Based on the results of both the ANOVA test and T-test, we can conclude that there is a relationship between age and average amount of sleep an individual gets at night. The Chi-Square test shows that Vancouver population is representative of the population of Canada so we our sample is valid to represent Canada. We found that older individuals tend to sleep less than younger individuals. Young children acquire more sleep because of the large amount of physical activities they do during the day. Contrastingly, adults exert less energy physically however, they are constantly worried about family and work related stress which can affect their ability to sleep. This can be due a number of factors as aforementioned, including, but not limited to, a decrease in production of the sleep promoting hormone melatonin, sleep apnea and insomnia, an increase in daily life stresses, and the onset of various diseases and health disorders as a result of aging.

Our data displays a sampling bias, due to the fact that members of our group participated in convenience sampling, which only displayed data that represented samples that were closely related to members of our group. This does not accurately represent the population of Vancouver. Another bias in our data is the unbalance of genders in each age group. In some age groups, there are more females than males such as children and in older age groups, there are more males than females. A likely reason of the gender bias in seniors and adults could be because females are less willing to reveal their age even though we inform the participants this survey is confidential. In addition, participants may report a false age which could be a potential flaw in our data. Example of improvements to the project could be attempting other methods of sampling such as systematic sampling where we would survey every 5th person passing the library. This way we would get more randomized data. Further research includes a multi-variable regression which could include all the possible factors that affect sleep such as age, gender, use of social media, and any health problems.