Population: FamiliesVariable: Wealth.
Population, in statistics, is the entirety of units for which some variable information is collected for statistical purposes. "Population" need not have anything to do with people. For example, in a forestry study the population might be all trees in a given area, and the measured variable could be the species and/or ages of a selection (sample) of the population.
you might not get the experiment correct (:
lurking
I could help when you are dealing wit a hidden variable and will help solve the question. The expression has no answer so it shows the work.
We would need more information about the situation to respond to this question.
Population, in statistics, is the entirety of units for which some variable information is collected for statistical purposes. "Population" need not have anything to do with people. For example, in a forestry study the population might be all trees in a given area, and the measured variable could be the species and/or ages of a selection (sample) of the population.
you might not get the experiment correct (:
variable
What might be the dependent variable in Shannon lucid's experiment
lurking
extraneous variable can be defined as any variable other than the independent variable that could cause a change in the dependent variable. In our study we might realize that age could play a role in our outcome, as could family history, education of parents or partner, interest in the class topic, or even time of day, preference for the instructor's teaching style or personality. The list, unfortunately, could be quite long and must be dealt with in order to increase the probability of reaching valid and reliable results.
dependent variable
In well-designed experiment, the dependent variable might be affected by the factor being tested. The dependent variable refers to any variable whose value depends on that of another.
Yes, but it might be a bit crowded.
dependent variable
dependent variable
They are the variables that you think predict some outcome (which is considered the dependent variable). So you might have a theory that gender and age predicts personal income. Gender and age are the independent variables, and income is the dependent. The choice of whether a variable is independent or dependent often is driven by the question you're trying to answer. So in many cases it's possible that the same variable could be an independent variable in one analysis, but a dependent variable in a different analysis. For example, while income was the dependent variable in the earlier example, if you were trying to predict whether a child goes to college, the parents' income might be an important independent variable in that case.