# Mathisen’s test

## Mathisen’s test :

Mathisen’s test is a statistical method used to evaluate the significance of a relationship between two variables. It is often used in the fields of psychology and sociology to determine whether a particular relationship is statistically significant, or if it is simply the result of chance.
To understand Mathisen’s test, it is helpful to have a basic understanding of statistics and probability. In statistics, the term “significance” refers to the likelihood that a particular result is not due to chance, but rather reflects a real relationship between the variables being studied. For example, if a researcher is studying the relationship between a person’s age and their income, and finds that older people tend to earn more money than younger people, this relationship is considered significant if it is unlikely to have occurred by chance.
To conduct a Mathisen’s test, the researcher must first define the null hypothesis, which is the assumption that there is no relationship between the two variables being studied. In the example above, the null hypothesis would be that there is no relationship between a person’s age and their income.
Next, the researcher must determine the sample size, which is the number of people who will be included in the study. The larger the sample size, the more accurate the results of the test will be.
Once the sample size has been determined, the researcher must collect data on the two variables being studied. In the age and income example, the researcher might collect data on the ages and incomes of a sample of people.
After the data has been collected, the researcher must calculate the test statistic, which is a measure of the strength of the relationship between the two variables. In Mathisen’s test, the test statistic is calculated using a formula that takes into account the sample size, the mean and standard deviation of the two variables, and the correlation between the two variables.
Finally, the researcher must compare the calculated test statistic to a critical value, which is a pre-determined value used to determine whether the relationship between the variables is significant. If the calculated test statistic is greater than the critical value, the relationship is considered significant.
One example of a situation in which Mathisen’s test might be used is in a study of the relationship between alcohol consumption and academic performance in college students. In this study, the researcher might define the null hypothesis as there being no relationship between alcohol consumption and academic performance. The researcher might then collect data on the alcohol consumption and academic performance of a sample of college students, calculate the test statistic using Mathisen’s formula, and compare the calculated test statistic to the critical value to determine whether the relationship is significant.
Another example of a situation in which Mathisen’s test might be used is in a study of the relationship between exercise and weight loss. In this study, the researcher might define the null hypothesis as there being no relationship between exercise and weight loss. The researcher might then collect data on the exercise habits and weight loss of a sample of people, calculate the test statistic using Mathisen’s formula, and compare the calculated test statistic to the critical value to determine whether the relationship is significant.