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Bivariate Data - Melissa + Sheryn - Coggle Diagram
Bivariate Data - Melissa + Sheryn
Multivariate Data
eg. how various characteristics like fruit, weight, colour all relate
effect of multiple independent variables on two or more dependent variables
Bivariate Data
data collected in two variables , each data point is one variable has a correlating data point in the other — how one variable affects another
Numerical Variable
measurement of data taken in numerical value
eg. height in cm, weight in kg, speed in m/s, circumference or diameter of an object
Categorical Variables
data of variable taken as one of fixed possible values; each individual is likely to be measured on the basis of a qualitative property, fits into a certain category
eg. race, sex, age group, eye colour
Discrete Variables
measured in particular finite number of distinct values, integers
eg. number of houses/cars owned, countries population, no. of books issued
Correlation
a statistical measure that expresses the extent to which two variables are linearly related (meaning they change together at a constant rate)
eg. the height and weight of a person are related, and taller people tend to be heavier than shorter people.
Continuous Variables
variables that can assume any value within a specified range, can be a fraction/decimal - do not have to be fixed intervals/ratio
eg. weight (measured in kilograms and decimal points), temperature (takes on any value in an interval with decimal points)
Response Variables
variable that is being measured, is what changes as a result of the explanatory variable (variable that is being manipulated—essentially the dependent variable
eg. doing an experiment on seeing the effect of caffeine dose on reaction time: response variable = reaction time
Interpolation
a technique to estimate the values of unknown date points that fall in between existing, known data points.
eg. if a child's height was measured at age 5 and 6, interpolation could be used to estimate the child's height at age 5.5
extrapolation
a technique to predict future data based on historical data.
eg., estimating the size of a population after a few years based on the current population size and its rate for growth.
regression & regression line
A regression line is an estimate of the line that describes the true, but unknown, linear relationship between the two variables. / a measure of the relation between the mean value of one variable.
It is used to predict or estimate the value of the response variable from a given value of the explanatory variable. Explanatory variable is a type of independent variable.
eg. an insurance company might have limited resources with which to investigate homeowner's insurance claims. With linear regression, the company's team can build a model for estimating claims costs.
Causation
one event is the result of the occurence of the other event
eg. the job promotion in the first example caused the salary of the employee to increase
