Please enable JavaScript.
Coggle requires JavaScript to display documents.
Correlation and Regression - Coggle Diagram
Correlation and Regression
Correlation-
a statistical technique that is used to measure and describe the relationship between two variables.
scatter plot-
a type of graph used to show the relationship between two different variables.
positive correlation-
the two variables tend to change in the same direction
negative correlation-
the two variables tend to go in opposite directions
envelope-
a boundary around a scatter plot or line graph that shows variation or confidence limits.
Pearson correlation-
measures the degree and the direction of the linear relationship between two variables.
sum of products-
measure how two variables change together.
definitional formula-
a way to directly calculate how two variables vary together, computes the sum of the products of the deviations.
computational formula-
another way to compute the sum of the products of the deviations.
linear relationship-
how well the data points fit a straight line.
correlation matrix-
a table that shows the relationship between multiple variables.
Using and interpreting the Pearson Correlation
Prediction-
using known information (like data you’ve collected) to estimate or guess an unknown value.
Validity-
a test or tool measures what it’s supposed to measure.
Theory Verification-
checking to see if an idea (or "theory") about how something works is actually true by using data and evidence.
Reliability-
a test gives consistent results—even if it’s taken more than once or by different people.
outliers-
One or two extreme data points.
restricted range-
a situation where the data being analyzed doesn't cover the full spectrum or variety of possible values.
coefficient of determination-
measures the proportion of variability in one variable that can be determined from the relationship with the other variable. r^2
Alternatives to the Pearson Correlation
Spearman correlation-
a statistical method used to measure the strength and direction of the relationship between two variables, but it differs from the Pearson correlation in that it is based on the rank (or order) of the data, not the actual values.
monotonic-
a sequence that is consistently increasing (or decreasing).
point-biserial correlation-
used to measure the relationship between two variables in situations in which one variable consists of regular, numerical scores, but the second variable has only two values.
dichotomous variable-
or a binomial variable, A variable with only two values.
phi-coefficient-
a measure of association for two binary (dichotomous) variables.
Introduction to Linear Equations and Regression
linear equation-
an equation that describes a straight line when plotted on a graph.
slope-
a measure of how steep the line is. In the context of a linear equation
Y-intercept-
he point where a line crosses the y-axis on a graph.
regression-
a statistical method used to understand the relationship between two or more variables.
regression line-
a straight line that best represents the relationship between two variables in a scatter plot.
least-squared-error solution-
a method used to find the line that best fits the data points in a scatter plot.
regression equation for Y-
the formula that describes the relationship between two variables — a predictor (independent variable, X) and an outcome (dependent variable, Y).
standardized form of the regression equation
- expresses the relationship between standardized scores (z-scores) rather than raw scores.
standard error of estimate-
tells you how much the actual data points deviate from the regression line.
analysis of regression-
The process of testing the significance of a regression equation