4.1 Correlation Coefficient.notebook. November 14, 2016

Similar documents
Relationships Between Two Variables: Scatterplots and Correlation

Lecture 11: Chapter 5, Section 3 Relationships between Two Quantitative Variables; Correlation

You buy a TV for $1000 and pay it off with $100 every week. The table below shows the amount of money you sll owe every week. Week

Chapter 10. Key Ideas Correlation, Correlation Coefficient (r),

Describing Relationships between Two Variables

Section 3 Part 1. Relationships between two numerical variables

Unit 9 Describing Relationships in Scatter Plots and Line Graphs

Homework 11. Part 1. Name: Score: / null

2. Here is a small part of a data set that describes the fuel economy (in miles per gallon) of 2006 model motor vehicles.

Homework 8 Solutions

Correlation Coefficient The correlation coefficient is a summary statistic that describes the linear relationship between two numerical variables 2

Pearson s Correlation Coefficient

Correlation key concepts:

Section 14 Simple Linear Regression: Introduction to Least Squares Regression

Exercise 1.12 (Pg )

Scatter Plot, Correlation, and Regression on the TI-83/84

Chapter 7: Simple linear regression Learning Objectives

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

Chapter 9 Descriptive Statistics for Bivariate Data

COMP6053 lecture: Relationship between two variables: correlation, covariance and r-squared.

FREE FALL. Introduction. Reference Young and Freedman, University Physics, 12 th Edition: Chapter 2, section 2.5

CALCULATIONS & STATISTICS

Lecture 13/Chapter 10 Relationships between Measurement (Quantitative) Variables

Statistics 2014 Scoring Guidelines

Transforming Bivariate Data

MULTIPLE REGRESSION EXAMPLE

AP STATISTICS REVIEW (YMS Chapters 1-8)

2. Simple Linear Regression

Linear Regression. use waist

AP * Statistics Review. Descriptive Statistics

Father s height (inches)

We are often interested in the relationship between two variables. Do people with more years of full-time education earn higher salaries?

The Dummy s Guide to Data Analysis Using SPSS

The data set we have taken is about calculating body fat percentage for an individual.

CORRELATION ANALYSIS

Chapter 7 Scatterplots, Association, and Correlation

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

Simple linear regression

Correlation. What Is Correlation? Perfect Correlation. Perfect Correlation. Greg C Elvers

Diagrams and Graphs of Statistical Data

c. Construct a boxplot for the data. Write a one sentence interpretation of your graph.

Descriptive statistics; Correlation and regression

Pennsylvania System of School Assessment

Session 7 Bivariate Data and Analysis

STAT 350 Practice Final Exam Solution (Spring 2015)

Lab 1: The metric system measurement of length and weight

DesCartes (Combined) Subject: Mathematics Goal: Statistics and Probability

Simple Regression Theory II 2010 Samuel L. Baker

Lesson 1: Positive and Negative Numbers on the Number Line Opposite Direction and Value

Introduction to Quantitative Methods

Name Partners Date. Energy Diagrams I

The Correlation Coefficient

Statistics E100 Fall 2013 Practice Midterm I - A Solutions

Scatter Plots with Error Bars

Graphing Calculator Workshops

A full analysis example Multiple correlations Partial correlations

Linear Models in STATA and ANOVA

Univariate Regression

Academic Support Center. Using the TI-83/84+ Graphing Calculator PART II

Linear Regression. Chapter 5. Prediction via Regression Line Number of new birds and Percent returning. Least Squares

The Effect of Dropping a Ball from Different Heights on the Number of Times the Ball Bounces

Physics Labs with Computers, Vol. 2 P38: Conservation of Linear Momentum A

PLOTTING DATA AND INTERPRETING GRAPHS

Correlation and Regression

Copyright 2013 by Laura Schultz. All rights reserved. Page 1 of 7

Course Objective This course is designed to give you a basic understanding of how to run regressions in SPSS.

Chapter 1 Introduction to Correlation

Linear Programming. Solving LP Models Using MS Excel, 18

Answer: C. The strength of a correlation does not change if units change by a linear transformation such as: Fahrenheit = 32 + (5/9) * Centigrade

The importance of graphing the data: Anscombe s regression examples

hp calculators HP 17bII+ Net Present Value and Internal Rate of Return Cash Flow Zero A Series of Cash Flows What Net Present Value Is

Statistics for Sports Medicine

Grade. 8 th Grade SM C Curriculum

Calculator Notes for the TI-Nspire and TI-Nspire CAS

Determine If An Equation Represents a Function

HYPOTHESIS TESTING WITH SPSS:

FRICTION, WORK, AND THE INCLINED PLANE

6.4 Normal Distribution

Module 3: Correlation and Covariance

AP Statistics Solutions to Packet 2

Module 5: Multiple Regression Analysis

Z - Scores. Why is this Important?

Tutorial for the TI-89 Titanium Calculator

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

AP Statistics Ch 3 Aim 1: Scatter Diagrams

ENERGYand WORK (PART I and II) 9-MAC

Elasticity. I. What is Elasticity?

X X X a) perfect linear correlation b) no correlation c) positive correlation (r = 1) (r = 0) (0 < r < 1)

Statistics. Measurement. Scales of Measurement 7/18/2012

1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96

1 of 7 9/5/2009 6:12 PM

LESSON TITLE: Math in Restaurants (by Deborah L. Ives, Ed.D)

Midterm Review Problems

Descriptive Statistics

This unit will lay the groundwork for later units where the students will extend this knowledge to quadratic and exponential functions.

How Does My TI-84 Do That

What does the number m in y = mx + b measure? To find out, suppose (x 1, y 1 ) and (x 2, y 2 ) are two points on the graph of y = mx + b.

MTH 140 Statistics Videos

Independent samples t-test. Dr. Tom Pierce Radford University

Transcription:

Correlation Coefficient A scatter plot displays the direction, form and strength of the relationship between two variables. However we do not know how strong or weak this relationship is. It s difficult for us to tell without a scale of what is considered strong and weak. The two images below are the same scatterplot, just a different scale 1

How to we compare two scatter plots? Correlation Coefficient: A numerical value (between +1 and 1) that identifies the strength of the linear relationship between variables. Some important facts about correlation coefficient: 1) We use the variable r to symbolize correlation coefficient. Enter data in (Stat edit) LI and L2 Stat Calc LinReg (Choice #4) 2

2) The correlation always falls in between 1 and 1 0 r <.5 weak Same scale for negatives.5 r <.8 moderate.8 r < 1 strong r = 1 perfect positive r = 1 perfect negative 3

http://www.rossmanchance.com/applets/guesscorrelation.html 4

Some more things to consider: 1) Changing units of measurements does not change the correlation coefficient. Example: changing kilograms to lbs 2) Correlation coefficient has NO UNIT OF MEASUREMENT. It s just r = 3) Correlation ignores the distinction between explanatory and response variables. Example: If we reversed the axis, it would still be the same r value 4) Correlation only measures the strength of LINEAR relationships only. Example: curved lines wouldn t have an r value 5

5) The correlation coefficient IS AFFECTED by outliers. The farther your point is away from the rest, The more it affects your correlation coefficient. When you see an outlier, it s important to calculate the r value with and WITHOUT the outlier (to see how it changes) 6

Match each graph with its corresponding correlation coefficient below:.85.40 0.50.90.99 7

4.1A Name: The 2008 EPA fuel economy ratings for both highway and city driving are given for 25 randomly selected standard pickup trucks with 4 wheel drive. A scatterplot is shown below. 1. Describe what you see in the scatterplot. 2. Is one of the points on the scatterplot unusual to you in comparison to the other points? Explain why you think this point is unusual. 3. In this situation, is it more reasonable to simply explore the relationship between the two variables or to view one of the variables as an explanatory variable and the other as a response variable? In the latter case, identify which is the explanatory and which is the response variable. 4. Based on this scatterplot, what does this tell you about the relationship between highway mpg and city mpg for trucks in this category? 8

Graded Assignment 4.1D Name: 1. State Park rangers are interested in estimating the weight of the bears that inhabit their park. One way to estimate the weight of a bear is by measuring its neck size (distance around the neck). One method used to accomplish this is to measure the bear s neck while it is hibernating, which is how some college students in Maine who were studying to be rangers and conservation officers got their data. Neck Size (inches) Weight (pounds) 15 65 20.5 142 16 80 28 344 32 432 31 416 26.5 262 20 204 18 144 24 207 2. Describe what the scatterplot tells you about the direction and form of the relationship. 3. Using your calculator, find the value of the correlation. 4. Explain in words what this r says. 5. Use the scatterplot to predict the approximate weight of a bear with a neck size of 22 inches. 6. Add a point to the scatterplot that would reduce the correlation between these variables. Explain why the point you added would have this effect. 9

10