Quartile Q1: 3
Quartile Q3: 4
Average (mean): μ=3.56621621622Minimum: 2
Quartile Q1: 3
Quartile Q3: 3.8
Average (mean): μ=3.3056
packed lunch bought lunch
For my analysis, I generated 2 scatterplots and boxplots to visually see where most of the results lied. For the explanatory variable, I set it as either packed or bought lunches, and for the response variable, I set it to weighted GPA. There were 12 more responses for packed lunches, so the results might be a little biased towards packed lunches. I could improve my sampling techniques to hopefully get the same number of each next time. However, judging from the scatterplot, the packed lunch has clusters near 4 while bought lunch has an even distribution from 3-4. The mean for the packed lunches was 3.6 GPA while the mean for bought lunches was 3.3 GPA. The 50% of students who packed lunches had GPA’s above 3.6 while those with bought lunches had GPA’s above 3.3. We can infer that students at Edison High School generally have higher GPA’s if they pack their lunches. There are a lot of lurking variables that are not accounted for such as study habits, classes, and socioeconomic background so the relationship of this study can still be falsely portrayed. Perhaps my next study can find the relationship of these other variables linked with GPA.
I have done a bit of analysis on my data and have come up with a few results. First of all, when I made a scatter plot with my data that used hours of sleep as an explanatory variable and weighted GPA as a response variable I did get a positive correlation as I had predicted. In context, this means that it was true that students perform better when they get more sleep. Unfortunately, my correlation coefficient was only .1874 which means my correlation is weak. I believe this to be because of the multitude of confounding variables such as student intelligence, effort put in by the student and what they do instead of getting enough sleep (for instance, if the spend the time studying this will help heir grades but if they stay up to watch Netflix that will hurt). I am attaching the scatter plot as well as a dot plot I made to show how many individuals said they thought they were getting enough sleep and how many thought they weren’t. In that plot, I assigned the number 0 to the response of no, and the number 1 to the response of yes. So it seems most students think they should get more sleep. I look forward to sharing my findings in class!
Survey Data – Sheet1
So here are the fruits of my labors! Out of my 76 responses, I only got one dubious answer. I don’t think anyone with a 0.0012 GPA is going to graduate from school any time soon. Most of the respondents had sandwiches for lunch be it that they packed or bought their lunches. I was surprised to see that a handful of people did not eat lunch at all but still managed to have an average of 3.0 GPA. Nearly 50% of all students surveyed packed lunch to school while only 34% bought their lunches. Maybe my next genius hour project could lead to finding ways to increase buying school lunches. I will have graphs, boxplots and scatterplots up soon whenever I can figure out how to make them. Then I will analyze the data and hopefully find if an association exists between my variables.
So yesterday on Thursday and Friday, I set up my survey during lunch. I decided on using a cluster sample with groups of 3 or more being the clusters. Due to the time limit, I had 2 of my friends also help me gather survey data. I ended up choosing about 20 groups of people and I ended up with around 76 survey results. I’ll post my survey results once I finish inserting into a program.
What grade are you in?
Do you usually buy school lunches or bring packed lunches?
What do you usually have for lunch?
What is your cumulative weighted GPA?
Other than that, I went to the cafeteria and got a list of all the meals on the menu and their semi-nutritional facts.
I have collected all of my data! In total, I have 58 responses after surveying the two classes. I have input the data into a google sheets spreadsheet but have not begun analysis of the data yet. I only received one survey with obviously “joke” answers and that explains the gap at survey #35 (this person said they had a 69 GPA and got “Deez Nuts” hours of sleep per night…). An interesting fact from a brief look at the data is that 48 out of 58 individuals said they feel like they don’t get enough sleep to perform their best in school. Perhaps an interesting project for next quarter would be finding reasons for students getting less sleep than they know they need (for example, do most students spend these should-be sleep hours doing extracurricular activities, hanging out with friends or simply doing schoolwork). Anyway, I am hoping to make a few graphs including scatter plots and histograms to show various correlations that appear from my questions.
Here is a link to the google sheets document:
Student Sleep Survey Responses
The hope for my project is that our school library can have a more recent collection of books readily available for all Edison student to use. Here’s a summary of the current age distribution in the large book section in our school library:
Total number of large books:1114 Mean:1992 Max: 2011 ~ First Quartile:1999 ~ Median:1995 ~ Third Quartile:1988 ~ Min: 1941
The goal is to get the mean to at least the year 2000!
Have you ever heard the saying “You are what you eat?”. Well lucky for you since my Genius Hour project is a data analysis design which might help you solve this question.
For my Genius Hour Project. I will be examining the whether buying your lunch at school or packing a lunch from home has an association with having good grades at school.
I hope to find an association somewhere that reinforces whether packing lunch can reinforce good study habits and time management or if buying lunch can save more time overall and have more time for studying.
I intend to conduct my survey tomorrow and analyze the results of my observational study to see whether this project was a success or not. I am planning on taking a stratified random sample where the strata are people with bought vs. packed lunches and see whether certain lunches can have more of an effect on one’s GPA
I will most likely construct scatteplots to track the association between alcohol use and marijuana use and GPA, but I do believe that I won’t have enough time to present 8 scatterplot, 2 for each grade. Therefore I am seeking advice on which grade(s) to focus on. I will either purely focus on Seniors and may expand on my survey then or I will focus on Seniors and Sophmores because that is the earliest grade which I can get an actual cumulative GPA, and then I can still evaluate/analyze the differences between the two age groups.
What grade are you in?
A number scale for usage rates:
1= once or twice in my life
2= a few times a year
3= once a month
4= a few times a month
5= once a week
6= a few times a week
7= almost every day
8= every day
9= multiple times a day
Knowing the scale above how would you rate your use of alcohol. If applicable place your usage rate between two numbers, to the first decimal place, to be as accurate as possible. For example a 5.3 would indicate a usage rate between 5 and 6, but slightly more accurately defined by the usage rate associated with the number 5.
Your number here:
Now rate your use of marijuana using the same process and scale:
Place the most accurate GPA you are able to give here:
For my project I will be evaluating the presence of alcohol and marijuana use at our school and its association with grades and grade level. I am going to come up with a sample survey to do so and I will try to quantify people’s usage rates of these substances with a number scale and then ask them for their cumulative GPA. Overall the purpose for my project is to understand the situation and to invoke possible further action in more projects or solutions. I am currenlty coming up with the number scale and survey and will probably post both of them later today.