Q: Non examples of independent and dependent variables?

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well dependent is when you are are NOT independent so in your daily life you could just have S.E.X and then that is how you become non independent

dependent variables, independent variable, nominal, ordinal, interval, ratio variableThere are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.

in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.

There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative. There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

It is a relationship which is non-linear. The same amount of change in the independent variable brings about different amounts of changes in the dependent variable and these differences depend on the initial values of the independent variable.

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well dependent is when you are are NOT independent so in your daily life you could just have S.E.X and then that is how you become non independent

When non-experimental variables are held constant, it means keeping factors other than the independent variable the same for all participants or conditions in order to ensure that any observed effects are due to the independent variable and not to any other variable. This helps to isolate the impact of the independent variable on the dependent variable and strengthens the validity of the experiment.

Directional manipulate the independent variables and then the dependent also will change because from its name wich dependent so it will change like the first one will change alsoo.It show us precise nature of relationship.

dependent and subordinate

dependent variable

dependent variables, independent variable, nominal, ordinal, interval, ratio variableThere are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.

in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.

There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative. There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

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It is a relationship which is non-linear. The same amount of change in the independent variable brings about different amounts of changes in the dependent variable and these differences depend on the initial values of the independent variable.

Table The difference in the values of the "dependent" variable is a fixed multiple of the difference between the corresponding values of the independent variable. And the value of the dependent variable is non-zero when the independent is zero.Graph A non-vertical straight line which does not pass through the origin.Equation y = mx + c (or equivalent) where m is some real number and c is non-zero.

In mathematics, when the dependent variable is not proportional to the independent variable. The function does not vary directly with the input. Example: y=sin (x).