Performing a regression analysis

Slides:



Advertisements
Similar presentations
Statistics 350 Lecture 21. Today Last Day: Tests and partial R 2 Today: Multicollinearity.
Advertisements

AP Statistics Section 3.2 A Regression Lines. Linear relationships between two quantitative variables are quite common. Just as we drew a density curve.
(a) (b) (c) (d). What is (1,2,3)  (3,4,2)? (a) (1, 2, 3, 4) (b) (1,2)  (3,4) (c) (1,3,4,2) (d) (3,1)  (4,2)
Correlation & Regression
Describing Bivariate Relationships Chapter 3 Summary YMS3e AP Stats at LSHS Mr. Molesky Chapter 3 Summary YMS3e AP Stats at LSHS Mr. Molesky.
Scatterplots October 14, Warm-Up Given the following domain and range in set notation, write the equivalent domain and range in algebraic notation.
AP STATISTICS LESSON 3 – 3 LEAST – SQUARES REGRESSION.
Example 1: page 161 #5 Example 2: page 160 #1 Explanatory Variable - Response Variable - independent variable dependent variable.
STATISTICS 12.0 Correlation and Linear Regression “Correlation and Linear Regression -”Causal Forecasting Method.
Aim: Review for Exam Tomorrow. Independent VS. Dependent Variable Response Variables (DV) measures an outcome of a study Explanatory Variables (IV) explains.
A medical researcher wishes to determine how the dosage (in mg) of a drug affects the heart rate of the patient. DosageHeart rate
Chapter 6 Simple Regression Introduction Fundamental questions – Is there a relationship between two random variables and how strong is it? – Can.
Correlations: Relationship, Strength, & Direction Scatterplots are used to plot correlational data – It displays the extent that two variables are related.
Chapter 9 Correlational Research Designs. Correlation Acceptable terminology for the pattern of data in a correlation: *Correlation between variables.
Regression and Least Squares The need for a mathematical construct… Insert fig 3.8.
Chapter 4: Correlation and Regression 4.1 – Scatter Diagrams and Linear Correlation 4.2 – Linear Regression and the Coefficient of Determinant.
4.2 Correlation The Correlation Coefficient r Properties of r 1.
SWBAT: Measure and interpret the linear association between two variables using correlation. Do Now: You have data for many years on the average price.
LEAST-SQUARES REGRESSION 3.2 Role of s and r 2 in Regression.
3.2 Correlation. Correlation Measures direction and strength of the linear relationship in the scatterplot. Measures direction and strength of the linear.
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.
Unit 3 Section : Regression  Regression – statistical method used to describe the nature of the relationship between variables.  Positive.
P REVIEW TO 6.7: G RAPHS OF P OLYNOMIAL. Identify the leading coefficient, degree, and end behavior. Example 1: Determining End Behavior of Polynomial.
Statistics 3502/6304 Prof. Eric A. Suess Chapter 3.
Introduction to regression 3C. Least-squares regression.
4.2 – Linear Regression and the Coefficient of Determination Sometimes we will need an exact equation for the line of best fit. Vocabulary Least-Squares.
Exploring Relationships Between Numerical Variables Correlation.
Linear Models and Correlation  Linear Function- A set of ordered pairs (x,y) which can be described by an equation of the form y=mx+b, where m and b.
Sections 3.3 & 3.4 Quiz tomorrow.
Covariance/ Correlation
Calculating the correlation coefficient
LSRL.
Least Squares Regression Line.
LEAST – SQUARES REGRESSION
Linear Regression Special Topics.
Two Quantitative Variables
DISCUSS regression and correlation
CHS 221 Biostatistics Dr. wajed Hatamleh
Chapter 3.2 LSRL.
Covariance/ Correlation
2. Find the equation of line of regression
Coefficient of Determination
Describing Bivariate Relationships
Prof. Eric A. Suess Chapter 3
No notecard for this quiz!!
Least Squares Regression Line LSRL Chapter 7-continued
Investigating associations between two numerical variables
Investigating associations between categorical variables
Simple Linear Regression
Chapter 5 LSRL.
Chapter 5 LSRL.
Least-Squares Regression
Regression making predictions
HW# : Complete the last slide
THE NORMAL DISTRIBUTION AND THE 68–95–99.7% RULE
Scatter Plots and Least-Squares Lines
7.1 Draw Scatter Plots & Best-Fitting Lines
Correlation and Regression
CALCULATING EQUATION OF LEAST SQUARES REGRESSION LINE
Investigating associations between two variables
Covariance/ Correlation
Correlation and causality
Section 3.2: Least Squares Regressions
Correlation & Trend Lines
Scatterplots Regression, Residuals.
Statistics 101 CORRELATION Section 3.2.
Precedence tables and activity networks
Plan for Today: Chapter 14: Describing Relationships: Scatterplots and Correlation.
Chapter 3: Describing Relationships
3.2 Correlation Pg
Presentation transcript:

Performing a regression analysis 12 Further mathematics Performing a regression analysis

Performing a regression analysis

Performing a regression analysis The scatterplot and correlation coefficient We start our investigation of the association between price and age by constructing a scatterplot and using it to describe the association in terms of strength, direction and form. In this analysis, age is the explanatory variable.

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Performing a regression analysis

Exercise 4C Odd Numbered Questions WORK TO BE COMPLETED Exercise 4C Odd Numbered Questions