Measures of Difference: T-TEST Flashcards
Why are t-tests important?
Allows us to determine if a sample mean is significantly differed from a hypothesised value.
What is the importance of two tail t-tests?
Allows us to determine if differences in means between two groups are statistically different.
What kind of data is required in two tail t-tests?
Continuous data on one variable and nominal (2 category) data on another.
List the two types of t-tests.
- Paired Samples t-tests
- Independent Samples t-tests
When are Paired Samples t-tests used?
When we do not have independent samples and the means are correlated because they are from the same observations.
How are Paired Samples t-tests caclulated?
The correlated t test is computed by first computing the differences between the two scores for each subject. Then, a test of a single mean is computed on the mean of these difference scores.
When are Independent Samples t-tests used?
When the two groups we are interested in are based on differing nominal characteristics at one point in time.
Give some examples of Independent Samples.
Males, females
Immigrants, non-immigrants
Private sector employees and public sector employees
High social class and low social class.
Write the formula for a t-test.
calculate the mean of each group, subtract those means and divide by standard error of the difference between the means.
What do we need to look for when interpreting t-tests?
- Mean and differences between means
- t-statistic and degrees of freedom
- Confidence interval of the difference
- P-value
List the assumptions that are made when carrying out an Independent Sample t-test.
- The data are continuous (not discrete).
- The data follow the normal probability distribution.
- The variances of the two populations are equal.
- The two samples are independent. There is no relationship between the individuals in one sample as compared to the other.
- Both samples are simple random samples from their respective populations.
