GOAL: I CAN USE TECHNOLOGY TO COMPUTE AND INTERPRET THE CORRELATION COEFFICIENT OF A LINEAR FIT. (S-ID.8) Data Analysis Correlation Coefficient.

Slides:



Advertisements
Similar presentations
Describing Relationships Using Correlation and Regression
Advertisements

Chapter 8 Linear Regression © 2010 Pearson Education 1.
LSRL Least Squares Regression Line
Correlation Relationship between Variables. Statistical Relationships What is the difference between correlation and regression? Correlation: measures.
Correlation: Relationship between Variables
Basic Statistical Concepts Part II Psych 231: Research Methods in Psychology.
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.
Correlation & Regression Math 137 Fresno State Burger.
Chapter 21 Correlation. Correlation A measure of the strength of a linear relationship Although there are at least 6 methods for measuring correlation,
Correlation vs. Causation What is the difference?.
Correlation and Linear Regression Chapter 13 McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Correlation and Regression A BRIEF overview Correlation Coefficients l Continuous IV & DV l or dichotomous variables (code as 0-1) n mean interpreted.
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 1: Correlation Coefficient
Chapter 13 Statistics © 2008 Pearson Addison-Wesley. All rights reserved.
Introduction to Quantitative Data Analysis (continued) Reading on Quantitative Data Analysis: Baxter and Babbie, 2004, Chapter 12.
Copyright © 2011 Pearson Education, Inc. Slide 5-1 Unit 5E Correlation Coefficient.
Correlation.
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 1 Section 13-6 Regression and Correlation.
Run the colour experiment where kids write red, green, yellow …first.
Max temp v min temp. It can be seen from the scatterplot that there is a correlation between max temp and min temp. Generally, as min temp increases,
 Graph of a set of data points  Used to evaluate the correlation between two variables.
Holt Algebra Curve Fitting with Linear Models 2-7 Curve Fitting with Linear Models Holt Algebra 2 Lesson Presentation Lesson Presentation.
7-2 Correlation Coefficient Objectives Determine and interpret the correlation coefficient.
Scatterplots are used to investigate and describe the relationship between two numerical variables When constructing a scatterplot it is conventional to.
Objective: Understanding and using linear regression Answer the following questions: (c) If one house is larger in size than another, do you think it affects.
Relationships If we are doing a study which involves more than one variable, how can we tell if there is a relationship between two (or more) of the.
Describing Relationships Using Correlations. 2 More Statistical Notation Correlational analysis requires scores from two variables. X stands for the scores.
CHAPTER 5 Regression BPS - 5TH ED.CHAPTER 5 1. PREDICTION VIA REGRESSION LINE NUMBER OF NEW BIRDS AND PERCENT RETURNING BPS - 5TH ED.CHAPTER 5 2.
Correlations: Relationship, Strength, & Direction Scatterplots are used to plot correlational data – It displays the extent that two variables are related.
Linear regression 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.
April 1 st, Bellringer-April 1 st, 2015 Video Link Worksheet Link
Creating a Residual Plot and Investigating the Correlation Coefficient.
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 2.6 – Draw Scatter Plots and Best Fitting Lines A scatterplot is a graph of a set of data pairs (x, y). If y tends to increase as x increases,
5.4 Line of Best Fit Given the following scatter plots, draw in your line of best fit and classify the type of relationship: Strong Positive Linear Strong.
Correlation The apparent relation between two variables.
Financial Statistics Unit 2: Modeling a Business Chapter 2.2: Linear Regression.
Chapter 9: Correlation and Regression Analysis. Correlation Correlation is a numerical way to measure the strength and direction of a linear association.
Chapter 3-Examining Relationships Scatterplots and Correlation Least-squares Regression.
We would expect the ENTER score to depend on the average number of hours of study per week. So we take the average hours of study as the independent.
1 Data Analysis Linear Regression Data Analysis Linear Regression Ernesto A. Diaz Department of Mathematics Redwood High School.
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.
.  Relationship between two sets of data  The word Correlation is made of Co- (meaning "together"), and Relation  Correlation is Positive when the.
Chapter 8 Linear Regression. Fat Versus Protein: An Example 30 items on the Burger King menu:
CORRELATION ANALYSIS.
Unit 3 Section : Regression  Regression – statistical method used to describe the nature of the relationship between variables.  Positive.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Linear Regression and Correlation Chapter 13.
Scatter Plots. Standard: 8.SP.1 I can construct and interpret scatterplots.
Correlation & Linear Regression Using a TI-Nspire.
Week 2 Normal Distributions, Scatter Plots, Regression and Random.
Chapter 2 Bivariate Data Scatterplots.   A scatterplot, which gives a visual display of the relationship between two variables.   In analysing the.
Correlation & Regression
Interpret Scatterplots & Use them to Make Predictions
Suppose the maximum number of hours of study among students in your sample is 6. If you used the equation to predict the test score of a student who studied.
Correlation and Simple Linear Regression
2. Find the equation of line of regression
The Weather Turbulence
CORRELATION ANALYSIS.
Correlation and Simple Linear Regression
Correlation.
Simple Linear Regression and Correlation
y = mx + b Linear Regression line of best fit REMEMBER:
Objective: Interpret Scatterplots & Use them to Make Predictions.
Algebra Review The equation of a straight line y = mx + b
Warsaw Summer School 2017, OSU Study Abroad Program
Solution to Problem 2.25 DS-203 Fall 2007.
Correlation and Simple Linear Regression
Correlation and Simple Linear Regression
Presentation transcript:

GOAL: I CAN USE TECHNOLOGY TO COMPUTE AND INTERPRET THE CORRELATION COEFFICIENT OF A LINEAR FIT. (S-ID.8) Data Analysis Correlation Coefficient

Correlation Describes the relationship between two variables in a scatterplot. Data can have a positive correlation, a negative correlation, or no correlation.

Correlation Coefficient Correlation coefficients measure the strength and direction of a relationship between two variables. Generally, the correlation coefficient is denoted by r

Correlation Coefficient How to Interpret a Correlation Coefficient The value of a correlation coefficient ranges between -1 and 1. The strongest linear relationship is indicated by a correlation coefficient of -1 or 1. The weakest linear relationship is indicated by a correlation coefficient equal to 0. A positive correlation means that if one variable gets bigger, the other variable tends to get bigger. (just like a positive slope) A negative correlation means that if one variable gets bigger, the other variable tends to get smaller. (just like a negative slope)

Correlation Coefficient Keep in mind that the Pearson product-moment correlation coefficient only measures linear relationships. Therefore, a correlation of 0 does not mean zero relationship between two variables; rather, it means zero linear relationship.

Scatter plots and Correlation Coefficients Maximum positive correlation (r = 1.0) Strong positive correlation (r = 0.80) Zero correlation (r = 0) Maximum negative correlation (r = -1.0) Moderate negative correlation (r = ) Strong correlation & outlier (r = 0.71)

Example The data below are the gestation periods, in months, of randomly selected animals and their corresponding life spans, in years. 1) Find the equation of the regression line for the given data. 2) What does the rate of change mean in the context of this problem? Gestation, x Life Span, y

Example The data below are the gestation periods, in months, of randomly selected animals and their corresponding life spans, in years. 3) What is the correlation coefficient? 4) What does the correlation coefficient tell you about the model? Gestation, x Life Span, y

Example The data below are the final exam scores of 10 randomly selected statistics students and the number of hours they studied for the exam. 1) Find the equation of the regression line for the given data. 2) What does the rate of change mean in the context of this problem? Hours, x Scores, y

Example The data below are the final exam scores of 10 randomly selected statistics students and the number of hours they studied for the exam. 3) What is the correlation coefficient? 4) What does the correlation coefficient tell you about the model? Hours, x Scores, y

Summary Several points are evident from the scatter plots. When the slope of the line in the plot is negative, the correlation is negative; and vice versa.slope The strongest correlations (r = 1.0 and r = -1.0 ) occur when data points fall exactly on a straight line. The correlation becomes weaker as the data points become more scattered. If the data points fall in a random pattern, the correlation is equal to zero. Correlation is affected by outliers. Compare the first scatter plot with the last scatter plot. The single outlier in the last plot greatly reduces the correlation (from 1.00 to 0.71).outliers