And so survival time is the response variable. The type of therapy given is the explanatory variable; it may or may not affect the response variable. In this example, we have only one explanatory variable: type
And so survival time is the response variable. The type of therapy given is the explanatory variable; it may or may not affect the response variable. In this example, we have only one explanatory variable: type of treatment. In real life you would have several more explanatory variables, inc...
The usage of mathematical models and statistics in any professional application is to serve four main purposes: 1. Determine explanatory factors; 2. Determine the sensitivity of the dependent variable to explanatory factors; 3. Estimate outcome values; 4. Perform sensitivity and what-if analysis, to...
Both the simulations and the data example indicate that the proposed methods are feasible, reliable and appropriate for analyzing the gold price time series.doi:10.1080/03610926.2021.1964529Kai YangBo PengXiaogang DongCommunication in Statistics- Theory and Methods...
But sometimes, the term “explanatory variable” is preferred over “independent variable”, because in real world contexts, independent variables are often influenced by other variables. That means they’re not truly independent. Example: Explanatory versus independent variables ...
And so survival time is the response variable. The type of therapy given is the explanatory variable; it may or may not affect the response variable. In this example, we have only one explanatory variable: type of treatment. In real life you would have several more explanatory variables, inc...
In addition, coefficients of the explanatory variables can be more easily interpreted because they will estimate the direct relationship between the explanatory variable and the dependent variable while filtering out the noise introduced by spatial effects. This tool is intended to create explanator...
The integer autoregressive (INAR) model defined through the thinning operator can be used to model many count data in applications. Usually, the autoregressive parameter in the thinning operator is assumed to be constant or random variable varying in [0,1]. To make the INAR model more practica...
Example: Explanatory research You have been teaching statistics to undergraduate students during both the first and second semesters for several years in a row. You analyzed their final grades and noticed that the students who take your course in the first semester always obtain higher grades than ...
In this example, explanatory variable is type of treatment. However, in real life there could be several more explanatory variables, including: age, health, weight, and other lifestyle factors. Example 2: Height & Age A group of middle school students want to know if they can use height to...