Sentences with phrase «terms of random variables»

A statistical model uses a set of math equations to describe the behavior of something in terms of random variables and probability.

Not exact matches

This might also involved was is the integral of what is called the probable density function as it applies to a random variable in terms of all its possible values.

Unlike the common practice with other mathematical variables, a random variable can not be assigned a value; a random variable does not describe the actual outcome of a particular experiment, but rather describes the possible, as - yet - undetermined outcomes in terms of real numbers.

Such a matched group design is weaker in terms of its ability to support strong causal conclusions than a random assignment design because it doesn't eliminate the possibility that the two groups differed at the outset of the study on variables not measured and therefore not included in the matching algorithm.

The error term, εij, is distributed as a logistic random variable with set variance of 1.6 [33].

For variables which are the cumulative sum of random disturbances the proper statistical analysis should be in terms of the period - to - period changes in the variable.

General Introduction Two Main Goals Identifying Patterns in Time Series Data Systematic pattern and random noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time Series

The regression model takes the GCM input as representative of the explanatory power of a class of GCMs and constructs a random term using the residual unexplained by the independent variables and the SAC error weighting model.