 What is correlation?  How to compute?  How to interpret? 2.

Slides:



Advertisements
Similar presentations
Psychology Practical (Year 2) PS2001 Correlation and other topics.
Advertisements

Chapter 16: Correlation.
Chapter 6: Correlational Research Examine whether variables are related to one another (whether they vary together). Correlation coefficient: statistic.
Correlation CJ 526 Statistical Analysis in Criminal Justice.
Correlation Chapter 9.
Chapter 15 (Ch. 13 in 2nd Can.) Association Between Variables Measured at the Interval-Ratio Level: Bivariate Correlation and Regression.
Section #1 Quiz 1 Stem and Leaf Plot (N=29) X|8 2| | |00 Mean=29.9; M=30; Mode= 29; s=6.38;
CJ 526 Statistical Analysis in Criminal Justice
Chapter 5: Correlation Coefficients
Regression and Correlation
Correlation Relationship between Variables. Statistical Relationships What is the difference between correlation and regression? Correlation: measures.
S519: Evaluation of Information Systems Social Statistics Ch5: Correlation.
Lecture 17: Correlations – Describing Relationships Between Two Variables 2011, 11, 22.
Correlation and Regression. Relationships between variables Example: Suppose that you notice that the more you study for an exam, the better your score.
Chapter 21 Correlation. Correlation A measure of the strength of a linear relationship Although there are at least 6 methods for measuring correlation,
Week 11 Chapter 12 – Association between variables measured at the nominal level.
Correlation and Regression A BRIEF overview Correlation Coefficients l Continuous IV & DV l or dichotomous variables (code as 0-1) n mean interpreted.
Scatterplots and Correlation BPS chapter 4 © 2006 W.H. Freeman and Company.
Week 12 Chapter 13 – Association between variables measured at the ordinal level & Chapter 14: Association Between Variables Measured at the Interval-Ratio.
Joint Distributions AND CORRELATION Coefficients (Part 3)
Bivariate Correlation Lesson 10. Measuring Relationships n Correlation l degree relationship b/n 2 variables l linear predictive relationship n Covariance.
SHOWTIME! STATISTICAL TOOLS IN EVALUATION CORRELATION TECHNIQUE SIMPLE PREDICTION TESTS OF DIFFERENCE.
STAT 211 – 019 Dan Piett West Virginia University Lecture 2.
MEASURES OF RELATIONSHIP Correlations. Key Concepts Pearson Correlation  interpretation  limits  computation  graphing Factors that affect the Pearson.
Bivariate Relationships Analyzing two variables at a time, usually the Independent & Dependent Variables Like one variable at a time, this can be done.
Chapter 14 – Correlation and Simple Regression Math 22 Introductory Statistics.
Chapter 3 Correlation. Suppose we found the age and weight of a sample of 10 adults. Create a scatterplot of the data below. Is there any relationship.
Irkutsk State Medical University Department of Faculty Therapy Correlations Khamaeva A. A. Irkutsk, 2009.
Bivariate Correlation Lesson 11. Measuring Relationships n Correlation l degree relationship b/n 2 variables l linear predictive relationship n Covariance.
Statistics in Applied Science and Technology Chapter 13, Correlation and Regression Part I, Correlation (Measure of Association)
WELCOME TO THETOPPERSWAY.COM.
Experimental Research Methods in Language Learning Chapter 11 Correlational Analysis.
Correlations. Outline What is a correlation? What is a correlation? What is a scatterplot? What is a scatterplot? What type of information is provided.
Basic Statistics Correlation Var Relationships Associations.
1 Further Maths Chapter 4 Displaying and describing relationships between two variables.
B AD 6243: Applied Univariate Statistics Correlation Professor Laku Chidambaram Price College of Business University of Oklahoma.
Figure 15-3 (p. 512) Examples of positive and negative relationships. (a) Beer sales are positively related to temperature. (b) Coffee sales are negatively.
When trying to explain some of the patterns you have observed in your species and community data, it sometimes helps to have a look at relationships between.
Investigating the Relationship between Scores
The Correlational Research Strategy
Correlation.
URBP 204A QUANTITATIVE METHODS I Statistical Analysis Lecture IV Gregory Newmark San Jose State University (This lecture is based on Chapters 5,12,13,
Introduction to Correlation Analysis. Objectives Correlation Types of Correlation Karl Pearson’s coefficient of correlation Correlation in case of bivariate.
Semester 2: Lecture 5 Quantitative Data Analysis: Bivariate Analysis 2 – Identifying Correlations using Parametric and Non-Parametric Tests Prepared by:
Chapter 16 Data Analysis: Testing for Associations.
CORRELATIONAL RESEARCH STUDIES
U Describes the relationship between two or more variables. Describes the strength of the relationship in terms of a number from -1.0 to Describes.
Describing Relationships Using Correlations. 2 More Statistical Notation Correlational analysis requires scores from two variables. X stands for the scores.
Chapter Thirteen Copyright © 2006 John Wiley & Sons, Inc. Bivariate Correlation and Regression.
Chapter Bivariate Data (x,y) data pairs Plotted with Scatter plots x = explanatory variable; y = response Bivariate Normal Distribution – for.
Section 5.1: Correlation. Correlation Coefficient A quantitative assessment of the strength of a relationship between the x and y values in a set of (x,y)
Chapter 9: Correlation and Regression Analysis. Correlation Correlation is a numerical way to measure the strength and direction of a linear association.
Correlations. Distinguishing Characteristics of Correlation Correlational procedures involve one sample containing all pairs of X and Y scores Correlational.
CHAPTER 4 CORRELATION.
Chapter 16: Correlation. So far… We’ve focused on hypothesis testing Is the relationship we observe between x and y in our sample true generally (i.e.
UNIT 4 Bivariate Data Scatter Plots and Regression.
.  Relationship between two sets of data  The word Correlation is made of Co- (meaning "together"), and Relation  Correlation is Positive when the.
CORRELATION ANALYSIS.
SOCW 671 #11 Correlation and Regression. Uses of Correlation To study the strength of a relationship To study the direction of a relationship Scattergrams.
Chapter 15 Association Between Variables Measured at the Interval-Ratio Level.
©2013, The McGraw-Hill Companies, Inc. All Rights Reserved Chapter 3 Investigating the Relationship of Scores.
Chapter 2 Bivariate Data Scatterplots.   A scatterplot, which gives a visual display of the relationship between two variables.   In analysing the.
Correlations FSE 200.
Simple Linear Correlation
Chapter 10 CORRELATION.
Scatterplots and Correlation
EDRS6208 Fundamentals of Education Research 1
CORRELATION ANALYSIS.
4/4/2019 Correlations.
Correlation & Trend Lines
Presentation transcript:

 What is correlation?  How to compute?  How to interpret? 2

 The relations between two variables  How the value of one variable changes when the value of another variable changes  A correlation coefficient is a numerical index to reflect the relationship between two variables.  Range: -1 ~ +1  Bivariate correlation (for two variables) 3

 Parametric  Pearson product-moment correlation (named for inventor Karl Pearson)  Non-parametric  Spearman’s rank correlation  Kendall tau rank correlation coefficient 4

 For two variables which are continuous in nature  Height, age, test score, income  But not for discrete or categorical variables  Race, political affiliation, social class, rank R xy is the correlation between variable X and variable Y 5

 Direct correlation (positive correlation):  If both variables change in the same direction  Indirect correlation (negative correlation):  If both variables change in opposite directions 6

 Below is Correlation Report of different Currency Exchange Rate on November 13 – 2014 (source: Bloomberg Terminal)  -0.8 and 0.5, which is stronger? 7

the correlation coefficient between X and Y n the size of the sample X the individual’s score on the X variable Ythe individual’s score on the Y variable XYthe product of each X score times its corresponding Y score X 2 the individual X score, squared Y 2 the individual Y score, squared 8

 Calculate Pearson correlation coefficient for US school enrollment (unit: k) in some time points of previous 50 years. (Source: United States Census Bureau) 1. Select two columns of data – are they correlated? 2. What does this correlated mean? 9 Year G9-12 Public G9-12 Private College- Public College- Private

 CORREL function  Or PEARSON function 10

 Scatterplot or scattergram X Y 11 XY

12

 r =1, a perfect direct (or positive) correlation  In real life case, 0.7 and 0.8 could be the highest you will see 13

 Strength and direction are important 14

Four sets of data with the same correlation of

 Linear correlation means that X and Y are in one straight line  Curvlilinear correlation  Age and memory 16

incomeeducationattitudevote How to calculate the correlation coefficient? 1.CORREL() 2.Correlation in data analysis toolset 17

 Correlation matrix IncomeEducationAttitudeVote Income Education Attitude Vote

 Data Analysis tool - correlation 19

 Correlation value:  - finite number ~ + finite number  Correlation coefficient value:  ~ r xy valueInterpretation 0.8 ~ 1.0Very strong relationship (share most of the things in common) 0.6 ~0.8Strong relationship (share many things in common) 0.4 ~ 0.6Moderate relationship (share something in common) 0.2 ~ 0.4Weak relationship (share a little in common) 0.0 ~ 0.2Weak or no relationship (share very little or nothing in common) 20

 Coefficient of determination:  The percentage of variance in one variable that is accounted for by the variance in the other variable.  = square of coefficient 49% of the variance in GPA can be explained by the variance in studying time 21

 The amount of unexplained variance is called the coefficient of undetermination (coefficient of alienation) correlationdeterminationinterpretation

 In a small town in Greece,  The local police found the direct correlation between ice cream and crime 23

 The correlation represents the association between two or more variables  It has nothing to do with causality (there is no cause relation between two correlated variables)  Ices cream and crime are correlated, but  Ices cream does not cause crime 24

Summer Summer is when people get together. More specifically, casual drinkers and drug users are more likely to go to bars or parties on weekends and evenings, as opposed to a Tuesday morning. These people in the social mix, flooding the city’s streets and neighborhood bars, feed the peak times for murder, experts say. 25