurant manager is developing a clientele profile. Some of the information for the profile follows:

Dr. Maddah ENMG 624 Financial Eng g I 03/22/06. Chapter 6 Mean-Variance Portfolio Theory

Elementary Statistics and Inference. Elementary Statistics and Inference. Chapter 20 Chance Errors in Sampling (cont.) 22S:025 or 7P:025.

Quantitative Analysis

Monetary Economics: Problem Set #5 Solutions

NPTEL DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING IIT KANPUR QUANTITATIVE FINANCE END-TERM EXAMINATION (2015 JULY-AUG ONLINE COURSE)

I. Measures of Central Tendency: -Allow us to summarize an entire data set with a single value (the midpoint).

APPLIED STATISTICS Complementary Course of BSc Mathematics - IV Semester CUCBCSS Admn onwards Question Bank

A Bayesian perspective on estimating mean, variance, and standard-deviation from data

TUSCULUM COLLEGE. Group Number:

Topic 14: Maximum Likelihood Estimation

ECON 5350 Class Notes Maximum Likelihood Estimation

ISBN Copyright 2015 The Continental Press, Inc.

An Empirical Study of the Behaviour of the Sample Kurtosis in Samples from Symmetric Stable Distributions

Maximum Empirical Likelihood Estimation (MELE)

STRAND: FINANCE. Unit 3 Loans and Mortgages TEXT. Contents. Section. 3.1 Annual Percentage Rate (APR) 3.2 APR for Repayment of Loans

r i = a i + b i f b i = Cov[r i, f] The only parameters to be estimated for this model are a i 's, b i 's, σe 2 i

CHAPTER 2 PRICING OF BONDS

STAT 135 Solutions to Homework 3: 30 points

CHANGE POINT TREND ANALYSIS OF GNI PER CAPITA IN SELECTED EUROPEAN COUNTRIES AND ISRAEL

Unbiased estimators Estimators

Department of Mathematics, S.R.K.R. Engineering College, Bhimavaram, A.P., India 2

Osborne Books Update. Financial Statements of Limited Companies Tutorial

Data Analysis and Statistical Methods Statistics 651

= α e ; x 0. Such a random variable is said to have an exponential distribution, with parameter α. [Here, view X as time-to-failure.

Confidence Intervals based on Absolute Deviation for Population Mean of a Positively Skewed Distribution

Current Year Income Assessment Form 2017/18

MA Lesson 11 Section 1.3. Solving Applied Problems with Linear Equations of one Variable

FINM6900 Finance Theory How Is Asymmetric Information Reflected in Asset Prices?

Models of Asset Pricing

Transcription:

BASIC STATISTICS ECOE 33 SPRING 007 FINAL EXAM NAME: ID NUMBER: INSTRUCTIONS:. Write your ame ad studet ID.. You have hours 3. This eam must be your ow work etirely. You caot talk to or share iformatio with ayoe. 4. Show all your work. Partial credit will oly be give where sufficiet uderstadig of the problem has bee demostrated ad work is show. DON'T WRITE ON THIS TABLE QUESTION # # #3 #4 BONUS TOTAL POINTS

SECTION : MULTIPLE-CHOICE Questio # For each questio i this sectio, circle the correct aswer. (Problem is worth pts.). The distictio betwee descriptive ad iferetial statistics is that a) descriptive statistics are umeric, iferetial statistics are graphic. b) descriptive statistics are mea-based, iferetial statistics are media-based. c) descriptive statistics describe data sets, iferetial statistics ivolve geeralizig to populatios. d) descriptive statistics are used i social sciece, iferetial statistics are used i physical scieces. e) Noe of these.. For which of the followig statistics would oe ot eed to put the data i order from smallest to largest? a) the iterquartile rage b) the trimmed mea c) the media d) the rage e) the variace 3. Suppose that for a set of umeric data, where the umbers are ot all differet, the stadard deviatio is less tha.0. The it must be true that a) the variace < the stadard deviatio. b) the variace the stadard deviatio. c) the variace = the stadard deviatio. d) the stadard deviatio e) the stadard deviatio the variace. < the variace. 4. Which of the followig idicates that a associatio betwee ad y is positive? a) A positive coefficiet of determiatio b) A positive stadard deviatio about the least squares lie c) A positive itercept of the least squares lie d) A positive Pearso s correlatio coefficiet e) A positive residual sum of squares 5. The slope of the regressio lie ad the correlatio betwee two variables is related i the followig way: a) The slope is always greater i absolute value tha the correlatio. b) The slope ad correlatio must be of the same sig. c) The slope ad correlatio must be of differet sig. d) The slope is always less i absolute value tha the correlatio. e) Noe of (a) - (d) is ecessarily true.

6. Of the properties below, which is NOT a basic property of probability? ( ) a) For ay evet E, 0 P E. ( ) b) If S is the sample space for a eperimet, P S =. c) If two evets E ad F are disjoit, the ( ) = ( ) + ( ) P E or F P E P F. d) For ay evet E, P ( E ) P ( ot E ) + = e) For ay two DISJOINT evets, E ad F, ( ) P ( E or F ) P E ad F 7. The evet, ot A is called the of evet A. a) egatio b) complemet c) uio d) itersectio e) cojuctio For questios 8-9, let deote the umber of accidets i a give moth at a certai high school parkig lot. Suppose that the probability distributio of is: 0 3 4 5 P().0.5.60.4.34.067 8. What is the probability that there are fewer tha 3 accidets i a give moth? a).0 b).4 c).585 d).799 e) Noe of these 9. What is the probability that to 4 (iclusive) accidets occur i a give moth? a).6 b).34 c).394 d).608 e) Noe of these 0. Which of the followig statemets about ormal curves is false? a) Every ormal curve is symmetric. b) Every ormal curve is symmetric about 0. c) Every ormal curve is bell-shaped. d) Every ormal curve is cetered at its mea. e) About 0.68 of the area uder a ormal curve is withi stadard deviatio of its mea.

. The proportio of values i a ormal populatio distributio that fall withi stadard deviatios of the mea is: a) 0.08 b) 0.977 c) 0.0456 d) 0.9544 e) 0.3400. Which of the followig is ot a property of a biomial eperimet? a) It cosists of a fied umber of trials,. b) Outcomes of differet trials are idepedet. c) Each trial ca result i oe of several differet outcomes. d) Observatios cosist of the umber of successes for each trial of the eperimet. e) The probability of success is costat for each trial. 3. If is a biomial radom variable with = 0 ad p = 0.5, the a) σ =.875 b) σ =.5 c) σ =.875 d) σ =.5 e) Noe of (a) - (d) 4. Suppose that has a probability distributio with desity fuctio c, if 6 < < 8 f ( ) = 0 otherwise. The the value of c is: a) 0.5 b) 0.6 c) 0.7 d) 0.8 e) 0.9 5. Whe costructig a 95% cofidece iterval, the cofidece level is: 0.95 0.95 a) 0.95 b) - 0.95 c) d) e) Caot be determied 6. Which of the followig is ot a statistical hypothesis? a) > 00 b) µ = 00 c) µ > 00 σ = d) 5 e) P.5 3

7. A type I error is made by a) rejectig H 0 whe it is true. b) rejectig H 0 whe it is false. c) failig to reject H 0 whe it is true. d) failig to reject H 0 whe it is false. 8. The P-value for a z test of H : P=.5 vs. H : P<.5, where z=.36 is: 0 0 ( > ) b) P( z<.36) P( z> ) ( z> 6 ) e) P(.36 < z ad z>.36) a) P z.36 c).36 d) P.3 9. Suppose you take a simple radom sample from a populatio kow to be ormally distributed, but the value of σ is ukow. Your sample size is = 0. Which formula below should be used to fid the 90% cofidece iterval for the mea? a) ±.645 s σ b) ±.645 0 0 d) ±.8 σ σ e) ±.833 0 0 c) ±.833 s 0 0. The degrees of freedom of a paired t test based o = 0 pairs is a) 9 b) 0 c) 9 d) 0 e) Noe of these 4

Questio () (I) A reporter for a studet ewspaper is writig a article o the cost of attedig college. A portio of the article deals with the cost of off-campus housig. A sample of 0 oe-bedroom uits withi oe-half mile of campus resulted i a sample mea of $350 per moth ad a sample stadard deviatio of $30, assumig that the populatio is ormally distributed. (a) [5 Poits] Provide a 95% cofidece iterval estimate of the populatio mea. (b) [8 Poits] The college ewspaper claims that mea cost per moth for oe-bedroom uits withi oe-half mile of campus is less tha $370. Test this claim at 0.05 level of sigificace. 5

(II) [7 Poits] To estimate the proportio of traffic deaths i Florida last year that were alcohol related, determie the ecessary sample size for the estimate to be accurate to withi.05 with probability.99. Based o results of a previous study, we epect the proportio to be about.35. 6

Questio (3) (I) [0 Poits] I 990, 5.8% of job applicats who were tested for drugs failed the test. At the 0.0 level, test the claim that the failure rate is ow lower if a radom sample of 50 curret job applicats results i 58 failures. H o : H a : Test Statistic: P-value: Coclusio: (a) State H 0 ad H a. H 0: p=0.058 H a: p<0.058 (b) Calculate the test statistic. z = 50, = ˆp p SE ˆp 0 = = 58 58, ˆp = 50 0. 038 0. 058 0. 006 = 0. 038, = 3. 3 SE ˆp = p0( p) 0 = ( 0. 058)( 0. 94) 50 = 0. 006 (c) Fid the P-value or give the rejectio regio. P-value=P(Z<-3.3)=ormalcdf(-E99,-3.3)=0.00048 (d) State your coclusio. Coclusio: We reject H 0 ad coclude that the failure rate is ow lower tha 5.8%. 7

(II) [0 Poits] How large a sample size is eeded to estimate the mea aual icome of Native Americas correct to withi $000 with probability.99? Suppose there is o prior iformatio about the stadard deviatio of aual icome of Native Americas, but we guess that about 68% of their icomes are betwee $0000 ad $40,000 ad that this distributio of icomes is approimately moud shaped. 8

Questio (4) (I) [0 Poits] The Motaa Highway Patrol is iterested i determiig whether Motaa residets or oresidets drive faster o a particular stretch of Iterstate 90. Idepedet radom samples of the speeds of cars havig Motaa licese plates ad cars licesed i other states results i the summary data listed below. Group Sample size Sample Mea Sample stadard deviatio Motaa 4 73. 3.8 Others 7 76.6 4.7 Assume the populatio variaces are the same. At 0.05 level of sigificace, is there sufficiet evidece to coclude that oresidets drive faster o this stretch of Iterstate 90 tha residets of Motaa? H o : H a : Test Statistic: P-value Coclusio: 9

(II) [0 Poits] A article reports that (4.0, 5.6) is a 95% cofidece iterval for the mea legth of stay, i days, of patiets i hospital for a particular operatio. The article reports the sample size of 50, but ot the sample mea or stadard deviatio. Fid them. 0

إضافي Bous: (I) [3 Poits] For a ormally distributed variable, verify that the probability betwee µ +. 67σ equals.50 µ 67σ. ad (II) [3 Poits] Fid the b-value such that the iterval probability for a ormal distributio. µ bσ ad µ + bσ cotais 98% of the (III) A fast food chai sells hamburger that they claim has sodium cotet of 650 milligrams. A simple radom sample of 35 hamburgers was aalyzed for sodium cotet. A 99% cofidece iterval for the populatio mea sodium cotet, µ, of such hamburgers is (65, 67). Aswer the followig questios with yes, o or ca't tell. Give a eplaatio for your aswer. (a) [ Poit] Does the populatio mea lie i the iterval (65, 67)? (b) [ Poit] If we were to use the precedig data to test the hypotheses H o : µ =650 versus H a : µ 650. At a % sigificace level, would we reject the ull hypothesis? Eplai.

Formulas: i i = IQR = Q3 Q, =, S = i i = ( ) i y i y S y i = yˆ = a + b, b = r, a = y b r = S i y i y i = i = k k! P ( X = k ) = p ( p ), k = 0,,,, =,! = ( ) 3.., µ = p, σ = p p k k k!( k )! Populatio mea (s) Level C cofidece iterval Hypothesis test Large sample Oe-sample z test Use s ifσ is ukow Small sample ad σ ukow Oe-sample t test Large samples Two-sample z test Use s ad s if σ, σ are ukow Pooled two-sample t test ( ) s + ( ) s s p = ( + ) σ, ukow & equal σ Two-sample t test σ ± z σ s ± t df = ( ) σ, ukow & uequal ( ) Matched pairs t-test Oe-Proportio z test Computig P-values Sample size for desired margi of error m Oe-sample z iterval: z σ = m ± z σ + σ µ z = σ t ( ) µ =, df = s z = σ σ + ( ) ± t sp + t = sp + df = + df = + s s ± t + t = s + s ( ) df = mi, df = mi, t =, =, df = s p~( p~) p p p~ ± z z = + 4 p ( p ) where Wilso Estimate where the Sample proportio + p~ = p ˆ = + 4 Use z -table for z tests ad t-table for t tests Reject H if P-value < α Oe-proportio z iterval: z + 4 = p p m ( ) ( ) ( ), 4 z + = m ( )

3

4

5