How history shows lots of autoimmune diseases

In this project, I am choosing to collect data regarding student’s nutrition and
concentration levels and see how that affects their GPA. I chose this topic because I am highly
interested in how nutrition affects our lives not just daily but also in the long run. Personally, my
family history shows lots of autoimmune diseases and because of that in the last two years I have
turned vegan to ensure what I gave my body would help it stay healthier and avoid such diseases
in the future. I noticed changes to my lifestyle and habits, and I was wondering if other students
experienced such or if there is a correlation to nutrition and GPA. The quantitative variables i
focused on were weight, height and GPA. The categorical variables were their concentration
levels on a scale of 1-5, where their main food source was, if they considered themselves healthy
eaters or not, if they followed a certain food diet or not, and if the students personally connected
their concentration levels with their nutrition.
The targeted audience for my survey were college students from Nazareth College. I
focused on this population because it was the only population available to me, and a population
that included students of similar lifestyles to mine so I could also compare how I fit in the data. I
hypothesized that students who ate their own food or followed a diet would be better focused or
have achieved higher GPAs. My hypothesis comes from my own experience, having to follow a
diet and cook alone with a budget or so made me plan a lot more throughout my day, and I
believe that extra planning somehow made me focus better on their classes.
I collected data from multiple buildings on campus, they are: Peckham Hall, GAC, Library,
Smyth Hall and Shults Center. I collected 10 responses per day (Monday-Thursday), two
responses from each building on those days, and these two students were the seventh persons to
walk in the building.
t #
on Level in
What is
Which of
diets do
Do you think
your nutrition
affects your
1 175 62 32.
3.5 5 Yes Own None Yes
2 150 65 25.
4 1 Yes Naz
Other Yes
3 182 73 24.
2.2 5 No Own None Yes
4 190 67 29.
3.2 4 Yes Own Keto Yes
5 230 73 30.
2.3 3 Yes Take
None No
6 138 68 21.
3.2 3 No Own None Yes
7 155 72 21.
3 3 No Own None Yes
8 155 70 22.
4 1 No Own None No
9 120 67 18.
3 2 Yes Own None Yes
10 176 68 26.
3 5 No Own None Yes
11 205 61 38.
3.5 1 Yes Naz
None No
12 198 62 36.
2.3 5 Yes Naz
None Yes
13 213 69 31.
3.75 3 Yes Take
None Yes
14 115 63 14. 4
3 No Own None Yes
15 170 74 21. 8
2 No Take
None Yes
16 172 69 25. 4
1 No Own None Yes
17 200 72 27. 1
4 Yes Own None Yes
18 220 76 26. 8
3 No Naz
Vegetaria n
19 175 71 24. 4
4 Yes Own None No
20 112 61 21. 2
3 No Naz
None Yes
21 135 65 22. 5
5 Yes Naz
None Yes
22 147 66 23. 7
4 Yes Own None Yes
23 136 62 24. 9
1 Yes Own None No
24 180 68 27. 4
2 No Naz
None Yes
25 174 67 27. 2
5 Yes Naz
None Yes
26 186 73 24. 5
5 No Own Other No
27 135 64 23. 2
3 No Take
None Yes
28 188 76 22. 9
3 No Naz
None Yes
29 122 63 21. 6
3 Yes Own Vegetaria n
30 116 61 21. 9
5 Yes Own None Yes
31 178 72 24. 1
1 Yes Own None Yes
32 132 67 20. 7
3 Yes Naz
None No
33 156 68 23. 7
4 No Naz
None Yes
Analysis of Individual Variables
Quantitative: BMI
Since my study is to find whether there is a correlation between nutrition and concentration
levels, the best way to evaluate someone’s nutrition is through calculating their BMI (Body Mass
Indicator). The BMI is a person’s weight in kilograms divided by the square of their height in
centimeters, this tells us whether someone’s weight is in healthy proportion to their height. I
consider this to be my most accurate indicator of someone’s health in terms of weight and height,
as it is based on actual data and not thoughts or feelings. I suppose one could acquire a healthy
BMI but have a poor nutritional diet, but that would still mean that they’re either exercising or
have a fast mode metabolism or some sort of compensation. That is why I have included the
question of whether the individuals would say they are healthy eaters.
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 14.0 21.5 24.4 25.1 27.1 38.4
34 172 69 25.
3.5 2 Yes Own None No
35 183 68 27.
3.3 5 Yes Naz
None Yes
36 220 74 28.
2.5 1 Yes Own None Yes
37 138 66 22.
4 3 No Own None Yes
38 176 69 26.
2.7 3 No Take
None Yes
39 112 63 19.
2.8 3 Yes Own Vegan Yes
40 180 72 24.
3 4 Yes Own Vegan Yes
The mean was at 25,
which according to the
BMI chart is the first
c o l u m n i n t o t h e
overweight section. I
honestly expected that due
to our generation being
more prone to being
overweight in comparison
to older generations,
however it is just one
column in. The minimum
and maximum values
show us that there are
indeed some students who
f a l l u n d e r t h e v e r y
underweight category but
also the obese orange
section. No one was under
the extremely obese
section though from those who took
the survey. For some reason R
histogram wouldn’t work, but minitab
was really easy to make and to look at
and it shows us that the data is not
exactly skewed but if it were it would
be skewed to the left since most data
is on the right. Just as expected a lot
more people with bigger BMI than
lower. Interesting fact is that all
Vegans who participated in the survey
fall under the green healthy category.
Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum
BMI 40 0 25.015 0.719 4.545 14.400 21.975 24.400 27.175 38.700
IQR Rule:
There are two outliers that are in the obese category at points 36 and 38. Even though the mean is
at 25 which is at overweight, the median is at 24 which is considered healthy still. I honestly
thought I would have at least one outlier in the underweight categories but I guess not.
IQR 27 – 21 6
Q1-1.5(IQR) 21-1.5(6) 12
Q3+1.5(IQR) 27+1.5(6) 36
Categorical Variable: Does nutrition affect concentration levels?
My initial theory is that students with better nutrition acquire better planning skills than students
with poor diets, hence leading to higher concentration levels and higher GPA’s. However, I had
lots of peers who skipped on breakfast or ate fast food all day and concentrated fine, personally I
was raised to never leave house without breakfast and could not concentrate without it.
Therefore, I decided to ask the students participating in my survey the question of whether they
think their nutrition affects their concentration levels because who would be a better judge about
their own bodies than themselves. Not everyone was raised the same or in nearly same diets,
therefore this question really targets the essence of my investigation regarding nutrition and
concentration.As we can see over 3/4 of the student participating do think that their nutrition
concentrates their level of concentration.
Again, just want to highlight that
this is what they think, it could be
that for those who said no the truth
is that their nutrition affects their
concentration but they just don’t
know it. So it is interesting how
one can take these results and think
about its true indication.
Nutrition affects concentration count percentage
Yes 9 22.5%
No 31 77.5%
Analysis of relationship between variables
Quantitative vs Quantitative
I am going to look at the relationship between height and weight. Since to me, people in America
are completely of a different demographic than I am used to, I feel like everyone here is super
tall compared to back home in the Middle East. Height adds on to the weight so when my peers
here tell me about their weights the numbers feel a little larger. So for me to discover whether
that is extra weight or normal healthy weight I have decided to analyze these two quantitative
variables together. I expect that the taller someone is the larger their weight should be, hence a
positive association in the scatterplot with a positive slope in the equation of the regression line.
As we can see the two variables
are positively correlated. The
0.077 value which is moderately
positive indicates how moderate
the two variables are correlated.
Simple Linear Model
the y intersect, 149.8105, is the
value equal to weight when height
is zero. The slope coefficient
0,2356 indicates the value weight
will increase if there is unit change
in height.
The coefficient of determination is
�2 = �2 =correlation2 = (0.077)2 =
0.5929% if the total variability in
weight is explained by this linear
regression with height.
Quantitative vs Categorical
I am going to look at the
relationship between weight
and if the students thought
their nutrition affected their
concentration. Since to me,
people know how their bodies
best and not what one person
does applies to everyone.
Personally, I have never left
the house without breakfast,
and if I fast I tend to eat more
and gain more weight. So I
believe putting these two
variables next to each other
will show if other students see
any true difference between their weight and their thoughts.
This box plot shows us that the median weight for each case is about the same, the only
somewhat significant difference is within the outliers. People who thought their nutrition did not
affect their concentration had outliers on the further end of the weight scale, whereas people who
thought their nutrition affected their concentration had outliers who weighed less than those who
thought otherwise. I think in the end, if you are someone who is at 120lbs trying to get to 115lbs
then the difference is a lot and you might want to consider that yes your nutrition matters and
affects your weight as you will present behavior according to that thought. However is a
difference of 5lbs doesn’t matter to you then there isn’t much of a difference at all.

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