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Bivarate Data - Coggle Diagram
Bivarate Data
Numerical Variable
A property that may have different values for different individuals and for which these values result from counting or measuring. Measurement variables are numerical, as are whole-number variables.
Multivarate Data
A data set that has several variables.
Example: A data set consisting of the heights, ages, genders and eye colours of a class of Year 9 students.
Discrete Variables
A discrete distribution could be an experimental distribution, a sample distribution, a population distribution, or a theoretical probability distribution.
Example: a random sample of households in New Zealand. The distribution of household sizes from this sample is an example of a discrete sample distribution.
Response Variables
a response variable, also known as a dependent variable, is a concept, idea, or quantity that someone wants to measure Example: Grade & Height
Continuous Variables
The variation in the values of a variable that can take any value in an (appropriately-sized) interval of numbers.
A continuous distribution may be an experimental distribution, a sample distribution or a theoretical distribution of a measurement variable.
Example: The height of a randomly selected individual from a population.
Categorical Variables
Data in which the values can be organised into distinct groups. These distinct groups (or categories) must be chosen so they do not overlap and so that every value belongs to one and only one group, and there should be no doubt as to which one.
example: The eye colours of a class of Year 9 students.
Correlation
The strength and direction of the relationship between two numerical variables.
Examole:The actual weights and self-perceived ideal weights of a random sample of 40 female students enrolled in an introductory Statistics course at the University of Auckland are displayed on the scatter plot below.
Bivariate Data
A pair of variables from a data set with at least two variables.
Consider a data set consisting of the heights, ages, genders and eye colours of a class of Year 9 students. The two variables from the data set could be:
both numerical (height and age),
both category (gender and eye colour), or
one numerical and one category (height and gender, respectively).
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Interpolation
The process of estimating the value of one variable based on knowing the value of the other variable, where the known value is within the range of values of that variable for the data on which the estimation is based.
Extrapolation
The process of estimating the value of one variable based on knowing the value of the other variable, where the known value is outside the range of values of that variable for the data on which the estimation is based.
causation
Causation indicates that one event is the result of the occurrence of the other event
Example when the weatherman says that it's going to rain lots of people decide to bring an umbrella with them that day