Correlation measures the relationship between two variables. It can be positive, meaning the variables increase or decrease together, or negative, meaning one variable increases as the other decreases. The Pearson correlation coefficient ranges from -1 to 1, with -1 indicating a perfect negative correlation, 0 indicating no correlation, and 1 indicating a perfect positive correlation. Values between -1 and 0 represent negative correlation, while values between 0 and 1 represent positive correlation. Graphically, correlation strength can be classified as small, medium, or large depending on how close the coefficient is to -1 or 1.
3. Correlation
• Correlation is the relationship or
connection between two or more things.
• Correlation is the study of relationship of
one variable to another.
• Interdependence of variable
4. Correlation
• Correlation is positive when both variables
increase or decrease together. e.g:
demand has increased and prices of
colors increase.
• Correlation is consider negative when one
increase and other variable decrease. e.g:
supply of hair colors has increased then
demand of color has decreased.
5. Pearson correlation
• It refers to the Pearson R correlation, a
statistical formula which is used to
measure strength between variable and
relationship.
• To determine the strong relation between
variables, its range from -1.00 to 1.00
• Positive
• Negative
6. Coefficient of correlation
• Correlation coefficient are expressed as
value between +1 to -1.
• When both variable increase or decrease
together, it would consider positive
correlation.
• The change of variable in opposite
direction would consider negative
correlation
• if value come in zero then no realtion.
7. Coefficient of correlation
• -1 0 +1
perfect negative perfect reliable
correlation
-0.39 poor adverse 0—0.39poor reliable
-0.40 -- -0.69 moderate 0.40—0.69 moderate
-0.70 -- -0.99 high o.70—0.99 high
