INFERENTIAL STATISTICS: COMMON TESTS

Correlation

Correlation

• Correlation refers to a type of statistic, to find out about a particular relationship between two variables.
• The correlation coefficient is written as r.
• Correlation requires that both variables be quantitative.
• Correlation Coefficient, r measures the direction and the strength of the linear association between two numerical paired variables.
• Values range between –1 and +1 and measure the strength and direction of the relationship.
• A positive relationship exists when both variables increase and decrease at the same time. (Weight and height).
• A negative relationship exist when one variable increases and the other variable decreases or vice versa. (Strength and age).
• A scatter plot is used to explain the relationship between dependent and independent variable.
• By convention, the independent variable is plotted on the horizontal x-axis.  The dependent variable is plotted on the vertical y-axis.
• Independent variable: is a variable that can be controlled or manipulated.
• Dependent variable: is a variable that cannot be controlled or manipulated.  Its values are predicted from the independent variable.

Strength of linear Relationship

Example

1. Independent variable in this example is the number of hours studied.
2. The grade the student receives is a dependent variable.
3. The grade student receives depend upon the number of hours he or she will study.
4. Are these two variables related?