Download presentation

Presentation is loading. Please wait.

Published byGrace Craig Modified over 3 years ago

1
Chapter 3 Examining Relationships Lindsey Van Cleave AP Statistics September 24, 2006

2
3.1: Scatterplots Scatterplot: shows the relationship between two quantitative variables, and each individual appears as a point in the plot. Explanatory Variable: explains the observed outcome. effect Response Variable: outcome of a study. cause

3
Interpretting Scatterplots There are four things to look for when interpretting a scatter plot: –Direction: positive or negative –Outliers: falls outside the normal pattern –Form: linear, cluster, or gaps –Strength: how well the plot follows clear form Strong, moderately strong, weak, no relationship

4
Examples of Scatterplots

5
3.2 Correlation Correlation: measures the direction and strength of the linear relationship between two quantitative variables written as r. –*Correlation is not a complete description of two-variable data, even when the relationship between the variables is linear.

6
Correlation Formula:

7
Example:

8
3.3: Least-Squares Regression Least-Squares Regression: method for finding a line that summarizes the relationship between two variables, but only in a specific setting.

9
Coefficient of Determination: Coefficient of Determination: fraction of the variation in the values of y that is explained by least-squares regression of y on x.

10
Facts about least-squares regression: 1. The distinction between explanatory and response variables is essential in regression. 2. A change of one standard deviation in x corresponds to a change of r standard deviations in y. 3. The least-squares regression line always passes through the point (x,y) 4. The square of the correlation, r, is the fraction of the variation in the values of y that is explained by the least-squares regression of y on x.

11
Residuals Residuals: plot the error (observed- predicted) of the LSRL. The shape of the plot can give some insight into our data. Four things to look for in residuals: –1. A pattern: especially curves –2. Increasing/Decreasing spread –3. Outliers –4. Extreme individual values of explanatory variable Good Residual Plot: –1. No pattern –2. Roughly equal number above and below 0 –3. constant spread

12
Chapter 3 Dont even worry you can do most of this stuff on the calculator!!! Yay!

Similar presentations

OK

Notes Bivariate Data Chapters 7 - 9. Bivariate Data Explores relationships between two quantitative variables.

Notes Bivariate Data Chapters 7 - 9. Bivariate Data Explores relationships between two quantitative variables.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Ppt on macbeth Ppt on id ego superego iceberg Ppt on abo blood grouping procedure Ppt on traction rolling stock manufacturers Ppt on computer languages 1gl Ppt on architectural heritage of india Ppt on chapter 12 electricity Ppt on earth movements and major landforms in brazil Ppt on council of ministers nepal Hrm ppt on recruitment process