KINDLY REFER TO CHAPTER 9 OF THE COMPREHENSIVE VIDEO LECTURES AND READ UP THE TOPICS BELOW BEFORE YOU ATTEMPT THE QUESTIONS THAT FOLLOW.
|
|
|
- Aubrey Shaw
- 5 years ago
- Views:
Transcription
1 KINDLY REFER TO CHAPTER 9 OF THE COMPREHENSIVE VIDEO LECTURES AND READ UP THE TOPICS BELOW BEFORE YOU ATTEMPT THE QUESTIONS THAT FOLLOW. THANKS CIS QA LEVEL 1 WEEK 4 TOPIC: MEASURES OF RELATIONSHIP: CORRELATION AND REGRESSION OBJECTIVE AND SHORT ANSWER QUESTIONS 1. A simple linear regression model for y on x is y a bx where ' a' and 'b' are constants. Then y and x represent which of the following? A. Dependent variable and gradient respectively B. Independent and dependent variables respectively C. Control and independent variables respectively D. Independent and control variables respectively E. Dependent and independent variables respectively STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 1
2 2. If the correlation coefficient of total monthly sales on monthly cost of advertising is 0:89, find the coefficient of determination: A B C D Which of the following can be regarded as a goodness of fit test? A. Chi-Square test. B. ANOVA. C. Poisson distribution test. D. Regression slope test. 4. The correlation coefficient that indicates the weakest linear relationship between two variables is? A STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 2
3 B C D A study was conducted to estimate urban car travel time between locations in two cities. Data was collected for passenger cars and a simple linear regression was conducted using data sets for different types of vehicles, where Y=urban travel time in minutes and X=distance between locations in kilometers. The following regression equation was obtained: Y= x. R2=0.75 What is the estimated increase in travel time for a commuter planning to move 8 km farther from his workplace? A B STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 3
4 C D The correlation coefficient is simply regarded as. 7. There is a perfect relationship between variables X and Y if their product moment correlation is A. Equal to Zero B. Zero C. Less than 1 D. Less or equal to 1 E. Equal to 1 8. Given the following trend equation: Y= x What is the expected value of Y when x is 10? A STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 4
5 B C D The correlation co-efficient that indicates the strongest linear relationship between variables is: A B C D Which of the following statements about covariance and correlation is least likely correct? A. A zero covariance implies there is no linear relationship between the returns on two assets. B. If two assets have perfect negative correlation, the variance of returns for a portfolio that consists of these two assets will equal zero. STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 5
6 C. The covariance of a two-stock portfolio is equal to the correlation coefficient times the standard deviation of one stock s returns times the standard deviation of the other stock s returns. D. None of the above. 11. A study of relationship existing between a population and samples drawn from the population is called 12. The method of least squares is a method of fitting a... equation by...the sum of squares of the deviations of the estimated regression values from the observed values of the series 13. Regression analysis is being used to find the line of best fit (y = a + bx) from eleven pairs of data. The calculations have produced the following information: Σx = 440, Σy = 330, Σx2 = 17,986, Σy2 = 10,366, Σxy = 13,467 and b = What is the value of a in the equation for the line of best fit (to 2 decimal places)? STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 6
7 A B C D Which of the following statements most accurately describes a situation in which the regression coefficient between a security and the market index is 0.4? A. For every percent move in the market, the security's return is expected to change by 0.4% B. The relationship between the two securities is positive; however, the degree to which they move in the same direction is not perfect. C.This certainly implies that the portfolio has a high degree of unsystematic risk. D. Movements in the market explain 40% of the variation in the security's return. STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 7
8 15. When the Correlation Coefficient is positive, it is said to be...correlated 16. Which of the following statements with regards to correlation analysis is not true? A. Correlation simply means an interrelationship or association. B. Correlation analysis always assumes that the relationship between the dependent and independent variable is linear. C. There is positive correlation when movement in one variable causes movement in the same direction in the other variable. D. Coefficient of determination explains that portion of the variability in the dependent variable that is not explained by the independent variable. 17. Given the trend equation Y= x. What does the figure 5.47 represent? A. Slope STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 8
9 B. Intercept C. Derivative D. Rate of change 18. An analyst estimated that ABC s earnings will grow from N3 to N4.50 per share over the next eight years. What is the rate of growth in ABC s earnings? A. 4.9% B. 5.2% C. 6.7% D. 7.2% 19. Regression and correlation are concerned with relationships between variables STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 9
10 20. The coefficient of determination takes on real values between... and Which of the following is/are true? I. Correlation measures pattern of relationships II. When the rank correlation is +1, it means perfect agreement III. Coefficient of determination can only take possible integer values. A. I only B. II only C. III only D. I and II E. II and III 22. Which of the following is/are true of moving average method? I. Extreme values are always lost II. The method is suitable for forecasting STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 10
11 III. It is not good for non-linear trend A. I only B. I and II C. I, II and III D. II only E. III only 23. Observations taken over a period of time often contains the following characteristics EXCEPT A. A long- term trend B. Secular trend C. Moving average method D. Seasonal fluctuations E. Residual variations 24. Which of the following statements is true about uncorrelated variables? STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 11
12 A. No relationship exists between them B. Partial relationship exists between them C. Perfect relationship exists between them D. Inverse relationship exists between them E. Positive relationship exists between them 25. Given the regression line of y on x as y x.The value of regression coefficient is A. 17 B. 3.6 C D E If co-efficient of correlation of a distribution is What is the co-efficient of determination of the same distribution? A STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 12
13 B C D A simple relationship between the Spearman s coefficient of rank correlation (r), the differences in the corresponding pairs of ranks (d) and the total number of rankings (n) is given by... STARRY GOLD ACADEMY , , info@starrygoldacademy.com, Page 13
OCR Maths S1. Topic Questions from Papers. Bivariate Data
OCR Maths S1 Topic Questions from Papers Bivariate Data PhysicsAndMathsTutor.com 1 The scatter diagrams below illustrate three sets of bivariate data, A, B and C. State, with an explanation in each case,
Chapter 10. Correlation and Regression. McGraw-Hill, Bluman, 7th ed., Chapter 10 1
Chapter 10 Correlation and Regression McGraw-Hill, Bluman, 7th ed., Chapter 10 1 Chapter 10 Overview Introduction 10-1 Scatter Plots and Correlation 10- Regression 10-3 Coefficient of Determination and
Interactions. Interactions. Lectures 1 & 2. Linear Relationships. y = a + bx. Slope. Intercept
Interactions Lectures 1 & Regression Sometimes two variables appear related: > smoking and lung cancers > height and weight > years of education and income > engine size and gas mileage > GMAT scores and
(ii) Scan your answer sheets INTO ONE FILE only, and submit it in the drop-box.
FINAL EXAM ** Two different ways to submit your answer sheet (i) Use MS-Word and place it in a drop-box. (ii) Scan your answer sheets INTO ONE FILE only, and submit it in the drop-box. Deadline: December
CORRELATION AND REGRESSION
CORRELATION AND REGRESSION CORRELATION The correlation coefficient is a number, between -1 and +1, which measures the strength of the relationship between two sets of data. The closer the correlation coefficient
regression analysis is a type of inferential statistics which tells us whether relationships between two or more variables exist
regression analysis is a type of inferential statistics which tells us whether relationships between two or more variables exist sales $ (y - dependent variable) advertising $ (x - independent variable)
ADMS2320.com. We Make Stats Easy. Chapter 4. ADMS2320.com Tutorials Past Tests. Tutorial Length 1 Hour 45 Minutes
We Make Stats Easy. Chapter 4 Tutorial Length 1 Hour 45 Minutes Tutorials Past Tests Chapter 4 Page 1 Chapter 4 Note The following topics will be covered in this chapter: Measures of central location Measures
Lecture # 31. Questions of Marks 3. Question: Solution:
Lecture # 31 Given XY = 400, X = 5, Y = 4, S = 4, S = 3, n = 15. Compute the coefficient of correlation between XX and YY. r =0.55 X Y Determine whether two variables XX and YY are correlated or uncorrelated
STATS DOESN T SUCK! ~ CHAPTER 16
SIMPLE LINEAR REGRESSION: STATS DOESN T SUCK! ~ CHAPTER 6 The HR manager at ACME food services wants to examine the relationship between a workers income and their years of experience on the job. He randomly
Forecasting. Dr. Richard Jerz rjerz.com
Forecasting Dr. Richard Jerz 1 1 Learning Objectives Describe why forecasts are used and list the elements of a good forecast. Outline the steps in the forecasting process. Describe at least three qualitative
UNIT-IV CORRELATION AND REGRESSION
Correlation coefficient: UNIT-IV CORRELATION AND REGRESSION The quantity r, called the linear correlation coefficient, measures the strength and the direction of a linear relationship between two variables.
Regression: Ordinary Least Squares
Regression: Ordinary Least Squares Mark Hendricks Autumn 2017 FINM Intro: Regression Outline Regression OLS Mathematics Linear Projection Hendricks, Autumn 2017 FINM Intro: Regression: Lecture 2/32 Regression
QUANTITATIVE TOOLS IN BUSINESS MAY Four Quarterly Moving Total
SOLUTION 1 (a) Q 1 2 3 4 6 7 8 9 10 11 13 14 Sales 200 20 24 214 208 26 260 216 220 260 266 216 218 264 Four Quarterly Moving Total 918 926 932 938 940 92 96 962 962 960 964 Four Quarterly Moving Average
THE ROYAL STATISTICAL SOCIETY 2008 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE (MODULAR FORMAT) MODULE 4 LINEAR MODELS
THE ROYAL STATISTICAL SOCIETY 008 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE (MODULAR FORMAT) MODULE 4 LINEAR MODELS The Society provides these solutions to assist candidates preparing for the examinations
About Bivariate Correlations and Linear Regression
About Bivariate Correlations and Linear Regression TABLE OF CONTENTS About Bivariate Correlations and Linear Regression... 1 What is BIVARIATE CORRELATION?... 1 What is LINEAR REGRESSION... 1 Bivariate
Chapter 10. Correlation and Regression. McGraw-Hill, Bluman, 7th ed., Chapter 10 1
Chapter 10 Correlation and Regression McGraw-Hill, Bluman, 7th ed., Chapter 10 1 Example 10-2: Absences/Final Grades Please enter the data below in L1 and L2. The data appears on page 537 of your textbook.
Statistical Techniques II EXST7015 Simple Linear Regression
Statistical Techniques II EXST7015 Simple Linear Regression 03a_SLR 1 Y - the dependent variable 35 30 25 The objective Given points plotted on two coordinates, Y and X, find the best line to fit the data.
Correlation and Regression
Correlation and Regression 1 Overview Introduction Scatter Plots Correlation Regression Coefficient of Determination 2 Objectives of the topic 1. Draw a scatter plot for a set of ordered pairs. 2. Compute
QUESTIONS 1-46 REVIEW THE OBJECTIVES OF CHAPTER 2.
MAT 101 Course Review Questions Valid for Fall 2014, Spring 2015 and Summer 2015 MIDTERM EXAM FINAL EXAM Questions 1-86 are covered on the Midterm. There are 25 questions on the midterm, all multiple choice,
CORRELATION AND REGRESSION
CORRELATION AND REGRESSION CORRELATION Introduction CORRELATION problems which involve measuring the strength of a relationship. Correlation Analysis involves various methods and techniques used for studying
CORRELATION AND SIMPLE REGRESSION 10.0 OBJECTIVES 10.1 INTRODUCTION
UNIT 10 CORRELATION AND SIMPLE REGRESSION STRUCTURE 10.0 Objectives 10.1 Introduction 10. Correlation 10..1 Scatter Diagram 10.3 The Correlation Coefficient 10.3.1 Karl Pearson s Correlation Coefficient
Wooldridge, Introductory Econometrics, 4th ed. Chapter 2: The simple regression model
Wooldridge, Introductory Econometrics, 4th ed. Chapter 2: The simple regression model Most of this course will be concerned with use of a regression model: a structure in which one or more explanatory
* Tuesday 17 January :30-16:30 (2 hours) Recored on ESSE3 General introduction to the course.
Name of the course Statistical methods and data analysis Audience The course is intended for students of the first or second year of the Graduate School in Materials Engineering. The aim of the course
4/22/2010. Test 3 Review ANOVA
Test 3 Review ANOVA 1 School recruiter wants to examine if there are difference between students at different class ranks in their reported intensity of school spirit. What is the factor? How many levels
Bivariate Relationships Between Variables
Bivariate Relationships Between Variables BUS 735: Business Decision Making and Research 1 Goals Specific goals: Detect relationships between variables. Be able to prescribe appropriate statistical methods
Lecture 4 Forecasting
King Saud University College of Computer & Information Sciences IS 466 Decision Support Systems Lecture 4 Forecasting Dr. Mourad YKHLEF The slides content is derived and adopted from many references Outline
The Multiple Regression Model
Multiple Regression The Multiple Regression Model Idea: Examine the linear relationship between 1 dependent (Y) & or more independent variables (X i ) Multiple Regression Model with k Independent Variables:
Simple Linear Regression
Simple Linear Regression Christopher Ting Christopher Ting : christophert@smu.edu.sg : 688 0364 : LKCSB 5036 January 7, 017 Web Site: http://www.mysmu.edu/faculty/christophert/ Christopher Ting QF 30 Week
Ch 13 & 14 - Regression Analysis
Ch 3 & 4 - Regression Analysis Simple Regression Model I. Multiple Choice:. A simple regression is a regression model that contains a. only one independent variable b. only one dependent variable c. more
EXAMINATIONS OF THE ROYAL STATISTICAL SOCIETY
EXAMINATIONS OF THE ROYAL STATISTICAL SOCIETY HIGHER CERTIFICATE IN STATISTICS, 2011 MODULE 4 : Linear models Time allowed: One and a half hours Candidates should answer THREE questions. Each question
Correlation & Regression. Dr. Moataza Mahmoud Abdel Wahab Lecturer of Biostatistics High Institute of Public Health University of Alexandria
بسم الرحمن الرحيم Correlation & Regression Dr. Moataza Mahmoud Abdel Wahab Lecturer of Biostatistics High Institute of Public Health University of Alexandria Correlation Finding the relationship between
Glossary. The ISI glossary of statistical terms provides definitions in a number of different languages:
Glossary The ISI glossary of statistical terms provides definitions in a number of different languages: http://isi.cbs.nl/glossary/index.htm Adjusted r 2 Adjusted R squared measures the proportion of the
C. 3 PRACTICE FINAL EXAM. 1. Simplify B. 2. D. E. None of the above. 2. Factor. completely. E. None of the above. 3.
MA 1500 1. Simplify ; A. B. 2 C. 2. Factor 8 completely. A. x y x + y B. x 2y C. 2x y 2x + y 2x y. Simplify ( ) ; A. a b c B. C. a b c a b 6c c a b 1 MA 1500 4. Subtract and simplify. + 2 A. x: x ; x;
CORRELATION ANALYSIS. Dr. Anulawathie Menike Dept. of Economics
CORRELATION ANALYSIS Dr. Anulawathie Menike Dept. of Economics 1 What is Correlation The correlation is one of the most common and most useful statistics. It is a term used to describe the relationship
A LEVEL MATHEMATICS QUESTIONBANKS REGRESSION AND CORRELATION. 1. Sketch scatter diagrams with at least 5 points to illustrate the following:
1. Sketch scatter diagrams with at least 5 points to illustrate the following: a) Data with a product moment correlation coefficient of 1 b) Data with a rank correlation coefficient of 1, but product moment
Can you tell the relationship between students SAT scores and their college grades?
Correlation One Challenge Can you tell the relationship between students SAT scores and their college grades? A: The higher SAT scores are, the better GPA may be. B: The higher SAT scores are, the lower
Chapter 12 Summarizing Bivariate Data Linear Regression and Correlation
Chapter 1 Summarizing Bivariate Data Linear Regression and Correlation This chapter introduces an important method for making inferences about a linear correlation (or relationship) between two variables,
CHANCE Program. Admissions Mathematics Practice Test. Part One will test your background in basic arithmetic, while Part Two will cover basic algebra.
CHANCE Program Admissions Mathematics Practice Test Part One will test your background in basic arithmetic, while Part Two will cover basic algebra. Each part of the test has 30 questions and has been
MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option:
MTH302 Quiz # 4 Solved By konenuchiha@gmail.com When a coin is tossed once, the probability of getting head is. 0.55 0.52 0.50 (1/2) 0.51 Suppose the slope of regression line is 20 and the intercept is
Mathematics for Economics MA course
Mathematics for Economics MA course Simple Linear Regression Dr. Seetha Bandara Simple Regression Simple linear regression is a statistical method that allows us to summarize and study relationships between
1: PROBABILITY REVIEW
1: PROBABILITY REVIEW Marek Rutkowski School of Mathematics and Statistics University of Sydney Semester 2, 2016 M. Rutkowski (USydney) Slides 1: Probability Review 1 / 56 Outline We will review the following
Marquette University Executive MBA Program Statistics Review Class Notes Summer 2018
Marquette University Executive MBA Program Statistics Review Class Notes Summer 2018 Chapter One: Data and Statistics Statistics A collection of procedures and principles
Trendlines Simple Linear Regression Multiple Linear Regression Systematic Model Building Practical Issues
Trendlines Simple Linear Regression Multiple Linear Regression Systematic Model Building Practical Issues Overfitting Categorical Variables Interaction Terms Non-linear Terms Linear Logarithmic y = a +
GROUPED DATA E.G. FOR SAMPLE OF RAW DATA (E.G. 4, 12, 7, 5, MEAN G x / n STANDARD DEVIATION MEDIAN AND QUARTILES STANDARD DEVIATION
FOR SAMPLE OF RAW DATA (E.G. 4, 1, 7, 5, 11, 6, 9, 7, 11, 5, 4, 7) BE ABLE TO COMPUTE MEAN G / STANDARD DEVIATION MEDIAN AND QUARTILES Σ ( Σ) / 1 GROUPED DATA E.G. AGE FREQ. 0-9 53 10-19 4...... 80-89
Chapter 14 Simple Linear Regression (A)
Chapter 14 Simple Linear Regression (A) 1. Characteristics Managerial decisions often are based on the relationship between two or more variables. can be used to develop an equation showing how the variables
Basic Business Statistics 6 th Edition
Basic Business Statistics 6 th Edition Chapter 12 Simple Linear Regression Learning Objectives In this chapter, you learn: How to use regression analysis to predict the value of a dependent variable based
Markowitz Efficient Portfolio Frontier as Least-Norm Analytic Solution to Underdetermined Equations
Markowitz Efficient Portfolio Frontier as Least-Norm Analytic Solution to Underdetermined Equations Sahand Rabbani Introduction Modern portfolio theory deals in part with the efficient allocation of investments
Lecture 13. Simple Linear Regression
1 / 27 Lecture 13 Simple Linear Regression October 28, 2010 2 / 27 Lesson Plan 1. Ordinary Least Squares 2. Interpretation 3 / 27 Motivation Suppose we want to approximate the value of Y with a linear
Final Exam Bus 320 Spring 2000 Russell
Name Final Exam Bus 320 Spring 2000 Russell Do not turn over this page until you are told to do so. You will have 3 hours minutes to complete this exam. The exam has a total of 100 points and is divided
Predicted Y Scores. The symbol stands for a predicted Y score
REGRESSION 1 Linear Regression Linear regression is a statistical procedure that uses relationships to predict unknown Y scores based on the X scores from a correlated variable. 2 Predicted Y Scores Y
ECON2228 Notes 2. Christopher F Baum. Boston College Economics. cfb (BC Econ) ECON2228 Notes / 47
ECON2228 Notes 2 Christopher F Baum Boston College Economics 2014 2015 cfb (BC Econ) ECON2228 Notes 2 2014 2015 1 / 47 Chapter 2: The simple regression model Most of this course will be concerned with
Correlation and Regression
Edexcel GCE Core Mathematics S1 Correlation and Regression Materials required for examination Mathematical Formulae (Green) Items included with question papers Nil Advice to Candidates You must ensure
MA 575 Linear Models: Cedric E. Ginestet, Boston University Mixed Effects Estimation, Residuals Diagnostics Week 11, Lecture 1
MA 575 Linear Models: Cedric E Ginestet, Boston University Mixed Effects Estimation, Residuals Diagnostics Week 11, Lecture 1 1 Within-group Correlation Let us recall the simple two-level hierarchical
9 Correlation and Regression
9 Correlation and Regression SW, Chapter 12. Suppose we select n = 10 persons from the population of college seniors who plan to take the MCAT exam. Each takes the test, is coached, and then retakes the
Kansas City Area Teachers of Mathematics 2018 KCATM Math Competition ALGEBRA GRADE 7
Kansas City Area Teachers of Mathematics 2018 KCATM Math Competition ALGEBRA GRADE 7 INSTRUCTIONS Do not open this booklet until instructed to do so. Time limit: 20 minutes You may use calculators. Mark
Lecture 14. Analysis of Variance * Correlation and Regression. The McGraw-Hill Companies, Inc., 2000
Lecture 14 Analysis of Variance * Correlation and Regression Outline Analysis of Variance (ANOVA) 11-1 Introduction 11-2 Scatter Plots 11-3 Correlation 11-4 Regression Outline 11-5 Coefficient of Determination
Lecture 14. Outline. Outline. Analysis of Variance * Correlation and Regression Analysis of Variance (ANOVA)
Outline Lecture 14 Analysis of Variance * Correlation and Regression Analysis of Variance (ANOVA) 11-1 Introduction 11- Scatter Plots 11-3 Correlation 11-4 Regression Outline 11-5 Coefficient of Determination
Table 2.1 presents examples and explains how the proper results should be written. Table 2.1: Writing Your Results When Adding or Subtracting
When you complete a laboratory investigation, it is important to make sense of your data by summarizing it, describing the distributions, and clarifying messy data. Analyzing your data will allow you to
Finding Relationships Among Variables
Finding Relationships Among Variables BUS 230: Business and Economic Research and Communication 1 Goals Specific goals: Re-familiarize ourselves with basic statistics ideas: sampling distributions, hypothesis
Lecture 2: Linear and Mixed Models
Lecture 2: Linear and Mixed Models Bruce Walsh lecture notes Introduction to Mixed Models SISG, Seattle 18 20 July 2018 1 Quick Review of the Major Points The general linear model can be written as y =
1-2 Analyzing Graphs of Functions and Relations
Use the graph of each function to estimate the indicated function values. Then confirm the estimate algebraically. Round to the nearest hundredth, if necessary. 2. 6. a. h( 1) b. h(1.5) c. h(2) a. g( 2)
not to be republished NCERT Correlation CHAPTER 1. INTRODUCTION
CHAPTER 7 Studying this chapter should enable you to: understand the meaning of the term correlation; understand the nature of relationship between two variables; calculate the different measures of correlation;
MTH 302 long questions solved by Pisces girl My Lord! Increase me in knowledge.
MTH 302 long questions solved by Pisces girl My Lord! Increase me in knowledge. Question No: 5 ( Marks: 3 ) In a school, 50% students study science subjects and 30% of them study biology. What is the probability
TABLES AND FORMULAS FOR MOORE Basic Practice of Statistics
TABLES AND FORMULAS FOR MOORE Basic Practice of Statistics Exploring Data: Distributions Look for overall pattern (shape, center, spread) and deviations (outliers). Mean (use a calculator): x = x 1 + x
LI EAR REGRESSIO A D CORRELATIO
CHAPTER 6 LI EAR REGRESSIO A D CORRELATIO Page Contents 6.1 Introduction 10 6. Curve Fitting 10 6.3 Fitting a Simple Linear Regression Line 103 6.4 Linear Correlation Analysis 107 6.5 Spearman s Rank Correlation
BNAD 276 Lecture 10 Simple Linear Regression Model
1 / 27 BNAD 276 Lecture 10 Simple Linear Regression Model Phuong Ho May 30, 2017 2 / 27 Outline 1 Introduction 2 3 / 27 Outline 1 Introduction 2 4 / 27 Simple Linear Regression Model Managerial decisions
Probabilities & Statistics Revision
Probabilities & Statistics Revision Christopher Ting Christopher Ting http://www.mysmu.edu/faculty/christophert/ : christopherting@smu.edu.sg : 6828 0364 : LKCSB 5036 January 6, 2017 Christopher Ting QF
Simultaneous Equation Models (Book Chapter 5)
Simultaneous Equation Models (Book Chapter 5) Interrelated equations with continuous dependent variables: Utilization of individual vehicles (measured in kilometers driven) in multivehicle households Interrelation
The P/Q Mathematics Study Guide
The P/Q Mathematics Study Guide Copyright 007 by Lawrence Perez and Patrick Quigley All Rights Reserved Table of Contents Ch. Numerical Operations - Integers... - Fractions... - Proportion and Percent...
Correlation. A statistics method to measure the relationship between two variables. Three characteristics
Correlation Correlation A statistics method to measure the relationship between two variables Three characteristics Direction of the relationship Form of the relationship Strength/Consistency Direction
Kansas City Area Teachers of Mathematics 2018 KCATM Math Competition ALGEBRA GRADE 8
Kansas City Area Teachers of Mathematics 2018 KCATM Math Competition ALGEBRA GRADE 8 INSTRUCTIONS Do not open this booklet until instructed to do so. Time limit: 20 minutes You may use calculators. Mark
Lecture 16 - Correlation and Regression
Lecture 16 - Correlation and Regression Statistics 102 Colin Rundel April 1, 2013 Modeling numerical variables Modeling numerical variables So far we have worked with single numerical and categorical variables,
Dr. Junchao Xia Center of Biophysics and Computational Biology. Fall /1/2016 1/46
BIO5312 Biostatistics Lecture 10:Regression and Correlation Methods Dr. Junchao Xia Center of Biophysics and Computational Biology Fall 2016 11/1/2016 1/46 Outline In this lecture, we will discuss topics
Chapter 7 Student Lecture Notes 7-1
Chapter 7 Student Lecture Notes 7- Chapter Goals QM353: Business Statistics Chapter 7 Multiple Regression Analysis and Model Building After completing this chapter, you should be able to: Explain model
Module 7 Practice problem and Homework answers
Module 7 Practice problem and Homework answers Practice problem, page 1 Is the research hypothesis one-tailed or two-tailed? Answer: one tailed In the set up for the problem, we predicted a specific outcome
Stochastic Processes
Stochastic Processes Stochastic Process Non Formal Definition: Non formal: A stochastic process (random process) is the opposite of a deterministic process such as one defined by a differential equation.
Least Squares Regression
Least Squares Regression Sections 5.3 & 5.4 Cathy Poliak, Ph.D. cathy@math.uh.edu Office in Fleming 11c Department of Mathematics University of Houston Lecture 14-2311 Cathy Poliak, Ph.D. cathy@math.uh.edu
Worksheet Topic 1 Order of operations, combining like terms 2 Solving linear equations 3 Finding slope between two points 4 Solving linear equations
Worksheet Topic 1 Order of operations, combining like terms 2 Solving linear equations 3 Finding slope between two points 4 Solving linear equations 5 Multiplying binomials 6 Practice with exponents 7
Business Statistics. Chapter 14 Introduction to Linear Regression and Correlation Analysis QMIS 220. Dr. Mohammad Zainal
Department of Quantitative Methods & Information Systems Business Statistics Chapter 14 Introduction to Linear Regression and Correlation Analysis QMIS 220 Dr. Mohammad Zainal Chapter Goals After completing
Algebra I Final Study Guide
2011-2012 Algebra I Final Study Guide Short Answer Source: www.cityoforlando.net/public_works/stormwater/rain/rainfall.htm 1. For which one month period was the rate of change in rainfall amounts in Orlando
Categorical Predictor Variables
Categorical Predictor Variables We often wish to use categorical (or qualitative) variables as covariates in a regression model. For binary variables (taking on only 2 values, e.g. sex), it is relatively
Unit 4 Study Guide Part I: Equations of Lines
Unit 4 Study Guide Part I: Equations of Lines Write out the general equations for: Point Slope Form: Slope-Intercept Form: Standard Form: 1. Given the points: (3, -7) and (-2, 8) a. Write an equation in
Operations Management
Operations Management Chapter 4 Forecasting PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 7e Operations Management, 9e 2008 Prentice Hall, Inc. 4 1 Outline Global
SMAM 319 Exam 1 Name. 1.Pick the best choice for the multiple choice questions below (10 points 2 each)
SMAM 319 Exam 1 Name 1.Pick the best choice for the multiple choice questions below (10 points 2 each) A b In Metropolis there are some houses for sale. Superman and Lois Lane are interested in the average
Correlation and Linear Regression
Correlation and Linear Regression Correlation: Relationships between Variables So far, nearly all of our discussion of inferential statistics has focused on testing for differences between group means
The Simple Regression Model. Simple Regression Model 1
The Simple Regression Model Simple Regression Model 1 Simple regression model: Objectives Given the model: - where y is earnings and x years of education - Or y is sales and x is spending in advertising
Regression. Estimation of the linear function (straight line) describing the linear component of the joint relationship between two variables X and Y.
Regression Bivariate i linear regression: Estimation of the linear function (straight line) describing the linear component of the joint relationship between two variables and. Generally describe as a
Simple Linear Regression
Simple Linear Regression ST 430/514 Recall: A regression model describes how a dependent variable (or response) Y is affected, on average, by one or more independent variables (or factors, or covariates)
V3: Circadian rhythms, time-series analysis (contd )
V3: Circadian rhythms, time-series analysis (contd ) Introduction: 5 paragraphs (1) Insufficient sleep - Biological/medical relevance (2) Previous work on effects of insufficient sleep in rodents (dt.
ASU Mathematics Placement Test Sample Problems June, 2000
ASU Mathematics Placement Test Sample Problems June, 000. Evaluate (.5)(0.06). Evaluate (.06) (0.08). Evaluate ( ) 5. Evaluate [ 8 + ( 9) ] 5. Evaluate 7 + ( ) 6. Evaluate ( 8) 7. Evaluate 5 ( 8. Evaluate
Chapter 14 Student Lecture Notes Department of Quantitative Methods & Information Systems. Business Statistics. Chapter 14 Multiple Regression
Chapter 14 Student Lecture Notes 14-1 Department of Quantitative Methods & Information Systems Business Statistics Chapter 14 Multiple Regression QMIS 0 Dr. Mohammad Zainal Chapter Goals After completing
Time series and Forecasting
Chapter 2 Time series and Forecasting 2.1 Introduction Data are frequently recorded at regular time intervals, for instance, daily stock market indices, the monthly rate of inflation or annual profit figures.
Review. Midterm Exam. Midterm Review. May 6th, 2015 AMS-UCSC. Spring Session 1 (Midterm Review) AMS-5 May 6th, / 24
Midterm Exam Midterm Review AMS-UCSC May 6th, 2015 Spring 2015. Session 1 (Midterm Review) AMS-5 May 6th, 2015 1 / 24 Topics Topics We will talk about... 1 Review Spring 2015. Session 1 (Midterm Review)
Multiple Regression. More Hypothesis Testing. More Hypothesis Testing The big question: What we really want to know: What we actually know: We know:
Multiple Regression Ψ320 Ainsworth More Hypothesis Testing What we really want to know: Is the relationship in the population we have selected between X & Y strong enough that we can use the relationship
ECM Final Exam Review. 6. Solve: 2x 3y =6 2x 6y =9
Name: Date: 1. On January 1, 2000, a car had a value of $15,000. Each year after that, the car s value will decrease by 20 percent of the previous year s value. Which expression represents the car s value
Exam details. Final Review Session. Things to Review
Exam details Final Review Session Short answer, similar to book problems Formulae and tables will be given You CAN use a calculator Date and Time: Dec. 7, 006, 1-1:30 pm Location: Osborne Centre, Unit
SMAM 319 Exam1 Name. a B.The equation of a line is 3x + y =6. The slope is a. -3 b.3 c.6 d.1/3 e.-1/3
SMAM 319 Exam1 Name 1. Pick the best choice. (10 points-2 each) _c A. A data set consisting of fifteen observations has the five number summary 4 11 12 13 15.5. For this data set it is definitely true
Test 3 Practice Test A. NOTE: Ignore Q10 (not covered)
Test 3 Practice Test A NOTE: Ignore Q10 (not covered) MA 180/418 Midterm Test 3, Version A Fall 2010 Student Name (PRINT):............................................. Student Signature:...................................................
ECON 427: ECONOMIC FORECASTING. Ch1. Getting started OTexts.org/fpp2/
ECON 427: ECONOMIC FORECASTING Ch1. Getting started OTexts.org/fpp2/ 1 Outline 1 What can we forecast? 2 Time series data 3 Some case studies 4 The statistical forecasting perspective 2 Forecasting is
FinQuiz Notes
Reading 9 A time series is any series of data that varies over time e.g. the quarterly sales for a company during the past five years or daily returns of a security. When assumptions of the regression