'R2 value' presentation slideshows

608 views • 52 slides

Detecting and reducing multicollinearity

Detecting and reducing multicollinearity. Detecting multicollinearity. Common methods of detection. Realized effects (changes in coefficients, changes in standard errors of coefficients, changes in sequential sums of squares) of multicollinearity.

701 views • 48 slides

599 views • 41 slides

Fertility Islands

Predictive modeling of spatial patterns of soil nutrients associated with fertility islands in the Mojave and Sonoran deserts. . Erika L. Mudrak, Jennifer L. Schafer, Andres Fuentes Ramirez, Claus Holzapfel, and Kirk A. Moloney. Fertility Islands. Shrub canopies provide windbreak

578 views • 35 slides

Multiple, stepwise and non-linear regression models

642 views • 33 slides

Plots, Correlations, and Regression

Plots, Correlations, and Regression. Getting a feel for the data using plots, then analyzing the data with correlations and linear regression. Introduction to Plots.

412 views • 23 slides

Regression Analysis

Regression Analysis. A statistical procedure used to find relations among a set of variables. In regression analysis, there is a dependent variable , which is the one you are trying to explain, and one or more independent variables that are related to it.

332 views • 23 slides

Poverty Estimation, Inequality, Correlation & Regression & Trend Growth Rate: SPSS/STATA

Poverty Estimation, Inequality, Correlation & Regression & Trend Growth Rate: SPSS/STATA. Srinivasulu Rajendran Centre for the Study of Regional Development (CSRD) Jawaharlal Nehru University (JNU) New Delhi India r.srinivasulu@gmail.com. Objective of the session.

333 views • 21 slides

Multiple Linear Regression

Multiple Linear Regression. Relationship between education level, income, and length of time out of school Our new regression equation:. = a + bX 1 + bX 2. Example of Multiple Regression. is the predicted value of the dependent variable (income). X 1.

383 views • 14 slides

STAT 3130 Statistical Methods II

STAT 3130 Statistical Methods II. Session 5 Multiple Regression. Multiple Regression. From last semester, we learned that a simple linear equation of a line takes the general form of y=mx+b, where: Y is the dependent variable m is the slope of the line

239 views • 11 slides

Lab 1: Kinetic Rate Law of CV+OH -

622 views • 5 slides

Assignment for next class

Assignment for next class. Correct data table and graph for your class/hour Trendline , equation, and r 2 value Estimated sucrose concentration of Dr. Wow/apple juice Estimated sucrose concentration of potato cells

175 views • 3 slides