'Error t' presentation slideshows

Weighting

804 views • 55 slides

Lecture 22 Adjunct Methods

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Regression in R

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RISK MANAGEMENT

RISK MANAGEMENT . GOALS AND TOOLS. ROLE OF RISK MANAGER. MONITOR RISK OF A FIRM, OR OTHER ENTITY IDENTIFY RISKS MEASURE RISKS REPORT RISKS MANAGE -or CONTROL RISKS. COMMON TYPES OF RISK. MARKET RISK CREDIT RISK LIQUIDITY RISK OPERATIONAL RISK SYSTEMIC RISK. COMMON TOOLS.

627 views • 42 slides

5. Statistical Inference: Estimation

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Lecture 13 Diagnostics in MLR Added variable plots Identifying outliers Variance Inflation Factor

435 views • 32 slides

Factor Models

Factor Models. Riccardo Colacito. Diversification and Portfolio Risk. Market risk Systematic or Nondiversifiable Firm-specific risk Diversifiable or nonsystematic. Portfolio Risk as a Function of the Number of Stocks. Portfolio Risk as a Function of Number of Securities.

411 views • 30 slides

Lecture 6: Multiple Linear Regression Adjusted Variable Plots

374 views • 28 slides

Multilevel modeling in R

Multilevel modeling in R. Tom Dunn and Thom Baguley, Psychology, Nottingham Trent University Thomas.Baguley@ntu.ac.uk. 1. Models for repeated measures or clustered data. Repeated measures ANOVA. Usual practice is psychology is to analyze repeated measures data using ANOVA:

596 views • 28 slides

Multiple Regression Analysis

Multiple Regression Analysis. General Linear Models. This framework includes: Linear Regression Analysis of Variance (ANOVA) Analysis of Covariance (ANCOVA ) These models can all be analyzed with the function lm()

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Why and how people use R

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ALR 8.3 & 9.7

ALR 8.3 & 9.7 . Alicia Hymel. Problem 8.3

449 views • 22 slides

Regression II Model Selection

Regression II Model Selection. Model selection based on t-distribution Information criteria Cross-validation. Introduction.

231 views • 21 slides

Full example

Full example. Simple Regression. Data. Howell dataset Hassles Number of minor daily hassles reported during a month (measure of stress) Psychological symptomology. First descriptives. Ouch!. Pearson r = 0.61. Big difference!.

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How to plot x-y data and put statistics analysis on

How to plot x-y data and put statistics analysis on. GLEON Fellowship Workshop January 14-18, 2013 Sunapee, NH Ari Santoso. Linear regression. It is an example of how to plot (x-y, scattered) our data and do linear regression analysis of the data

183 views • 6 slides

Zinc Data

Zinc Data. SPH 247 Statistical Analysis of Laboratory Data. zinc <- read.delim ("zinc.txt ") > names(zinc) [1] "Concentration" " Peak.Area " > zinc.lm <- lm( Peak.Area ~ Concentration,data =zinc) > summary( zinc.lm ) Call:

225 views • 5 slides