Quantitative Methods Questions Medium
In quantitative research, correlation refers to the statistical relationship between two or more variables. It measures the degree to which changes in one variable are associated with changes in another variable. Correlation can be positive, negative, or zero.
Positive correlation means that as one variable increases, the other variable also tends to increase. For example, there may be a positive correlation between the amount of time spent studying and the grades obtained in an exam. This indicates that students who study more tend to achieve higher grades.
Negative correlation, on the other hand, means that as one variable increases, the other variable tends to decrease. For instance, there may be a negative correlation between the number of hours spent watching television and academic performance. This suggests that students who spend more time watching TV tend to have lower grades.
Zero correlation indicates that there is no relationship between the variables. In this case, changes in one variable do not affect the other variable. For example, there may be zero correlation between shoe size and intelligence. This means that having a larger or smaller shoe size does not impact a person's intelligence.
Correlation is typically measured using a correlation coefficient, which ranges from -1 to +1. A correlation coefficient of +1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. The closer the correlation coefficient is to -1 or +1, the stronger the relationship between the variables.
It is important to note that correlation does not imply causation. Just because two variables are correlated does not mean that one variable causes the other to change. Correlation simply indicates that there is a relationship between the variables, but further research is needed to determine the underlying causes and mechanisms behind this relationship.