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A set of data involving only one variable is referred to as univariate data. This type of data focuses on a single characteristic or measurement, allowing for analysis of its distribution, central tendency, and variability. Examples include a dataset of students' heights or test scores, where only one attribute is examined. Univariate analysis can help identify patterns or trends within that single variable.
A discrete variable.
35 occurs most often in the collated data set.
The y-Variable
The relationship between one set of data that decreases as another set of data increases is described as an inverse or negative correlation. In this scenario, when the values of one variable rise, the values of the other variable fall, indicating that they move in opposite directions. This type of relationship can be observed in various contexts, such as the relationship between supply and price or the relationship between demand and price.
A set of data with one variable is a net-graph
Univariate.
A discrete variable.
The observed values of a variable form the data set. Not sure where "element" fits into it.
Bivariate
35 occurs most often in the collated data set.
An experiment usually involves a set of steps involving one variable. This is what is being tested. A control involves the same steps without the one variable. The results are checked against each other to see if the variable had any effect.
An experiment usually involves a set of steps involving one variable. This is what is being tested. A control involves the same steps without the one variable. The results are checked against each other to see if the variable had any effect.
An experiment usually involves a set of steps involving one variable. This is what is being tested. A control involves the same steps without the one variable. The results are checked against each other to see if the variable had any effect.
The y-Variable
The relationship between one set of data that decreases as another set of data increases is described as an inverse or negative correlation. In this scenario, when the values of one variable rise, the values of the other variable fall, indicating that they move in opposite directions. This type of relationship can be observed in various contexts, such as the relationship between supply and price or the relationship between demand and price.
Discrete data are observations on a variable that which take values from a discrete set.