What does a paired sample t test tell us?
One continuous, dependent variable (e.g. Fear of Statistics Test scores) measured on two different occasions or under different conditions. A paired-samples t-test will tell us whether there is a statistically significant difference in the mean scores for Time 1 and Time 2. Assumptions: The basic assumptions for t-tests should be checked.
How to choose the right type of statistical test?
Nominal: represent group names (e.g. brands or species names). Binary: represent data with a yes/no or 1/0 outcome (e.g. win or lose). Choose the test that fits the types of predictor and outcome variables you have collected (if you are doing an experiment, these are the independent and dependent variables ).
How many types of data are used in statistics?
There are four main levels of measurement/types of data used in statistics. They have different degrees of usefulness in statistical research.
How is a regression test used to test a relationship?
Regression tests are used to test cause-and-effect relationships. They look for the effect of one or more continuous variables on another variable.
When to use a repeated measures t test?
Repeated-Measures t-test The t-test assesses whether the mean scores from two experimental conditions are statistically different from one another. A repeated-measurest-test (also known by other names such as the paired samples or related[ t-test) is what you should use in situations when your design is within participants.
How to write up the results of a t test?
When writing up the results of your t-test you need to report whether or not the test was significant following this formula: t (df) = t value, p = p value…where you insert the relevant numbers into the underlined sections. For this particular example, we have found that the t-test is significant as the p-value is less than 0.05.
Can you do a one tailed t test?
Paired samples t-tests only calculate two-tailed p-values. However if your hypothesis is directional you can make it 1-tailed test by simply halving the p-value. What do we need from our output? When writing up the results of your t-test you need to report whether or not the test was significant following this formula: (df) = t value, p = p value