By Kanza Khan
T TEST AND ANOVA
The T-test assesses whether the means of two groups are statistically different from each other. It gives a p value. The p value is the evidence against a null hypothesis. The null hypothesis states that there is no relationship between variables being tested. The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. The most common threshold is p < 0.05 (5%). This indicates that there is less than 5% probability that the NULL hypothesis is true hence it is rejected and the alternative hypothesis is accepted.
There are two types of T tests: Independent T test and paired T test
Independent T test tests two groups; Experimental vs Control group.
An example is an experiment studying the effect of a new fertilizer on the growth of mint plant in the backyard. There are TWO groups of plants: an Experimental Group that has potting mix added to it and a Control Group that has no mix. After you have calculated the average growth for each of the two groups, run a t-test to see if there is a “statistically significant” difference in their growth. The t-test returns a p value that expresses the probability that this null hypothesis is wrong.
Paired t test is also called dependent sample T-test. It is usually used for “Before vs. After” type experiments, where the same individuals are measured before and after the application of some sort of treatment.
An example is that of an experiment where green tea causes weight loss if taken consistently for 12 weeks. Individuals are weighed at the start of 12 weeks and at the end of 12 weeks while consuming green tea for this duration.
ANOVA stands for Analysis of Variance. ANOVA is used to determine whether there is any difference in variance between three or more groups. It may be assumed that if the variance is similar between three groups, means must be similar too though that might not always be the case.
There are two types of ANOVA: One way ANOVA and two way ANOVA
ONE WAY ANOVA uses one independent variable. An example is type of fertilizer and treating crop fields with three different mixtures to find out difference in growth of crop.
Another example is weight loss in three different groups. Each group is doing a different diet. One group is on kept diet, second is on Atkins diet and third is on paleo diet.
TWO WAY ANOVA uses two independent variables. An example is that of sunlight (NO sunlight, Low, Medium, High) and watering frequency(daily, weekly) impact the growth of mint plant.
Another example is of SIMS & AIMC students scores in Medicine and Surgery exams.
A step by step tutorial of how these tests are performed in Microsoft Excel sheet is shown above in the attached video presentation.