Unit 3 Section 10-3. 10-3: Correlation  Correlation – statistical method used to determine whether a relationship between variables exists.  The correlation.

Slides:



Advertisements
Similar presentations
SCATTERPLOT AND PERSONS PRODUCT- MOMENT CORRELATION COEFFICIENT. EXERCISE 2E AND 2F.
Advertisements

Correlation & Regression Chapter 10. Outline Section 10-1Introduction Section 10-2Scatter Plots Section 10-3Correlation Section 10-4Regression Section.
Bivariate Data – Scatter Plots and Correlation Coefficient…… Section 3.1 and 3.2.
Correlation and Regression
© The McGraw-Hill Companies, Inc., 2000 CorrelationandRegression Further Mathematics - CORE.
Elementary Statistics Larson Farber 9 Correlation and Regression.
Correlation and Regression
Correlation and Regression Analysis
BIVARIATE DATA: CORRELATION AND REGRESSION Two variables of interest: X, Y. GOAL: Quantify association between X and Y: correlation. Predict value of Y.
Correlation and Regression. Correlation What type of relationship exists between the two variables and is the correlation significant? x y Cigarettes.
Lecture 17: Correlations – Describing Relationships Between Two Variables 2011, 11, 22.
Farrokh Alemi, Ph.D. Kashif Haqqi M.D.
Chapter 10r Linear Regression Revisited. Correlation A numerical measure of the direction and strength of a linear association. –Like standard deviation.
Correlation & Regression Math 137 Fresno State Burger.
STATISTICS ELEMENTARY C.M. Pascual
Correlation By Dr.Muthupandi,. Correlation Correlation is a statistical technique which can show whether and how strongly pairs of variables are related.
Correlation and Regression
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.
Correlation Indicates the relationship between two dependent variables (x and y) Symbol: r (Pearson correlation coefficient) -1< r < 1.
© The McGraw-Hill Companies, Inc., 2000 Business and Finance College Principles of Statistics Lecture 10 aaed EL Rabai week
Section 12.1 Scatter Plots and Correlation HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems,
1. Graph 4x – 5y = -20 What is the x-intercept? What is the y-intercept? 2. Graph y = -3x Graph x = -4.
© The McGraw-Hill Companies, Inc., Chapter 11 Correlation and Regression.
Hypothesis of Association: Correlation
2 Variable Stats Does the amount of time spent on homework improve your grade? If you eat more junk food will you gain weight? Does the amount of rainfall.
Correlation and Regression
Example 1: page 161 #5 Example 2: page 160 #1 Explanatory Variable - Response Variable - independent variable dependent variable.
 Graph of a set of data points  Used to evaluate the correlation between two variables.
Elementary Statistics Correlation and Regression.
Unit 10 Correlation and Regression McGraw-Hill, Bluman, 7th ed., Chapter 10 1.
1 Chapter 10 Correlation. Positive and Negative Correlation 2.
Chapter Bivariate Data (x,y) data pairs Plotted with Scatter plots x = explanatory variable; y = response Bivariate Normal Distribution – for.
Correlation and Regression. fourth lecture We will learn in this lecture: Correlation and Regression 1- Linear Correlation Coefficient of Pearson 2- Simple.
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,
Chapter 9: Correlation and Regression Analysis. Correlation Correlation is a numerical way to measure the strength and direction of a linear association.
WARM – UP #5 1. Graph 4x – 5y = -20 What is the x-intercept? What is the y-intercept? 2. Graph y = -3x Graph x = -4.
2.5 Using Linear Models A scatter plot is a graph that relates two sets of data by plotting the data as ordered pairs. You can use a scatter plot to determine.
Unit 3 Sections 9.2 – Day 1.  After we determine that a relationship between two variables exists (correlation), the next step is determine the line.
Unit 3 Sections 9.1. What we will be able to do throughout this chapter…  Determine relationships between two or more variables  Determine strengths.
Chapter 7 Calculation of Pearson Coefficient of Correlation, r and testing its significance.
.  Relationship between two sets of data  The word Correlation is made of Co- (meaning "together"), and Relation  Correlation is Positive when the.
Free Powerpoint Templates ROHANA BINTI ABDUL HAMID INSTITUT E FOR ENGINEERING MATHEMATICS (IMK) UNIVERSITI MALAYSIA PERLIS.
Unit 3 Section : Regression  Regression – statistical method used to describe the nature of the relationship between variables.  Positive.
Correlation: How Strong Is the Linear Relationship? Lecture 50 Sec Fri, Dec 9, 2005.
Go to Table of Content Correlation Go to Table of Content Mr.V.K Malhotra, the marketing manager of SP pickles pvt ltd was wondering about the reasons.
© The McGraw-Hill Companies, Inc., Chapter 10 Correlation and Regression.
Bivariate Data – Scatter Plots and Correlation Coefficient……
Unit 3 Sections 10-1 & What we will be able to do throughout this chapter…  Determine relationships between two or more variables  Determine strengths.
CHAPTER 10 & 13 Correlation and Regression Instructor: Alaa saud Note: This PowerPoint is only a summary and your main source should be the book.
GOAL: I CAN USE TECHNOLOGY TO COMPUTE AND INTERPRET THE CORRELATION COEFFICIENT OF A LINEAR FIT. (S-ID.8) Data Analysis Correlation Coefficient.
Correlation and Regression. O UTLINE Introduction  10-1 Scatter plots.  10-2 Correlation.  10-3 Correlation Coefficient.  10-4 Regression.
Irwin/McGraw-Hill © Andrew F. Siegel, 1997 and l Chapter 9 l Simple Linear Regression 9.1 Simple Linear Regression 9.2 Scatter Diagram 9.3 Graphical.
Correlation and Regression Note: This PowerPoint is only a summary and your main source should be the book.
Correlation and Regression Lecturer : FATEN AL-HUSSAIN Note: This PowerPoint is only a summary and your main source should be the book.
Scatter Plots and Correlation
Pearson’s Correlation Coefficient
CHAPTER 10 & 13 Correlation and Regression
Warm Up Scatter Plot Activity.
Correlation & Regression
Aim: How do we fit a regression line on a scatter plot?
SIMPLE LINEAR REGRESSION MODEL
Correlation and Regression
CHAPTER 10 Correlation and Regression (Objectives)
2. Find the equation of line of regression
Statistical Inference for Managers
Section 1.4 Curve Fitting with Linear Models
بسم الله الرحمن الرحيم. Correlation & Regression Dr. Moataza Mahmoud Abdel Wahab Lecturer of Biostatistics High Institute of Public Health University.
Correlation & Trend Lines
Correlation & Regression
Presentation transcript:

Unit 3 Section 10-3

10-3: Correlation  Correlation – statistical method used to determine whether a relationship between variables exists.  The correlation coefficient is used to determine the strength of the relationship between two variables.  The method we will be using for finding this value is the Pearson product moment correlation coefficient (PPMC).

 Correlation coefficient –measures the strength and direction of a linear relationship between two variables.  Symbol for sample correlation coefficient: r  Symbol for population correlation coefficient: ρ  The values of the correlation coefficient range from -1 to +1.  If the value is close to +1 the variables have a strong positive relationship.  If the value is close to -1 the variables have a strong negative relationship.  If the value is close to 0, the variables have no relationship or a weak relationship. Section 10-3

Formula for the Correlation Coefficient (r) n is the number of data pairs Section 10-3

Constructing a Scatter Plot  Compute the value of the correlation coefficient for the data obtained in the study of age and blood pressure given below: SubjectAge (x)Pressure (y) A43128 B48120 C56135 D61143 E67141 F70152 Section 10-3

Table Set Up: Section 10-3 Subjectxyxyx2x2 y2y2

The correlation coefficient suggested a strong positive relationship between age and blood pressure Section 10-3

Constructing a Scatter Plot  Construct a scatter plot for the data obtained in a study of the number of absences and the final grades of seven randomly selected students from a statistics class. Subject# of Absences (x)Final Grade (y) A682 B286 C1543 D974 E1258 F590 G878 Section 10-3

The correlation coefficient suggested a strong negative relationship between the student’s final grade and the number of absences. i.e. the larger the number of absences, the lower the grade Section 10-3

Constructing a Scatter Plot  Construct a scatter plot for the data obtained in a study on the number of hours that nine people exercise each week and the amount of milk (in ounces) each person consumes per week. SubjectHours (x)Amount (y) A348 B08 C232 D564 E810 F532 G1056 H272 I148 Section 10-3

The value of r indicated a very weak positive relationship between the variables. Section 10-3

Homework:  Read and take notes on Section 10.4 (pg 544 – 554)