11A Correlation, 11B Measuring Correlation

Slides:



Advertisements
Similar presentations
Bivariate Data – Scatter Plots and Correlation Coefficient…… Section 3.1 and 3.2.
Advertisements

10.1 Scatter Plots and Trend Lines
Describing Relationships: Scatterplots and Correlation
Relationship of two variables
Correlation with a Non - Linear Emphasis Day 2.  Correlation measures the strength of the linear association between 2 quantitative variables.  Before.
Chapter 14 – Correlation and Simple Regression Math 22 Introductory Statistics.
Prior Knowledge Linear and non linear relationships x and y coordinates Linear graphs are straight line graphs Non-linear graphs do not have a straight.
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.
Section 4.1 Scatter Diagrams and Correlation. Definitions The Response Variable is the variable whose value can be explained by the value of the explanatory.
Scatterplots are used to investigate and describe the relationship between two numerical variables When constructing a scatterplot it is conventional to.
STATISTICS 12.0 Correlation and Linear Regression “Correlation and Linear Regression -”Causal Forecasting Method.
1.1 example these are prices for Internet service packages find the mean, median and mode determine what type of data this is create a suitable frequency.
Scatter Diagrams Objective: Draw and interpret scatter diagrams. Distinguish between linear and nonlinear relations. Use a graphing utility to find the.
Describing Relationships: Scatterplots and Correlation.
Relationships Scatterplots and correlation BPS chapter 4 © 2006 W.H. Freeman and Company.
Creating a Residual Plot and Investigating the Correlation Coefficient.
Correlation The apparent relation between two variables.
Chapter 9: Correlation and Regression Analysis. Correlation Correlation is a numerical way to measure the strength and direction of a linear association.
Announcements Turn in homework Papers galore- Exams, homework, project proposal, etc. WILL GET IT ALL WEDNDESDAY. IB Grades New Layered Assessment Posted.
Scatter Diagram of Bivariate Measurement Data. Bivariate Measurement Data Example of Bivariate Measurement:
9.1 - Correlation Correlation = relationship between 2 variables (x,y): x= independent or explanatory variable y= dependent or response variable Types.
Statistics: Analyzing 2 Quantitative Variables MIDDLE SCHOOL LEVEL  Session #2  Presented by: Dr. Del Ferster.
Correlation  We can often see the strength of the relationship between two quantitative variables in a scatterplot, but be careful. The two figures here.
REGRESSION MODELS OF BEST FIT Assess the fit of a function model for bivariate (2 variables) data by plotting and analyzing residuals.
Bivariate Data – Scatter Plots and Correlation Coefficient……
Correlation & Linear Regression Using a TI-Nspire.
Two-Variable Data Analysis
Quantitative Data Essential Statistics.
Scatter Plots and Correlation
Warm Up Scatter Plot Activity.
CHAPTER 3 Describing Relationships
Sections Review.
REGRESSION (R2).
SCATTERPLOTS, ASSOCIATION AND RELATIONSHIPS
Ch. 10 – Scatterplots, Association and Correlation (Day 1)
Correlations and Scatterplots
Objectives Fit scatter plot data using linear models with and without technology. Use linear models to make predictions.
SIMPLE LINEAR REGRESSION MODEL
Scatterplots A way of displaying numeric data
Get a graphing calculator!!!
2-1 INTERPRET SCATTERPLOTS
Section 13.7 Linear Correlation and Regression
CHAPTER 10 Correlation and Regression (Objectives)
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.
Scatter plots & Association
2. Find the equation of line of regression
2-7 Curve Fitting with Linear Models Holt Algebra 2.
2.6 Draw Scatter Plots and Best-Fitting Lines
Regression.
Lecture Notes The Relation between Two Variables Q Q
Correlation and Regression
STEM Fair Graphs.
Residuals and Residual Plots
Review of Chapter 3 Examining Relationships
Section 1.4 Curve Fitting with Linear Models
Regression.
Correlation and Regression
11C Line of Best Fit By Eye, 11D Linear Regression
Unit 2 Quantitative Interpretation of Correlation
Algebra Review The equation of a straight line y = mx + b
Correlation & Trend Lines
Section 11.1 Correlation.
Association between 2 variables
Scatterplots Regression, Residuals.
Statistics 101 CORRELATION Section 3.2.
Draw Scatter Plots and Best-Fitting Lines
Relations P.O.D. #37 March
Chapter 3: Describing Relationships
Review of Chapter 3 Examining Relationships
Presentation transcript:

11A Correlation, 11B Measuring Correlation Unit 3: Statistical Applications 11A, 11B 2/23/2019 9:18 AM

Correlation 11A, 11B 2/23/2019 9:18 AM

Correlation 11A, 11B 2/23/2019 9:18 AM

Two Variable Statistics scatter plots are often an appropriate depiction for two quantitative variables on a scatter plot: independent (explanatory) variable horizontal axis dependent (response) variable vertical axis correlation: relationship or association between two variables Does correlation imply causation? Is the “dependent variable” truly dependent? p. 317 positive, negative, no correlation linear, non-linear strong, moderate, weak outliers Copy Copy 11A, 11B 2/23/2019 9:18 AM

Describing Correlation’s Trend Copy positive correlation as input increases, output tends to increase negative correlation as input increases, output tends to decrease no correlation 11A, 11B 2/23/2019 9:18 AM

Describing Correlation’s Shape linear correlation nonlinear correlation (might be quadratic, cubic, or exponential) 11A, 11B 2/23/2019 9:18 AM

Describing Correlation’s Strength 11A, 11B 2/23/2019 9:18 AM

Outliers isolated points which do not follow the general trend formed by the main body of the data with two variable statistics you may choose to visually identify any outliers and disregard them when finding a regression model or calculating r and r2 11A, 11B 2/23/2019 9:18 AM

“r” and “r2” Copy r Pearson’s Correlation Coefficient negative correlation no correlation positive correlation use p. 321 to interpret strength r2 Coefficient of Determination p. 326: “____% of the variation in [Dependent Variable] can be explained by the variation in [Independent Variable]” 11A, 11B 2/23/2019 9:18 AM

Example A chemical fertilizer company wishes to determine the extent of correlation between the quantity of a compound used and lawn growth per day. Find Pearson’s correlation coefficient between the two variables. Start by finding: Lawn Quantity (g) Growth (mm) A 1 3 B 2 C 4 6 D 5 8 Copy 11A, 11B 2/23/2019 9:18 AM

Example 11A, 11B 2/23/2019 9:18 AM

Example Copy very strong positive linear correlation 93.9% of the variation in growth can be explained by the variation in fertilizer quantity Quantity (g) x Growth (mm) y xy 1 3 2 6 4 24 5 8 40 12 20 73 Quantity (g) x Growth (mm) y 1 3 2 4 6 5 8 12 20 Quantity (g) x Growth (mm) y xy x2 1 3 2 6 4 24 16 5 8 40 25 12 20 73 46 Quantity (g) x Growth (mm) y xy x2 y2 1 3 9 2 6 4 24 16 36 5 8 40 25 64 12 20 73 46 118 11A, 11B 2/23/2019 9:18 AM

Cool-Down On a sheet of graph paper, construct a scatter plot for the data set below. Don’t make it too small. Describe the correlation. Using technology, calculate the correlation coefficient and coefficient of determination. Interpret the results. Find the mean of each variable. Using the two values, plot an ordered pair and label it M. It’s called the “mean point”. Draw a line through the mean point that “best fits” the original data set. Determine its equation. 11C, 11D 2/23/2019 9:18 AM

Practice p. 319: 1,2,4,5 (put scatter plots on graph paper) p. 322: 1,2 p. 324: 6 (find r using technology) p.325: 1(c), 2(b) (calculate r by hand) Read and follow all instructions. List the page and problem numbers alongside your work and answers in your notes. Use the back of the book to check your answers. Copy 11A, 11B 2/23/2019 9:18 AM