Mathisens Test
- A hypothesis test that assesses whether a relationship between two variables is statistically significant.
- Typical steps: state a null hypothesis, choose sample size, collect paired data, compute a test statistic, and compare it to a critical value.
- Commonly applied in fields such as psychology and sociology.
Definition
Section titled “Definition”Mathisen’s test is a statistical method used to evaluate the significance of a relationship between two variables.
Explanation
Section titled “Explanation”- “Significance” here means the likelihood that an observed result is not due to chance but reflects a real relationship between the variables.
- The test begins with a null hypothesis asserting no relationship between the two variables.
- The researcher determines a sample size; larger samples yield more accurate results.
- Data are collected for the two variables being studied.
- A test statistic is calculated using a formula that accounts for the sample size, the mean and standard deviation of the two variables, and the correlation between them.
- The calculated test statistic is compared to a pre-determined critical value. If the statistic exceeds the critical value, the relationship is considered significant.
Examples
Section titled “Examples”Alcohol consumption and academic performance
Section titled “Alcohol consumption and academic performance”A researcher defines the null hypothesis as there being no relationship between alcohol consumption and academic performance, collects data on both variables for a sample of college students, calculates the test statistic using Mathisen’s formula, and compares it to the critical value to determine significance.
Exercise and weight loss
Section titled “Exercise and weight loss”A researcher defines the null hypothesis as there being no relationship between exercise and weight loss, collects data on exercise habits and weight loss for a sample of people, calculates the test statistic using Mathisen’s formula, and compares it to the critical value to determine significance.
Use cases
Section titled “Use cases”- Frequently used in psychology and sociology to determine whether observed relationships between variables are statistically significant.
Notes or pitfalls
Section titled “Notes or pitfalls”- Larger sample sizes produce more accurate results.
Related terms
Section titled “Related terms”- Null hypothesis
- Test statistic
- Critical value
- Correlation
- Mean
- Standard deviation
- Statistical significance