Variables are symbols that replace unknown numbers. Variables are often letters. For example:
5*x=10
7*6=y
Here "x" and "y" are the variables.
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
Examples of independent variables are:AgeRaceeducationWhy age is independent? because you can assign many variables that are dependent to age. Example: maturity, character, experience, and similar others.Race is also independent since many variables can be due to race. Example: color of the skin, language, belief, height, and similar others.But a race may also become a dependent variable if you relate it to- example the european continent. European continent now becomes the independent variable and races, beliefs, religions, and languages are dependent variables.
dependant and independent
Independent variables are the factors or conditions that are manipulated or changed in an experiment to observe their effect on dependent variables. They are often referred to as predictors or explanatory variables. For example, in a study examining the impact of study time on test scores, the amount of study time would be the independent variable.
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
The two types of variables in an experiment are independent variables, which are controlled by the experimenter and can be manipulated, and dependent variables, which are the outcome or response that is measured in the experiment and may change in response to the independent variable.
Dependent and Independent variables
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
Examples of independent variables are:AgeRaceeducationWhy age is independent? because you can assign many variables that are dependent to age. Example: maturity, character, experience, and similar others.Race is also independent since many variables can be due to race. Example: color of the skin, language, belief, height, and similar others.But a race may also become a dependent variable if you relate it to- example the european continent. European continent now becomes the independent variable and races, beliefs, religions, and languages are dependent variables.
dependant and independent
An example of an independent variable is how many people to feed. An example of a dependent variable is how many eggs.
Independent variables are the factors or conditions that are manipulated or changed in an experiment to observe their effect on dependent variables. They are often referred to as predictors or explanatory variables. For example, in a study examining the impact of study time on test scores, the amount of study time would be the independent variable.
Partial independence refers to a statistical relationship where two random variables are independent under certain conditions or given specific information, but not universally independent. This concept is often applied in fields like probability theory and machine learning, where the relationship between variables may change based on the context or additional variables. For example, two variables might be independent when conditioned on a third variable, indicating a more nuanced understanding of their interactions.
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
a DEPENDENT variable is one of the two variables in a relationship.its value depends on the other variable witch is called the independent variable.the INDEPENDENT variable is one of the two variables in a relationship . its value determines the value of the other variable called the independent variable.
Independent and dependent are types of variables. These variables are used mostly in science and math. When using independent variables you can control them dependent variables you cannot.
! ANOVA is generally computed for two or more QUANTITATIVE variables. If the quantitative variables are two or less in number, people prefer the t test (one sample t, paired t, or independent samples t) The Independent variable however is qualitative( for example, Girls and boys or Names of Schools.) It is the dependent variable that is Quantitative (for example, the ages - 2, 5 , 70, etc or weight or number of somethings). If you have 2 independent variables, you go for the two way ANOVA. Else, it's the one way ANOVA. !