Example of dependent/explained Variable for Markov switching model
Linear regression is graphically depicted using a straightline of best fitwith the slope defining how the change in one variable impacts a change in the other. The y-intercept of a linear regression relationship represents the value of the dependent variable when the value of the independent variab...
The article focuses on the question of reliable assessment of the goodness of fit. The first part of the article reviews the measures of predictive power and then assesses the impact of the distribution of the dependent variable on the selected measures of goodness of fit. As a result, the ...
The attitude rating question is needed for the identification of the “ideal line” on which the ideal position is located by using the attitude toward the brand as the dependent variable and he factor scores as the independent variables. The beta coefficients of the independent variables (which ...
This movement expresses the law of demand, which states that as the price of a given commodity increases, the quantity demanded decreases as long as all else is equal. Note that this formulation implies that price is the independent variable, and quantity is the dependent variable. In most ...
Acontrol variableis a variable that could affect the dependent variable, however it is held constant, so it doesn’t interfere with the outcome. Using the same example, a control variable could be the‘quality of internet connection’. For instance, if the website is down or customers suddenl...
Define and give an example of equal matrices. Provide an example of a data set that would be in the binomial setting. Can be the dependent variable be nominal? Define and give an example of Row Matrix. Give four different symbols that have been used to represent statistical measures. Describ...
Variable costs are dependent on production output. Variable costs are directly related to production volume. Total variable costis the total cost, which is not fixed cost incurred for the total quantity of output expressed as: Total Variable Cost = Total Quantity * Variable cost per unit ...
Formula and Calculation of Multiple Linear Regression (MLR) yi=β0+β1xi1+β2xi2+...+βpxip+ϵwhere, fori=nobservations:yi=dependent variablexi=explanatory variablesβ0=y-intercept (constant term)βp=slope coefficients for each explanatory variableϵ=the model’s error term (also known ...
If the variance of the error term is homoskedastic, the model was well-defined. If there is too much variance, the model may not be defined well. Adding additional predictor variables can help explain the performance of the dependent variable. Oppositely, heteroskedasticity occurs when the vari...