Rand Final Pop 2. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

Size: px
Start display at page:

Download "Rand Final Pop 2. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question."

Transcription

1

2 Name: Class: Date: Rand Final Pop 2 Multiple Choice Identify the choice that best completes the statement or answers the question. Scenario 12-1 A high school guidance counselor wonders if it is possible to predict a student s GPA in their senior year from their GPA in the first marking period of their freshman year. She selects a random sample of 15 seniors from the graduating class of 468 and records both full-year GPA in their senior year ( Senior ) and first-marking-period GPA in their freshman year ( Fresh ). A computer regression analysis and a residual plot of these data are given below. Constant Fresh S = R-Sq = 40.3% R-Sq(adj) = 35.7% 1. Use Scenario Which of the following is the estimate from this sample for the standard deviation of the sampling distribution of slopes? A B C D E

3 Name: Scenario 12-2 Can we predict annual household electricity costs in a specific region from the number of rooms in the house? Below is a scatterplot of annual electricity costs (in dollars) versus number of rooms for 30 randomly-selected houses in Michigan, along with computer output for linear regression of electricity costs on number of rooms. Constant Rooms S = R-Sq = 16.6% R-Sq(adj) = 13.6% 2. Use Scenario Both the scatterplot and the residual plot indicate that residuals for 3 rooms and 8 and 9 rooms tend to be lower than residuals for 4 through 7 rooms. Which condition for regression inference is not satisfied in this case? A. Mean Annual Electricity costs is a linear function of Number of rooms. B. Observations for each household are independent. C. For each number of rooms, the distribution of annual electricity costs is roughly Normal. D. The variance of annual electricity costs is roughly equal for each number of rooms. E. The data come from a random sample. 3. Use Scenario Which value in the computer output is the estimate from this sample for the standard deviation of the residuals? A B C D E. This quantity is not provided by the computer output. 2

4 Name: 4. Use Scenario Which of the following statements is a correct interpretation of information in this computer output? A. A one-room house is predicted to have annual electricity costs of $ B. For each additional room a house has, predicted annual electricity costs increase by $ C. For each additional room a house has, predicted annual electricity costs increase by $ D. The standard deviation in annual electrical costs for houses in this sample is $ E. The standard deviation in annual electrical costs for houses in this sample is $ Scenario 12-3 Are high school students who like their English class more likely to enjoy their history class as well? Here is a regression analysis and residual plot for 30 randomly-selected students who were asked to rate how much they liked both English and history on a 0 to 5 scale (a higher rating means the student liked the subject more). [Data from Census at Schools survey in Canada]. Constant English S = R-Sq = 19.8% R-Sq(adj) = 17.0% 5. Use Scenario We wish to perform a t-test for regression slope. What is the test statistic for this test? A B C D E

5 Name: 6. Use Scenario Assuming that the conditions for inference have been met, which of the following represents a 99% confidence interval for the rate of change in history rating for a one-unit change in English rating? A. B. C. D. E. Scenario 12-5 Can we predict annual household electricity costs in a specific region from the number of rooms in the house? Below is computer output for a regression of annual electricity costs (in dollars) on number of rooms for 30 randomly-selected houses in Michigan. Assume the conditions for regression inference have been met. 7. Use Scenario Which of the following represents the proportion of variation in annual electricity costs that is accounted for by the regression of annual electricity costs on number of rooms? A B C D. E. 4

Linear regression model

Linear regression model Regression Model Assumptions (Solutions) STAT-UB.0003: Regression and Forecasting Models Linear regression model 1. Here is the least squares regression fit to the Zagat restaurant data: 10 15 20 25 10

More information

Statistical Models of Stocks and Bonds. Zachary D Easterling: Department of Economics. The University of Akron

Statistical Models of Stocks and Bonds. Zachary D Easterling: Department of Economics. The University of Akron Statistical Models of Stocks and Bonds Zachary D Easterling: Department of Economics The University of Akron Abstract One of the key ideas in monetary economics is that the prices of investments tend to

More information

Stat3011: Solution of Midterm Exam One

Stat3011: Solution of Midterm Exam One 1 Stat3011: Solution of Midterm Exam One Fall/2003, Tiefeng Jiang Name: Problem 1 (30 points). Choose one appropriate answer in each of the following questions. 1. (B ) The mean age of five people in a

More information

The Central Limit Theorem. Sec. 8.2: The Random Variable. it s Distribution. it s Distribution

The Central Limit Theorem. Sec. 8.2: The Random Variable. it s Distribution. it s Distribution The Central Limit Theorem Sec. 8.1: The Random Variable it s Distribution Sec. 8.2: The Random Variable it s Distribution X p and and How Should You Think of a Random Variable? Imagine a bag with numbers

More information

σ e, which will be large when prediction errors are Linear regression model

σ e, which will be large when prediction errors are Linear regression model Linear regression model we assume that two quantitative variables, x and y, are linearly related; that is, the population of (x, y) pairs are related by an ideal population regression line y = α + βx +

More information

Statistics 101: Section L - Laboratory 6

Statistics 101: Section L - Laboratory 6 Statistics 101: Section L - Laboratory 6 In today s lab, we are going to look more at least squares regression, and interpretations of slopes and intercepts. Activity 1: From lab 1, we collected data on

More information

Diploma Part 2. Quantitative Methods. Examiner s Suggested Answers

Diploma Part 2. Quantitative Methods. Examiner s Suggested Answers Diploma Part 2 Quantitative Methods Examiner s Suggested Answers Question 1 (a) The binomial distribution may be used in an experiment in which there are only two defined outcomes in any particular trial

More information

Time Observations Time Period, t

Time Observations Time Period, t Operations Research Models and Methods Paul A. Jensen and Jonathan F. Bard Time Series and Forecasting.S1 Time Series Models An example of a time series for 25 periods is plotted in Fig. 1 from the numerical

More information

GGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1

GGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1 GGraph 9 Gender : R Linear =.43 : R Linear =.769 8 7 6 5 4 3 5 5 Males Only GGraph Page R Linear =.43 R Loess 9 8 7 6 5 4 5 5 Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent

More information

Regression. Lecture Notes VII

Regression. Lecture Notes VII Regression Lecture Notes VII Statistics 112, Fall 2002 Outline Predicting based on Use of the conditional mean (the regression function) to make predictions. Prediction based on a sample. Regression line.

More information

Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions:

Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions: Chapter 17 Inference about a Population Mean Conditions for inference Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions: (1) Our data (observations)

More information

Introduction to Population Modeling

Introduction to Population Modeling Introduction to Population Modeling In addition to estimating the size of a population, it is often beneficial to estimate how the population size changes over time. Ecologists often uses models to create

More information

Homework Assignment Section 3

Homework Assignment Section 3 Homework Assignment Section 3 Tengyuan Liang Business Statistics Booth School of Business Problem 1 A company sets different prices for a particular stereo system in eight different regions of the country.

More information

Correlation between Inflation Rates and Currency Values

Correlation between Inflation Rates and Currency Values Parkland College A with Honors Projects Honors Program 2015 Correlation between Inflation Rates and Currency Values Valeria Rohde Parkland College Recommended Citation Rohde, Valeria, "Correlation between

More information

Statistic Midterm. Spring This is a closed-book, closed-notes exam. You may use any calculator.

Statistic Midterm. Spring This is a closed-book, closed-notes exam. You may use any calculator. Statistic Midterm Spring 2018 This is a closed-book, closed-notes exam. You may use any calculator. Please answer all problems in the space provided on the exam. Read each question carefully and clearly

More information

C.10 Exercises. Y* =!1 + Yz

C.10 Exercises. Y* =!1 + Yz C.10 Exercises C.I Suppose Y I, Y,, Y N is a random sample from a population with mean fj. and variance 0'. Rather than using all N observations consider an easy estimator of fj. that uses only the first

More information

CHAPTER 2 Describing Data: Numerical

CHAPTER 2 Describing Data: Numerical CHAPTER Multiple-Choice Questions 1. A scatter plot can illustrate all of the following except: A) the median of each of the two variables B) the range of each of the two variables C) an indication of

More information

1. (9; 3ea) The table lists the survey results of 100 non-senior students. Math major Art major Biology major

1. (9; 3ea) The table lists the survey results of 100 non-senior students. Math major Art major Biology major Math 54 Test #2(Chapter 4, 5, 6, 7) Name: Show all necessary work for full credit. You may use graphing calculators for your calculation, but you must show all detail and use the proper notations. Total

More information

Stat 328, Summer 2005

Stat 328, Summer 2005 Stat 328, Summer 2005 Exam #2, 6/18/05 Name (print) UnivID I have neither given nor received any unauthorized aid in completing this exam. Signed Answer each question completely showing your work where

More information

The Simple Regression Model

The Simple Regression Model Chapter 2 Wooldridge: Introductory Econometrics: A Modern Approach, 5e Definition of the simple linear regression model Explains variable in terms of variable Intercept Slope parameter Dependent variable,

More information

MBA 7020 Sample Final Exam

MBA 7020 Sample Final Exam Descriptive Measures, Confidence Intervals MBA 7020 Sample Final Exam Given the following sample of weight measurements (in pounds) of 25 children aged 4, answer the following questions(1 through 3): 45,

More information

STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15

STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15 STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15 For this assignment use the Diamonds dataset in the Stat2Data library. The dataset is used in examples

More information

The Simple Regression Model

The Simple Regression Model Chapter 2 Wooldridge: Introductory Econometrics: A Modern Approach, 5e Definition of the simple linear regression model "Explains variable in terms of variable " Intercept Slope parameter Dependent var,

More information

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -

More information

Central Limit Theorem

Central Limit Theorem Central Limit Theorem Lots of Samples 1 Homework Read Sec 6-5. Discussion Question pg 329 Do Ex 6-5 8-15 2 Objective Use the Central Limit Theorem to solve problems involving sample means 3 Sample Means

More information

Random Effects... and more about pigs G G G G G G G G G G G

Random Effects... and more about pigs G G G G G G G G G G G et s examine the random effects model in terms of the pig weight example. This had eight litters, and in the first analysis we were willing to think of as fixed effects. This means that we might want to

More information

d) What is the slope? Interpret in the context of the problem.

d) What is the slope? Interpret in the context of the problem. Stat and Data Analysis 4.2 More LSRL 1. Open the group USEDCAR to get the lists USEDA and USEDB. USEDA is the age of the used Corolla. USEDB is the price listed in the local paper for the car. a) Create

More information

Diploma in Financial Management with Public Finance

Diploma in Financial Management with Public Finance Diploma in Financial Management with Public Finance Cohort: DFM/09/FT Jan Intake Examinations for 2009 Semester II MODULE: STATISTICS FOR FINANCE MODULE CODE: QUAN 1103 Duration: 2 Hours Reading time:

More information

Subject CS1 Actuarial Statistics 1 Core Principles. Syllabus. for the 2019 exams. 1 June 2018

Subject CS1 Actuarial Statistics 1 Core Principles. Syllabus. for the 2019 exams. 1 June 2018 ` Subject CS1 Actuarial Statistics 1 Core Principles Syllabus for the 2019 exams 1 June 2018 Copyright in this Core Reading is the property of the Institute and Faculty of Actuaries who are the sole distributors.

More information

Homework Assignment Section 3

Homework Assignment Section 3 Homework Assignment Section 3 Tengyuan Liang Business Statistics Booth School of Business Problem 1 A company sets different prices for a particular stereo system in eight different regions of the country.

More information

Analysis of Variance in Matrix form

Analysis of Variance in Matrix form Analysis of Variance in Matrix form The ANOVA table sums of squares, SSTO, SSR and SSE can all be expressed in matrix form as follows. week 9 Multiple Regression A multiple regression model is a model

More information

Topic 8: Model Diagnostics

Topic 8: Model Diagnostics Topic 8: Model Diagnostics Outline Diagnostics to check model assumptions Diagnostics concerning X Diagnostics using the residuals Diagnostics and remedial measures Diagnostics: look at the data to diagnose

More information

Math 14, Homework 7.1 p. 379 # 7, 9, 18, 20, 21, 23, 25, 26 Name

Math 14, Homework 7.1 p. 379 # 7, 9, 18, 20, 21, 23, 25, 26 Name 7.1 p. 379 # 7, 9, 18, 0, 1, 3, 5, 6 Name 7. Find each. (a) z α Step 1 Step Shade the desired percent under the mean statistics calculator to 99% confidence interval 3 1 0 1 3 µ 3σ µ σ µ σ µ µ+σ µ+σ µ+3σ

More information

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences. STAB22H3 Statistics I Duration: 1 hour and 45 minutes

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences. STAB22H3 Statistics I Duration: 1 hour and 45 minutes UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences STAB22H3 Statistics I Duration: 1 hour and 45 minutes Last Name: First Name: Student number: Aids allowed: - One handwritten

More information

Final Exam - section 1. Thursday, December hours, 30 minutes

Final Exam - section 1. Thursday, December hours, 30 minutes Econometrics, ECON312 San Francisco State University Michael Bar Fall 2013 Final Exam - section 1 Thursday, December 19 1 hours, 30 minutes Name: Instructions 1. This is closed book, closed notes exam.

More information

11/28/2018. Overview. Multiple Linear Regression Analysis. Multiple regression. Multiple regression. Multiple regression. Multiple regression

11/28/2018. Overview. Multiple Linear Regression Analysis. Multiple regression. Multiple regression. Multiple regression. Multiple regression Multiple Linear Regression Analysis BSAD 30 Dave Novak Fall 208 Source: Ragsdale, 208 Spreadsheet Modeling and Decision Analysis 8 th edition 207 Cengage Learning 2 Overview Last class we considered the

More information

AMS7: WEEK 4. CLASS 3

AMS7: WEEK 4. CLASS 3 AMS7: WEEK 4. CLASS 3 Sampling distributions and estimators. Central Limit Theorem Normal Approximation to the Binomial Distribution Friday April 24th, 2015 Sampling distributions and estimators REMEMBER:

More information

National Quali cations

National Quali cations National Quali cations AH018 X70/77/11 Statistics THURSDAY, 10 MAY 1:00 PM 4:00 PM Total marks 100 Attempt ALL questions. You may use a calculator. Full credit will be given only to solutions which contain

More information

Graduated from Glasgow University in 2009: BSc with Honours in Mathematics and Statistics.

Graduated from Glasgow University in 2009: BSc with Honours in Mathematics and Statistics. The statistical dilemma: Forecasting future losses for IFRS 9 under a benign economic environment, a trade off between statistical robustness and business need. Katie Cleary Introduction Presenter: Katie

More information

Estimating a demand function

Estimating a demand function Estimating a demand function One of the most basic topics in economics is the supply/demand curve. Simply put, the supply offered for sale of a commodity is directly related to its price, while the demand

More information

Tests for One Variance

Tests for One Variance Chapter 65 Introduction Occasionally, researchers are interested in the estimation of the variance (or standard deviation) rather than the mean. This module calculates the sample size and performs power

More information

NEWCASTLE UNIVERSITY. School SEMESTER /2013 ACE2013. Statistics for Marketing and Management. Time allowed: 2 hours

NEWCASTLE UNIVERSITY. School SEMESTER /2013 ACE2013. Statistics for Marketing and Management. Time allowed: 2 hours NEWCASTLE UNIVERSITY School SEMESTER 2 2012/2013 Statistics for Marketing and Management Time allowed: 2 hours Candidates should attempt ALL questions. Marks for each question are indicated. However you

More information

Tests for the Difference Between Two Linear Regression Intercepts

Tests for the Difference Between Two Linear Regression Intercepts Chapter 853 Tests for the Difference Between Two Linear Regression Intercepts Introduction Linear regression is a commonly used procedure in statistical analysis. One of the main objectives in linear regression

More information

Business Statistics: A First Course

Business Statistics: A First Course Business Statistics: A First Course Fifth Edition Chapter 12 Correlation and Simple Linear Regression Business Statistics: A First Course, 5e 2009 Prentice-Hall, Inc. Chap 12-1 Learning Objectives In this

More information

Diploma in Business Administration Part 2. Quantitative Methods. Examiner s Suggested Answers

Diploma in Business Administration Part 2. Quantitative Methods. Examiner s Suggested Answers Cumulative frequency Diploma in Business Administration Part Quantitative Methods Examiner s Suggested Answers Question 1 Cumulative Frequency Curve 1 9 8 7 6 5 4 3 1 5 1 15 5 3 35 4 45 Weeks 1 (b) x f

More information

(GPA, student) (area code, person) (person, shirt color)

(GPA, student) (area code, person) (person, shirt color) Foundations of Algebra Unit 5 Review Part One Name: Day One: Function Notation In order for a relation to be a function, every must have exactly one. 1) Determine whether each of the following represents

More information

Student Loan Nudges: Experimental Evidence on Borrowing and. Educational Attainment. Online Appendix: Not for Publication

Student Loan Nudges: Experimental Evidence on Borrowing and. Educational Attainment. Online Appendix: Not for Publication Student Loan Nudges: Experimental Evidence on Borrowing and Educational Attainment Online Appendix: Not for Publication June 2018 1 Appendix A: Additional Tables and Figures Figure A.1: Screen Shots From

More information

SOLUTIONS TO THE LAB 1 ASSIGNMENT

SOLUTIONS TO THE LAB 1 ASSIGNMENT SOLUTIONS TO THE LAB 1 ASSIGNMENT Question 1 Excel produces the following histogram of pull strengths for the 100 resistors: 2 20 Histogram of Pull Strengths (lb) Frequency 1 10 0 9 61 63 6 67 69 71 73

More information

VIX Fear of What? October 13, Research Note. Summary. Introduction

VIX Fear of What? October 13, Research Note. Summary. Introduction Research Note October 13, 2016 VIX Fear of What? by David J. Hait Summary The widely touted fear gauge is less about what might happen, and more about what already has happened. The VIX, while promoted

More information

Econometrics and Economic Data

Econometrics and Economic Data Econometrics and Economic Data Chapter 1 What is a regression? By using the regression model, we can evaluate the magnitude of change in one variable due to a certain change in another variable. For example,

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Sample Exam 3 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Question 1-7: The managers of a brokerage firm are interested in finding out if the

More information

Section 1.2: Linear Functions and Applications

Section 1.2: Linear Functions and Applications Section 1.2: Linear Functions and Applications Linear function: a function that has constant rate of change (regardless of which 2 points are used to calculate it). It increases (or decreases) at the same

More information

Lecture note 8 Spring Lecture note 8. Analysis of Variance (ANOVA)

Lecture note 8 Spring Lecture note 8. Analysis of Variance (ANOVA) Lecture note 8 Analysis of Variance (ANOVA) 1 Overview of ANOVA Analysis of variance (ANOVA) is a comparison of means. ANOVA allows you to compare more than two means simultaneously. Proper experimental

More information

CHAPTER 7 MULTIPLE REGRESSION

CHAPTER 7 MULTIPLE REGRESSION CHAPTER 7 MULTIPLE REGRESSION ANSWERS TO PROBLEMS AND CASES 5. Y = 7.5 + 3(0) - 1.(7) = -17.88 6. a. A correlation matrix displays the correlation coefficients between every possible pair of variables

More information

INSTITUTE AND FACULTY OF ACTUARIES. Curriculum 2019 SPECIMEN EXAMINATION

INSTITUTE AND FACULTY OF ACTUARIES. Curriculum 2019 SPECIMEN EXAMINATION INSTITUTE AND FACULTY OF ACTUARIES Curriculum 2019 SPECIMEN EXAMINATION Subject CS1A Actuarial Statistics Time allowed: Three hours and fifteen minutes INSTRUCTIONS TO THE CANDIDATE 1. Enter all the candidate

More information

Optimal portfolio construction in markets with no risk-free asset available

Optimal portfolio construction in markets with no risk-free asset available Optimal portfolio construction in markets with no risk-free asset available Andreas Emmert Produced during the MSc in Finance studies at Strathclyde University in Glasgow/Scotland Portfolio Theory Optimal

More information

Online Appendix: Asymmetric Effects of Exogenous Tax Changes

Online Appendix: Asymmetric Effects of Exogenous Tax Changes Online Appendix: Asymmetric Effects of Exogenous Tax Changes Syed M. Hussain Samreen Malik May 9,. Online Appendix.. Anticipated versus Unanticipated Tax changes Comparing our estimates with the estimates

More information

Booth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Solutions to Midterm

Booth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Solutions to Midterm Booth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (34 pts) Answer briefly the following questions. Each question has

More information

Multiple Choice: Identify the choice that best completes the statement or answers the question.

Multiple Choice: Identify the choice that best completes the statement or answers the question. U8: Statistics Review Name: Date: Multiple Choice: Identify the choice that best completes the statement or answers the question. 1. A floral delivery company conducts a study to measure the effect of

More information

Sampling and sampling distribution

Sampling and sampling distribution Sampling and sampling distribution September 12, 2017 STAT 101 Class 5 Slide 1 Outline of Topics 1 Sampling 2 Sampling distribution of a mean 3 Sampling distribution of a proportion STAT 101 Class 5 Slide

More information

starting on 5/1/1953 up until 2/1/2017.

starting on 5/1/1953 up until 2/1/2017. An Actuary s Guide to Financial Applications: Examples with EViews By William Bourgeois An actuary is a business professional who uses statistics to determine and analyze risks for companies. In this guide,

More information

CHAPTER 4 DATA ANALYSIS Data Hypothesis

CHAPTER 4 DATA ANALYSIS Data Hypothesis CHAPTER 4 DATA ANALYSIS 4.1. Data Hypothesis The hypothesis for each independent variable to express our expectations about the characteristic of each independent variable and the pay back performance

More information

Sampling & populations

Sampling & populations Sampling & populations Sample proportions Sampling distribution - small populations Sampling distribution - large populations Sampling distribution - normal distribution approximation Mean & variance of

More information

Chapter 6. Transformation of Variables

Chapter 6. Transformation of Variables 6.1 Chapter 6. Transformation of Variables 1. Need for transformation 2. Power transformations: Transformation to achieve linearity Transformation to stabilize variance Logarithmic transformation MACT

More information

Math Fall 2016 Final Exam December 10, Total 100

Math Fall 2016 Final Exam December 10, Total 100 Name: Math 111 - Fall 2016 Final Exam December 10, 2016 Section: Student ID Number: 1 15 2 13 3 14 4 15 5 13 6 15 7 15 Total 100 You are allowed to use a Ti-30x IIS Calculator (only this model!), a ruler,

More information

FACULTY OF SCIENCE DEPARTMENT OF STATISTICS

FACULTY OF SCIENCE DEPARTMENT OF STATISTICS FACULTY OF SCIENCE DEPARTMENT OF STATISTICS MODULE ATE1A10 / ATE01A1 ANALYTICAL TECHNIQUES A CAMPUS APK, DFC & SWC SUPPLEMENTARY SUMMATIVE ASSESSMENT DATE 15 JULY 2014 SESSION 15:00 17:00 ASSESSOR MODERATOR

More information

Learning Objectives for Ch. 7

Learning Objectives for Ch. 7 Chapter 7: Point and Interval Estimation Hildebrand, Ott and Gray Basic Statistical Ideas for Managers Second Edition 1 Learning Objectives for Ch. 7 Obtaining a point estimate of a population parameter

More information

Tests for Two Variances

Tests for Two Variances Chapter 655 Tests for Two Variances Introduction Occasionally, researchers are interested in comparing the variances (or standard deviations) of two groups rather than their means. This module calculates

More information

Econometric Methods for Valuation Analysis

Econometric Methods for Valuation Analysis Econometric Methods for Valuation Analysis Margarita Genius Dept of Economics M. Genius (Univ. of Crete) Econometric Methods for Valuation Analysis Cagliari, 2017 1 / 26 Correlation Analysis Simple Regression

More information

Chapter 5. Forecasting. Learning Objectives

Chapter 5. Forecasting. Learning Objectives Chapter 5 Forecasting To accompany Quantitative Analysis for Management, Eleventh Edition, by Render, Stair, and Hanna Power Point slides created by Brian Peterson Learning Objectives After completing

More information

HARVEST MODELS INTRODUCTION. Objectives

HARVEST MODELS INTRODUCTION. Objectives 29 HARVEST MODELS Objectives Understand the concept of recruitment rate and its relationship to sustainable harvest. Understand the concepts of maximum sustainable yield, fixed-quota harvest, and fixed-effort

More information

Microeconomic Foundations of Incomplete Price Adjustment

Microeconomic Foundations of Incomplete Price Adjustment Chapter 6 Microeconomic Foundations of Incomplete Price Adjustment In Romer s IS/MP/IA model, we assume prices/inflation adjust imperfectly when output changes. Empirically, there is a negative relationship

More information

Making Sense of Cents

Making Sense of Cents Name: Date: Making Sense of Cents Exploring the Central Limit Theorem Many of the variables that you have studied so far in this class have had a normal distribution. You have used a table of the normal

More information

Extension Analysis. Lauren Goodwin Advisor: Steve Cherry. Spring Introduction and Background Filing Basics... 2

Extension Analysis. Lauren Goodwin Advisor: Steve Cherry. Spring Introduction and Background Filing Basics... 2 Extension Analysis Lauren Goodwin Advisor: Steve Cherry Spring 2015 Contents 1 Introduction and Background 2 1.1 Filing Basics............................................. 2 2 Objectives and Questions

More information

Linear functions Increasing Linear Functions. Decreasing Linear Functions

Linear functions Increasing Linear Functions. Decreasing Linear Functions 3.5 Increasing, Decreasing, Max, and Min So far we have been describing graphs using quantitative information. That s just a fancy way to say that we ve been using numbers. Specifically, we have described

More information

Name PID Section # (enrolled)

Name PID Section # (enrolled) STT 315 - Lecture 3 Instructor: Aylin ALIN 04/02/2014 Midterm # 2 A Name PID Section # (enrolled) * The exam is closed book and 80 minutes. * You may use a calculator and the formula sheet that you brought

More information

Chapter 7 Study Guide: The Central Limit Theorem

Chapter 7 Study Guide: The Central Limit Theorem Chapter 7 Study Guide: The Central Limit Theorem Introduction Why are we so concerned with means? Two reasons are that they give us a middle ground for comparison and they are easy to calculate. In this

More information

Economics 345 Applied Econometrics

Economics 345 Applied Econometrics Economics 345 Applied Econometrics Problem Set 4--Solutions Prof: Martin Farnham Problem sets in this course are ungraded. An answer key will be posted on the course website within a few days of the release

More information

KEY WORDS: Microsimulation, Validation, Health Care Reform, Expenditures

KEY WORDS: Microsimulation, Validation, Health Care Reform, Expenditures ALTERNATIVE STRATEGIES FOR IMPUTING PREMIUMS AND PREDICTING EXPENDITURES UNDER HEALTH CARE REFORM Pat Doyle and Dean Farley, Agency for Health Care Policy and Research Pat Doyle, 2101 E. Jefferson St.,

More information

STA2601. Tutorial letter 105/2/2018. Applied Statistics II. Semester 2. Department of Statistics STA2601/105/2/2018 TRIAL EXAMINATION PAPER

STA2601. Tutorial letter 105/2/2018. Applied Statistics II. Semester 2. Department of Statistics STA2601/105/2/2018 TRIAL EXAMINATION PAPER STA2601/105/2/2018 Tutorial letter 105/2/2018 Applied Statistics II STA2601 Semester 2 Department of Statistics TRIAL EXAMINATION PAPER Define tomorrow. university of south africa Dear Student Congratulations

More information

The data definition file provided by the authors is reproduced below: Obs: 1500 home sales in Stockton, CA from Oct 1, 1996 to Nov 30, 1998

The data definition file provided by the authors is reproduced below: Obs: 1500 home sales in Stockton, CA from Oct 1, 1996 to Nov 30, 1998 Economics 312 Sample Project Report Jeffrey Parker Introduction This project is based on Exercise 2.12 on page 81 of the Hill, Griffiths, and Lim text. It examines how the sale price of houses in Stockton,

More information

Quantitative Methods

Quantitative Methods THE ASSOCIATION OF BUSINESS EXECUTIVES DIPLOMA PART 2 QM Quantitative Methods afternoon 26 May 2004 1 Time allowed: 3 hours. 2 Answer any FOUR questions. 3 All questions carry 25 marks. Marks for subdivisions

More information

When determining but for sales in a commercial damages case,

When determining but for sales in a commercial damages case, JULY/AUGUST 2010 L I T I G A T I O N S U P P O R T Choosing a Sales Forecasting Model: A Trial and Error Process By Mark G. Filler, CPA/ABV, CBA, AM, CVA When determining but for sales in a commercial

More information

STATISTICAL DISTRIBUTIONS AND THE CALCULATOR

STATISTICAL DISTRIBUTIONS AND THE CALCULATOR STATISTICAL DISTRIBUTIONS AND THE CALCULATOR 1. Basic data sets a. Measures of Center - Mean ( ): average of all values. Characteristic: non-resistant is affected by skew and outliers. - Median: Either

More information

University of Nottingham

University of Nottingham University of Nottingham BUSINESS SCHOOL A LEVEL 2 MODULE, SPRING SEMESTER 2011 2012 INTRODUCTORY ECONOMETRICS Time allowed TWO hours Candidates must NOT start writing their answers until told to do so

More information

Web Appendix Figure 1. Operational Steps of Experiment

Web Appendix Figure 1. Operational Steps of Experiment Web Appendix Figure 1. Operational Steps of Experiment 57,533 direct mail solicitations with randomly different offer interest rates sent out to former clients. 5,028 clients go to branch and apply for

More information

Analyzing the Impact of County Radon Levels and Population Size on the Allocation of the State Indoor Radon Grant (SIRG) Funds

Analyzing the Impact of County Radon Levels and Population Size on the Allocation of the State Indoor Radon Grant (SIRG) Funds San Jose State University SJSU ScholarWorks Master's Theses Master's Theses and Graduate Research Fall 202 Analyzing the Impact of County Radon Levels and Population Size on the Allocation of the State

More information

A1. Relating Level and Slope to Expected Inflation and Output Dynamics

A1. Relating Level and Slope to Expected Inflation and Output Dynamics Appendix 1 A1. Relating Level and Slope to Expected Inflation and Output Dynamics This section provides a simple illustrative example to show how the level and slope factors incorporate expectations regarding

More information

Multiple Regression. Review of Regression with One Predictor

Multiple Regression. Review of Regression with One Predictor Fall Semester, 2001 Statistics 621 Lecture 4 Robert Stine 1 Preliminaries Multiple Regression Grading on this and other assignments Assignment will get placed in folder of first member of Learning Team.

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Exam Name The bar graph shows the number of tickets sold each week by the garden club for their annual flower show. ) During which week was the most number of tickets sold? ) A) Week B) Week C) Week 5

More information

Chapter 6 Simple Correlation and

Chapter 6 Simple Correlation and Contents Chapter 1 Introduction to Statistics Meaning of Statistics... 1 Definition of Statistics... 2 Importance and Scope of Statistics... 2 Application of Statistics... 3 Characteristics of Statistics...

More information

The instructions on this page also work for the TI-83 Plus and the TI-83 Plus Silver Edition.

The instructions on this page also work for the TI-83 Plus and the TI-83 Plus Silver Edition. The instructions on this page also work for the TI-83 Plus and the TI-83 Plus Silver Edition. The position of the graphically represented keys can be found by moving your mouse on top of the graphic. Turn

More information

ME3620. Theory of Engineering Experimentation. Spring Chapter III. Random Variables and Probability Distributions.

ME3620. Theory of Engineering Experimentation. Spring Chapter III. Random Variables and Probability Distributions. ME3620 Theory of Engineering Experimentation Chapter III. Random Variables and Probability Distributions Chapter III 1 3.2 Random Variables In an experiment, a measurement is usually denoted by a variable

More information

The Multivariate Regression Model

The Multivariate Regression Model The Multivariate Regression Model Example Determinants of College GPA Sample of 4 Freshman Collect data on College GPA (4.0 scale) Look at importance of ACT Consider the following model CGPA ACT i 0 i

More information

The line drawn for part (a) will depend on each student s subjective choice about the position of the line. For this reason, it has been omitted.

The line drawn for part (a) will depend on each student s subjective choice about the position of the line. For this reason, it has been omitted. CHAPTER 2 Exercise Answers EXERCISE 2.3 (a) The line drawn for part (a) will depend on each student s subjective choice about the position of the line. For this reason, it has been omitted. (b) b2 1.514286

More information

**BEGINNING OF EXAMINATION** A random sample of five observations from a population is:

**BEGINNING OF EXAMINATION** A random sample of five observations from a population is: **BEGINNING OF EXAMINATION** 1. You are given: (i) A random sample of five observations from a population is: 0.2 0.7 0.9 1.1 1.3 (ii) You use the Kolmogorov-Smirnov test for testing the null hypothesis,

More information

Quantitative Methods

Quantitative Methods THE ASSOCIATION OF BUSINESS EXECUTIVES DIPLOMA PART 2 QM Quantitative Methods afternoon 27 November 2002 1 Time allowed: 3 hours. 2 Answer any FOUR questions. 3 All questions carry 25 marks. Marks for

More information

Topic 30: Random Effects Modeling

Topic 30: Random Effects Modeling Topic 30: Random Effects Modeling Outline One-way random effects model Data Model Inference Data for one-way random effects model Y, the response variable Factor with levels i = 1 to r Y ij is the j th

More information

Survey Sampling, Fall, 2006, Columbia University Homework assignments (2 Sept 2006)

Survey Sampling, Fall, 2006, Columbia University Homework assignments (2 Sept 2006) Survey Sampling, Fall, 2006, Columbia University Homework assignments (2 Sept 2006) Assignment 1, due lecture 3 at the beginning of class 1. Lohr 1.1 2. Lohr 1.2 3. Lohr 1.3 4. Download data from the CBS

More information

Lecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 7.4-1

Lecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 7.4-1 Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola Section 7.4-1 Chapter 7 Estimates and Sample Sizes 7-1 Review and Preview 7- Estimating a Population

More information