The t-test is one of the most frequently used statistical procedures. It compares the means of two groups. The t-test can be divided into two types - the test which analyses data from groups which are independent and the t-test which is performed on the basis of information about related groups. In the second case the participants of the test do not share many common characteristics, while those who participate in the independent t-test do.
In order to analyze the data from the table, it is necessary to perform the following steps:
Create sample 1 and list data for it
Create sample 2 and list data for it
Define the number of replicates for each of the samples
Calculate each sample’s mean
Both samples should have s 2 calculated.
The two means calculated in the previous step should have calculated variance
sd should be calculated as well in order to find out the square root
t value requires calculation
the t-table should be entered at the freedom degrees; it is also necessary to choose the level of the significance which is normally required and read the t value which is tabulated;
If the t value turns out to exceed the tabulated value, this means that the level of probability is significantly different.
The variables included in the analysis would be gender, age, Pre-MBI, Post-MBI, days_tx, case, and weight loss. The dependent variables would be gender and age, the rest are independent since these are the most likely to demonstrate different results. However, dependent t-test should be used in order to compare the groups by the issue of gender and age – such analysis is more likely to bring scientific contribution and lead to conclusion which might be related to health promotion (Student’s T-test).
References
Student’s T-test. Retrieved from HYPERLINK "http://www.biology.ed.ac.uk/archive/jdeacon/statistics/tress4a.html" http://www.biology.ed.ac.uk/archive/jdeacon/statistics/tress4a.html
RELATED AND INDEPENDENT T-TESTS PAGE \* MERGEFORMAT …