Calculating and Interpreting the Correlation Coefficient ~adapted from walch education.

Slides:



Advertisements
Similar presentations
Proving Average Rate of Change
Advertisements

Interpreting Slope and y-intercept ~adapted from walch education.
5-7: Scatter Plots & Lines of Best Fit. What is a scatter plot?  A graph in which two sets of data are plotted as ordered pairs  When looking at the.
10.1 Scatter Plots and Trend Lines
Graphing the Set of All Solutions ~adapted from walch education.
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.
Fitting a Function to Data Adapted from Walch Education.
Aim: How do we calculate and interpret correlation coefficients with SPSS? SPSS Assignment Due Friday 2/12/10.
Correlational Research Strategy. Recall 5 basic Research Strategies Experimental Nonexperimental Quasi-experimental Correlational Descriptive.
Linear Regression Analysis
Correlation vs. Causation What is the difference?.
Scatterplots Grade 8: 4.01 & 4.02 Collect, organize, analyze and display data (including scatter plots) to solve problems. Approximate a line of best fit.
~adapted from Walch Education A scatter plot that can be estimated with a linear function will look approximately like a line. A line through two points.
~adapted from Walch Education Correlation does not imply causation. If a change in one event is responsible for a change in another event, the two events.
Learn to create and interpret scatter plots and find the line of best fit. 5.4 Scatter Plots.
Linear Models and Scatter Plots Digital Lesson. Copyright © by Houghton Mifflin Company, Inc. All rights reserved. 2 x 24 –2–2 – 4 y A scatter plot.
Introduction A correlation between two events simply means that there is a consistent relationship between two events, and that a change in one event implies.
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.
Scatterplots October 14, Warm-Up Given the following domain and range in set notation, write the equivalent domain and range in algebraic notation.
Objective: I can write linear equations that model real world data.
C. A. Warm Up 1/28/15 SoccerBasketballTotal Boys1812 Girls1614 Total Students were asked which sport they would play if they had to choose. 1)Fill in the.
Linear Models and Scatter Plots Objectives Interpret correlation Use a graphing calculator to find linear models and make predictions about data.
1. Graph 4x – 5y = -20 What is the x-intercept? What is the y-intercept? 2. Graph y = -3x Graph x = -4.
Example 1: page 161 #5 Example 2: page 160 #1 Explanatory Variable - Response Variable - independent variable dependent variable.
Introduction When linear functions are used to model real-world relationships, the slope and y-intercept of the linear function can be interpreted in context.
 Graph of a set of data points  Used to evaluate the correlation between two variables.
Correlation Correlation is used to measure strength of the relationship between two variables.
Introduction to Correlation Analysis. Objectives Correlation Types of Correlation Karl Pearson’s coefficient of correlation Correlation in case of bivariate.
Unit 1 – First-Degree Equations and Inequalities Chapter 2 – Linear Relations and Functions 2.5 – Statistics: Using Scatter Plots.
CORRELATIONAL RESEARCH STUDIES
Chapter Bivariate Data (x,y) data pairs Plotted with Scatter plots x = explanatory variable; y = response Bivariate Normal Distribution – for.
Chapter 2 – Linear Equations and Functions
Creating a Residual Plot and Investigating the Correlation Coefficient.
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,
Warm-Up Write the equation of each line. A B (1,2) and (-3, 7)
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.
9.1B – Computing the Correlation Coefficient by Hand
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.
Scatter Diagram of Bivariate Measurement Data. Bivariate Measurement Data Example of Bivariate Measurement:
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.
Correlations AP Psychology. Correlations  Co-relation  It describes the relationship b/w two variables.  Example #1  How is studying related to grades?
Quick Start Expectations 1.Fill in planner and HWRS HW: p. 98, #4-5, Get a signature on HWRS 3.On desk: calculator, journal, HWRS, pencil, pen.
2.5 Using Linear Models P Scatter Plot: graph that relates 2 sets of data by plotting the ordered pairs. Correlation: strength of the relationship.
7.1 Draw Scatter Plots and Best Fitting Lines Pg. 255 Notetaking Guide Pg. 255 Notetaking Guide.
Lesson 4.7 – Interpreting the Correlation Coefficient and Distinguishing between Correlation & Causation EQs: How do you calculate the correlation coefficient?
.  Relationship between two sets of data  The word Correlation is made of Co- (meaning "together"), and Relation  Correlation is Positive when the.
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.
The coefficient of determination, r 2, is The fraction of the variation in the value of y that is explained by the regression line and the explanatory.
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,
MATH 2311 Section 5.2 & 5.3. Correlation Coefficient.
Chapter 15 Association Between Variables Measured at the Interval-Ratio Level.
Correlation & Linear Regression Using a TI-Nspire.
4.3.2: Warm-up, P.107 A new social networking company launched a TV commercial. The company tracked the number of users in thousands who joined the network.
Scatter Plots and Correlation Coefficients
Pearson’s Correlation Coefficient
Lesson 4.8 – Interpreting the Correlation Coefficient and Distinguishing between Correlation & Causation EQ: How do you calculate the correlation coefficient?
Ch. 11: Quantifying and Interpreting Relationships Among Variables
2. Find the equation of line of regression
2.6 Draw Scatter Plots and Best-Fitting Lines
Scatterplots and Correlation
Correlation Coefficient Using Technology
~adapted for Walch Education
Section 1.4 Curve Fitting with Linear Models
Unit 2 Quantitative Interpretation of Correlation
Objectives Vocabulary
7.1 Draw Scatter Plots and Best Fitting Lines
Correlation & Trend Lines
Solution to Problem 2.25 DS-203 Fall 2007.
Presentation transcript:

Calculating and Interpreting the Correlation Coefficient ~adapted from walch education

Important Concepts: A correlation is a relationship between two events, where a change in one event implies a change in another event. Correlation doesn’t mean that a change in the first event caused a change in the other event. The strength of a linear correlation can be measured using a correlation coefficient. Before determining the correlation coefficient, look at the scatter plot of the data and make an initial assessment of the strength of a linear relationship between the two events.

Concepts, continued… A correlation coefficient of –1 indicates a strong negative correlation. A correlation coefficient of 1 indicates a strong positive correlation. A correlation coefficient of 0 indicates a very weak or no linear correlation. The correlation coefficient only assesses the strength of a linear relationship between two variables. The correlation coefficient does not assess causation—that one event causes the other.

Practice Caitlyn thinks that there may be a relationship between class size and student performance on standardized tests. She tracks the average test performance of students from 20 different classes, and notes the number of students in each class in the table on the next slide. Is there a linear relationship between class size and average test score? Use the correlation coefficient, r, to explain your answer.

Average test performance of students

Scatter Plot Average test score Number of students

Describe the relationship between the data As the class size increases, the average test score decreases. It appears that there is a linear relationship with a negative slope between the two variables. The correlation coefficient, r, is approximately –0.84 (calculated using a graphing calculator)

Use the correlation coefficient to describe the strength of the relationship between the data A correlation coefficient of –1 indicates a strong negative correlation, and a correlation of 0 indicates no correlation. A correlation coefficient of –0.84 is close to –1, and indicates that there is a strong negative linear relationship between class size and average test score.

THANKS FOR WATCHING !!! ~Ms. Dambreville