What should we do when variables are continuous? Drinking and fighting; social support and depression; IQ at age 5 and 25 What are our options? ANOVAs.

Slides:



Advertisements
Similar presentations
Correlation Chapter 9.
Advertisements

C82MCP Diploma Statistics School of Psychology University of Nottingham 1 Designing Experiments In designing experiments we: Manipulate the independent.
Looking at data: relationships - Correlation IPS chapter 2.2 Copyright Brigitte Baldi 2005 ©
Lecture 4: Correlation and Regression Laura McAvinue School of Psychology Trinity College Dublin.
Statistics for the Social Sciences Psychology 340 Fall 2006 Relationships between variables.
Linear Regression and Correlation Analysis
PSY 307 – Statistics for the Behavioral Sciences
Correlation Relationship between Variables. Statistical Relationships What is the difference between correlation and regression? Correlation: measures.
Correlation: Relationship between Variables
REGRESSION AND CORRELATION
Scatterplots By Wendy Knight. Review of Scatterplots  Scatterplots – Show the relationship between 2 quantitative variables measured on the same individual.
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Describing the Relation between Two Variables 4.
Correlation 1. Correlation - degree to which variables are associated or covary. (Changes in the value of one tends to be associated with changes in the.
EXAMPLE 1 Describe the correlation of data Describe the correlation of the data graphed in the scatter plot. a. The scatter plot shows a positive correlation.
Topics: Correlation The road map
Calculating and Interpreting the Correlation Coefficient ~adapted from walch education.
Chapter 5 Regression. Chapter 51 u Objective: To quantify the linear relationship between an explanatory variable (x) and response variable (y). u We.
February  Study & Abstract StudyAbstract  Graphic presentation of data. Graphic presentation of data.  Statistical Analyses Statistical Analyses.
Graph the linear function What is the domain and the range of f?
SHOWTIME! STATISTICAL TOOLS IN EVALUATION CORRELATION TECHNIQUE SIMPLE PREDICTION TESTS OF DIFFERENCE.
Correlation By Dr.Muthupandi,. Correlation Correlation is a statistical technique which can show whether and how strongly pairs of variables are related.
N318b Winter 2002 Nursing Statistics Specific statistical tests: Correlation Lecture 10.
Scatter Plots and Linear Correlation. How do you determine if something causes something else to happen? We want to see if the dependent variable (response.
Introduction to Quantitative Data Analysis (continued) Reading on Quantitative Data Analysis: Baxter and Babbie, 2004, Chapter 12.
Quantitative assessment of the strength of the relationship between x & y. It is the measure of the extent to which x & y are linearly related. *It is.
Math 15 Introduction to Scientific Data Analysis Lecture 5 Association Statistics & Regression Analysis University of California, Merced.
RESEARCH METHODS.
BPS - 3rd Ed. Chapter 41 Scatterplots and Correlation.
MEASURES OF CENTRAL TENDENCY TENDENCY 1. Mean 1. Mean 2. Median 2. Median 3. Mode 3. Mode.
Run the colour experiment where kids write red, green, yellow …first.
Research & Statistics Looking for Conclusions. Statistics Mathematics is used to organize, summarize, and interpret mathematical data 2 types of statistics.
WHS AP Psychology Research Methods: Correlation. I CAN ANSWER How do psychologists use the scientific method to study behavior and mental processes? What.
Scatter Diagrams. Scatter Diagram Page 195 Tool Book WHAT is a scatter diagram? –A picture of the correlation between two factors over time. –The more.
Investigating the Relationship between Scores
Topic 10 - Linear Regression Least squares principle - pages 301 – – 309 Hypothesis tests/confidence intervals/prediction intervals for regression.
Chapter 4 Describing the Relation Between Two Variables 4.1 Scatter Diagrams; Correlation.
Scatterplots are used to investigate and describe the relationship between two numerical variables When constructing a scatterplot it is conventional to.
Psych 230 Psychological Measurement and Statistics Pedro Wolf September 23, 2009.
“Life is a series of samples. You can infer the truth from the samples, but you never see the truth.” --Kenji, 2010 Educ 200C Friday, October 5, 2012.
AP Psychology Chapter 1: Science of Psychology Objective :Describe a correlational research study taking into account operational definitions, random sampling,
Regression MBA/510 Week 5. Objectives Describe the use of correlation in making business decisions Apply linear regression and correlation analysis. Interpret.
More about Correlation
Chapter 4: Describing the relation between two variables Univariate data: Only one variable is measured per a subject. Example: height. Bivariate data:
Describing Relationships Using Correlations. 2 More Statistical Notation Correlational analysis requires scores from two variables. X stands for the scores.
Correlations MODULE 6. Correlational Study  Collects a set of facts organized into two or more categories  measure parents’ disciplinary style  measure.
Yesterday Correlation Regression -Definition
Multiple Correlation and Regression
Relationships Scatterplots and correlation BPS chapter 4 © 2006 W.H. Freeman and Company.
3.3 Correlation: The Strength of a Linear Trend Estimating the Correlation Measure strength of a linear trend using: r (between -1 to 1) Positive, Negative.
Chapter 4 Summary Scatter diagrams of data pairs (x, y) are useful in helping us determine visually if there is any relation between x and y values and,
Section 4.2 Building Linear Models from Data. OBJECTIVE 1.
2.6 Scatter Diagrams. Scatter Diagrams A relation is a correspondence between two sets of data X is the independent variable Y is the dependent variable.
Correlation. Correlation is a measure of the strength of the relation between two or more variables. Any correlation coefficient has two parts – Valence:
Scatter Diagrams scatter plot scatter diagram A scatter plot is a graph that may be used to represent the relationship between two variables. Also referred.
CHS AP Psychology Unit 1: Science of Psychology Essential Task 1-6:Describe a correlational research study taking into account correlational coefficient,
What Do You See?. A scatterplot is a graphic tool used to display the relationship between two quantitative variables. How to Read a Scatterplot A scatterplot.
Mathematical Studies for the IB Diploma © Hodder Education Pearson’s product–moment correlation coefficient.
Chapter 14 STA 200 Summer I Scatter Plots A scatter plot is a graph that shows the relationship between two quantitative variables measured on the.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Describing the Relation between Two Variables 4.
ContentDetail  Two variable statistics involves discovering if two variables are related or linked to each other in some way. e.g. - Does IQ determine.
Scatter Plots. Scatter plots are used when data from an experiment or test have a wide range of values. You do not connect the points in a scatter plot,
CORRELATIONAL RESEARCH MARLINA BT ZUBAIRI NORLIN BT ABD GHAFAR FARADILLAH BT MD RAMLI ZURIANA BT SAARI EDU 702 RESEARCH METHODOLOGY.
Correlation  We can often see the strength of the relationship between two quantitative variables in a scatterplot, but be careful. The two figures here.
GOAL: I CAN USE TECHNOLOGY TO COMPUTE AND INTERPRET THE CORRELATION COEFFICIENT OF A LINEAR FIT. (S-ID.8) Data Analysis Correlation Coefficient.
©2013, The McGraw-Hill Companies, Inc. All Rights Reserved Chapter 3 Investigating the Relationship of Scores.
Chapter 8 Part I Answers The explanatory variable (x) is initial drop, measured in feet, and the response variable (y) is duration, measured in seconds.
Correlation Measures the relative strength of the linear relationship between two variables Unit-less Ranges between –1 and 1 The closer to –1, the stronger.
Simple Linear Correlation
The Weather Turbulence
Bivariate Data.
Presentation transcript:

What should we do when variables are continuous? Drinking and fighting; social support and depression; IQ at age 5 and 25 What are our options? ANOVAs don’t always work

Misleading Correlations Ice-cream sales in California and drowning deaths What else might be happening here? Are there any other misleading correlations we might find?

Misleading Correlations In investigating the relationship between age and some physical characteristics of women, begin by measuring the angle of the feet in walking. the angle tends to be greater among older women. You might first consider whether this indicates that women grow older because they toe out… NO! So it appears that age increases the angle between the feet, and-most women must come to toe out more as they grow older.

Misleading Correlations Children with longer arms reason better than those with shorter arms Bottled water linked to healthier babies Families that own cappuccino makers are more likely to have healthy babies. Breast fed babies have IQs that are 6 points higher than babies who are not breast fed

Misleading Correlations Discussion. If fat in the diet causes cancer, then the points in the diagram should slope up, other things being equal. So the diagram is some evidence for the theory

X independent variable Y dependent variable S X STANDARD DEVIATION OF X S Y STANDARD DEVIATION OF Y Z X A SUBJECT’S Z-SCORE ON X Z Y A SUBJECT’S Z-SCORE ON Y Describing a relationship between 2 variables

- SO WHAT IS THE LINEAR RELATION BETWEEN X AND Y? DIRECTION DEGREE - ANSWER IS r = Pearson PRODUCT-MOMENT CORRELATION

A PLOT OF SCORES ON X AND Y GIVES THE DIRECTION OF RELATIONSHIP CORRELATIONS ‘R’ RANGE FROM –1 TO +1 r = 0 NO CORRELATION, INDEPENDENT r = + POSITIVE CORRELATION r = - NEGATIVE CORRELATION THE CLOSER r IS TO 1 OR –1, THE STRONGER THE LINEAR RELATIONSHIP BETWEEN TWO VARIABLES THE SCATTER DIAGRAM

R=.08 R 2 =.007

R=.37 R 2 =.137

R=.689 R 2 =.474

R=.943 R 2 =.891

R=-.817, R 2 =.668

R=?

Extreme scores can have huge influence on correlation R=.75 R=.-75

R=-.05 R 2 =.002 Correlation only handles linear relationship Cannot handle more complicated curvilinear relatiomships

R

R R