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CORRELATION AND REGRESSION - Coggle Diagram
CORRELATION AND REGRESSION
CORRELATION:
statistical technique used to measure and describe the relationship between two variables
CORRELATION AND CAUSATION:
Although there may be a causal relationship, the simple existence of a correlation does not prove it.
POSITIVE CORRELATION:**
relationship in which two variables tend to change in the same direction
NEGATIVE CORRELATION:
correlation in which two variables tend to go in opposite directions
PEARSON CORRELATION:
measure of the degree and the direction of the linear relationship between two variables
COEEFICIENT OF DETERMINATION:
measure of proportion of variability in one variable determined from the relationship with another variable
SPEARMAN CORRELATION: r
elationship between two variables when both are measured in ordinal scales
MONOTONIC RELATIONSHIP:
consistently one-directional relationship between two variables
SUM OF PRODUCTS OF DEVIATIONS:**
measure of the amount of covariability between two variables
OUTLIER:
extreme datum point
RESTRICTED RANGE:
set of scores that do not represent the full range of possible values
CORRELATION MATRIX:
diagram of results from multiple relationships
POINT-BISERiAL CORRELATION:
relationship between two variables, one consisting of regular scores and the second having two values
DICHOTOMOUS VARIABLE:
relationship between two variables, one consisting of regular scores and the second having two values
PHI COEEFICIENT:
relationship between two variables when both measured for each individual are dichotomous
LINEAR EQUATION:
a mathematical model used to predict the value of a dependent variable based on the value of an independent variable.
LINEAR RELATIONSHIP:
equation expressed by the equation Y = bX + a
SLOPE:
value which determines how much Y variable changes when X is increased by one point
Y-INTERCEPT:
value which determines the value of Y when X = 0
REGRESSION:
statistical technique for finding the best-fitting straight rule for a set of data
REGRESSION LINE:
the resulting straight line of a regression
LEAST-SQUARED-ERROR SOLUTION:
best-fitting rule with the smallest total squared error
REGRESSION EQUATION FOR Y:
linear equation
STANDARD ERROR OF ESTIMATE:
measure of standard distance between predicted Y values on regression line and actual Y values
ANALYSIS OF REGRESSION:
process of testing the significance of a regression equation