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Standard Error of the Estimate or SEE

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  • Also called Standard Error of the Regression
  • Conceptually SEE helps to measure how imperfect your model is at predicting the value for a dependent variable, Y.
  • Mathematically SEE can be seen a measure of deviation(s) around your model’s regression line, a line one deviation above and below the predicted equation line

The following video explains the concept using sample data from Google and yahoo stock quotes.

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Quants: Single Variable Linear Regression Analysis

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Confidence Intervals (CI) for Dependent Variable Prediction

01
CFA L2: Quantitative Methods - Introduction
02
Quants: Correlation Analysis
03
Quants: Single Variable Linear Regression Analysis
04
Standard Error of the Estimate or SEE
05
Confidence Intervals (CI) for Dependent Variable Prediction
06
Coefficient of Determination (R-Squared)
07
Analysis of Variance or ANOVA
08
Multiple Regression Analysis
09
Multiple Regression and Coefficient of Determination (R-Squared)
10
Fcalc – the Global Test for Regression Significance
11
Regression Analysis and Assumption Violations
12
Qualitative and Dummy Variables in Regression Modeling
13
Time Series Analysis: Simple and Log-linear Trend Models
14
Auto-Regressive (AR) Time Series Models
15
Auto-Regressive Models - Random Walks and Unit Roots
16
ARMA Models and ARCH Testing
17
How to Select the Most Appropriate Time Series Model?

Topics

Risk Management
Statistical Methods