Identify the α or alpha-value. The problem statement generally gives you the alpha-value, also known as the significance level. You just need to find it from your reading. When you find the alpha-value, circle, mark or highlight it.
Determine the null hypothesis. Think of the null hypothesis as the default hypothesis that you try to disprove or want to test (see references 1). Generally, the null hypothesis states that things don't bring any changes or they stay the same. For example, you heard that sleeping less than 5 hours a night affects academic performance. Your null hypothesis would be "sleeping less than 5 hours a night does not affect academic performance."
Carry out the significance test. You need to correctly apply the significance test to get the correct p-value. Think of the p-value as the probability of getting the observed result given that the null hypothesis is true. Apply the significance test to one group at a time, then highlight the answer or circle it so that you can locate it easily.
Begin by stating whether the p-value is greater or lesser than alpha. Remember to state the values as well. Then determine whether you would reject or accept the null hypothesis. If the p-value is greater than the alpha-value, then you would accept the null hypothesis. If the p-value is lesser than the alpha-value, then you would reject the null hypothesis. Finally, interpret the results. Example of a summary statement: "In group 1, the p-value (0.44) > α (0.05). In group 2, the p-value (0.01) < α (0.05). Thus, aloe vera leaf skin does not have a statistically significant anti-inflammatory effect on the skin. However, aloe vera gel does have a statistically significant anti-inflammatory effect on the skin. We can conclude that there is a statistically significant difference between aloe vera leaf skin and aloe vera gel in anti-inflammatory effect."