ANOVA ANOVA One field that has been applied in a variety of s is statistics. Both scientist and no scientists interact with numbers almost every day of their lives. Statistics plays a big role in informing the audience, changing their opinions as well as well as creating curiosity. This paper will look how analysis of variance can be used in enhancing understanding of a given issue. Ideally, ANOVA is best suited when an analysts wish to compare the means of at least two groups or level of independent variables (Steinberg, 2010). One issue I would like to explore is with regards to individuals eating fast foods based on their age. It has been alleged that younger members of the society, especially from both developed and developing countries do not have time to engage in eating healthy. Due to their tight schedules as students or young professionals, they tend to consume fast food to save on time and to socialize.
From this idea, the independent variable would be the respondents age. This can be explained by the fact that ones age should dictate on fast food consumptions. Similarly, the dependent variable will be the frequency of fast food consumption. After running the analysis, I expect to find out that there is a significant difference in the mean number of times respondents consume fast food at the different level of age, (F= 4. 962, P= 0. 000). Similarly, I expect that the Tukey post hoc test will show that younger individuals probably less than 25 years old will have a significantly higher mean number of times they eat fast food (Mean= 10. 66) when compared to older respondents over 30 years (Mean= 6. 64)
Reference
Steinberg, J. (2010). Statistics Alive! New York: Sage Publications, Inc.
