Analysis of Variance (ANOVA) is a statistical method used to compare means among three or more groups to ascertain if at least one group mean is significantly different from the others. This technique is widely used in various fields such as psychology, agriculture, and medicine. Below are three practical examples of ANOVA lab reports demonstrating its application in different contexts.
In this experiment, researchers aim to determine the effect of three different types of fertilizers on the growth of tomato plants over a period of two months.
The study involved three groups of tomato plants:
At the end of the study, the height of plants in centimeters was measured as follows:
Using ANOVA, the researchers calculated the F-statistic and p-value to assess whether there were significant differences between the groups. The results indicated a p-value of 0.02, leading to the conclusion that at least one type of fertilizer significantly affected plant growth.
In an educational study, researchers investigated the effectiveness of three teaching methods on student performance in mathematics. The three methods were traditional lectures (Method A), interactive workshops (Method B), and online learning (Method C).
After conducting a semester-long course, the final test scores of students in each method were recorded:
ANOVA was conducted to determine if there were statistically significant differences in the test scores across the teaching methods. The analysis produced an F-statistic of 6.43 and a p-value of 0.004, indicating significant differences. Further post-hoc tests revealed that Method B (interactive workshops) yielded significantly higher scores than the other methods.
A health study was conducted to assess the impact of three different diets on weight loss over a three-month period. The diets included a low-carb diet (Diet A), a Mediterranean diet (Diet B), and a vegan diet (Diet C).
Participants’ weight loss in kilograms was recorded as follows:
The researchers performed ANOVA to evaluate the differences in weight loss among the three diets. The results showed a p-value of 0.01, indicating statistically significant differences in weight loss across the diets. Post-hoc comparisons indicated that the Mediterranean diet resulted in significantly greater weight loss compared to the other two diets.