PPT-Predictions 1. Multiple linear regression

Kenneth D Harris April 29 2015 Predictions in neurophysiology Predict neuronal activity from sensory stimulusbehaviour encoding model Predict stimulusbehaviour from neuronal activity decoding model. Jennifer Kensler. Laboratory for Interdisciplinary Statistical Analysis. Collaboration. . From our website request a meeting for personalized statistical advice. Great advice right now:. Meet with LISA . The relation is supposed to be linear. We have a hypothesis about the distribution of errors around the hypothesized regression line. There is a hypothesis about dependent and independent variables. The relation is non-linear. Model . the relationship between two or more explanatory variables and a response variable by fitting a linear equation to observed . data.. Formally, the model for multiple linear regression, given . 1. 2. 3. Outline. Jinmiao. Fu—Introduction and History . Ning. Ma—Establish and Fitting of the model. Ruoyu. Zhou—Multiple Regression Model in Matrix Notation. Dawei. . Xu. and Yuan Shang—Statistical Inference for Multiple Regression. Dummy variables as an independent variable. Dummy variable trap. Importance of the "reference group". Using dummy variables to test for equal means. Dummy variables for . Multiple categories. Ordinal variables. ;. some. do’s . and. . don’ts. Hans Burgerhof. Medical. . S. tatistics. and . Decision. Making. Department. of . Epidemiology. UMCG. . Help! Statistics! Lunchtime Lectures. When?. Where?. What?. 9-. 1. 2. Objectives. Understand the basic types of data. Conduct basic statistical analyses in Excel. Generate descriptive statistics and other analyses using the Analysis . ToolPak. Use regression analysis to predict future values. Al M Best, PhD. Virginia Commonwealth University. Task Force on Design and Analysis . in Oral Health Research. Satellite Symposium, AADR. Boston, MA: March 10, 2015. Multivariable statistical modeling from 10,000 feet. Scatter Plot Review. Using the Regression Line Model to Make Predictions. It’s the responsibility of the news medium to report on important decisions made by newsmakers. Examples include new traffic laws based on the number of accidents, immigration reform based on the number of people emigrating to the U.S., and gas prices based on the supply and demand of oil. These decisions make headlines because of the impact they have on our lives. 1. Correlation indicates the magnitude and direction of the linear relationship between two variables. . Linear Regression: variable Y . (criterion) . is predicted by variable X . (predictor) . using a linear equation.. What. is . what. ? . Regression: One variable is considered dependent on the other(s). Correlation: No variables are considered dependent on the other(s). Multiple regression: More than one independent variable. Nisheeth. Linear regression is like fitting a line or (hyper)plane to a set of points. The line/plane must also predict outputs the unseen (test) inputs well. . Linear Regression: Pictorially. 2. (Feature 1). 1. 2. Office Hours. :. More office hours, schedule will be posted soon.. . On-line office hours are for everyone, please take advantage of them.. . Projects:. Project guidelines and project descriptions will be posted Thursday 9/25.. Regression Trees. Characteristics of classification models. model. linear. parametric. global. stable. decision tree. no. no. no. no. logistic regression. yes. yes. yes. yes. discriminant. analysis.