explanation of negative correlation in psychology with examples
Explanation Of Negative Correlation In Psychology With Examples
Statistically, correlation is a measurement of the relationship between variables. In psychology though, the concept represents the association between two variables/events/instances. This Buzzle article provides an explanation of negative correlation in psychology with examples.
- When two variables have no relationship, it indicates zero correlation.
- When the value of one variable increases/decreases simultaneously with the other, it indicates a positive correlation, that is to say, they are positively related to each other.
- The definition of negative correlation states that it is a relationship between two variables, such that when the value of one variable increases, the value of the other decreases and vice versa.
- It is akin to the concept of inverse proportion. The variables are negatively related to each other.
- In statistical studies, a perfect negative correlation can be expressed as -1.00, a perfect positive correlation can be expressed by +1.00, and a zero correlation is expressed as 0.00.
- The concept of negative correlation can be explained clearly by means of a scatterplot, as shown below.
- In the above diagram, you can see that the variables are grades and absenteeism. That is to say, the more the absenteeism, lesser the grades.
- At (60, 40), it indicates that 60% of absence in class will lead to 40% reduction in grades. Similarly, at (80, 20), it indicates 20% grades for 80% absenteeism.
- To understand why and how the above concept seems to be related to psychology, you need to understand correlational studies, which are often used as a measure to find out the relationship between variables in psychology.
- That is to say, when trying to analyze instances from a psychological perspective, it is essential to find out units of measurement related to the individuals/situation, perform a comparative study among a group of individuals, and come up with suitable inferences.
- So, when you deal with a situation, you first understand and classify the variables. Then, you have to collect data and observe and detect patterns.
- Post this step, you will be able to conclude and establish what kind of relationship they share.
- Consider an example for negative correlation. Let's say, a comparative study is being done among a group of individuals who consume alcohol.
- From this group, there will be people who drink very little to those who consume a lot per day. This will be your first variable―the amount of alcohol consumed.
- For the second variable, you may consider the health factor of these individuals―the heart, liver, etc.
- Of course, this may be a very random assumption; after all, every one handles the effect of alcohol according to their drinking habits and body constitution, and other factors play a major part in determining health as well.
- As you note down the data and compare them, you may notice that more the alcohol consumed, less healthy the individual is. Conversely, the lesser the alcohol consumption, the healthier the individual is. This is what negative correlation is.
- This may be true for all individuals or a select few. If the former is true, it is an example of perfect negative relationship (-1.00).
- If the latter is true, the variables may be weakly or moderately in a negative relationship.
- A value of -0.20 to - 0.29 indicates a weak negative relationship. A value of -0.30 to -0.39 indicates a moderate negative relationship.
- Two variables are said to have a strong negative relationship if the correlation value is between -0.40 to -0.69. And, a value between -0.70 to -0.99 indicates a very strong negative relationship.