Quantrix
Chart Your Insight 2.0: Dataset and Submission Details
1.Age Category Vs Average BMI
We can infer what age group is having healthy BMI.
AGE Average
31
CATEGORY of BMI
18-24 26.00524 30
437
29
25-29 27.89631
987 28
30-34 28.58335
793 BMI 27
35-39 29.10648 26 Total
452
25
40-44 29.48070
85 24
18 25 30 35 40 45 50 55 60 65 70 75 80
45-49 29.81162
- - - - - - - - - - - - +
295 24 29 34 39 44 49 54 59 64 69 74 79
50-54 29.78927
442 Age Category
55-59 29.45828
581
60-64 29.19590
567 IDEAL SOLUTION: Between 18.5 and 26
– 65-69 28.84986 This is described as the 'healthy range'.
451 between 26.1 and 30 – This is
70-74 28.44673
022 described as overweight. between 30
75-79 27.88328 and 39.9 – This is described as obesity.
906
40 or over – This is described as severe
80+ 26.39648
736 obesity.
INFERENCE
18-24 Age group is the only age group which have good
health
No age group have over obesity
All the other age groups seemed to be over weight.
2.Age group Vs heart disease
We can infer what age group of people have more heart
disease
heart disease
Age No Yes
category
18-24 18587 94
25-29 15381 113
30-34 18227 201
35-39 20332 274
40-44 21160 435
45-49 20290 678
50-54 23916 1181
55-59 26063 1991
60-64 29406 3012
65-69 29611 3823
70-74 26542 4561
75-79 16953 3752
80+ 17415 4856
Grand 28388 24971
Total 3
INFERENCE
From the total sample of 308854 people, people who aged
above 80 are having more heart disease
People from age group between 40-44 to 80+ the count of
people with heart disease is increasing
3.Age group Vs People who exercise
We can infer what age group of people do more exercise
Age No Yes
category
18-24 269 1598
9 2
25-29 239 1310
0 4
30-34 301 1541
7 1
35-39 342 1718
4 2
40-44 386 1773
3 2
45-49 432 1664
7 1
50-54 538 1971
3 4
55-59 669 2136
2 2
60-64 801 2440
7 1
65-69 784 2558
7 7
70-74 795 2314
4 9
75-79 588 1482
4 1
80+ 797 1429
6 5
INFERENCE
From the total sample of 308854 people, people who aged
between 65-69 are doing exercise more than all the age
group.
People from age group between 25-29 are the count of
people who do less exercise.
4.Age group Vs People with depression
We can infer what age group of people have more
depression.
Age category No Yes
18-24 13893 478
8
25-29 11419 407
5
30-34 13863 456
5
35-39 15701 490
5
40-44 16728 486
7
45-49 16379 458
9
50-54 19686 541
1
55-59 22084 597
0
60-64 25718 670
0
65-69 27523 591
1
70-74 25946 515
7
75-79 17824 288
1
80+ 20189 208
2
INFERENCE
From the total sample of 308854 people, people who aged
between 60-64 are having more depression more than all the
age group.
People from age group above 80+ are the count of people
who have less depression.
5.Age group Vs People with skin cancer
We can infer what age group of people have more Skin
cancer.
Count of
Skin_Can
cer
Row No Yes
Labels
18-24 18626 55
25-29 15411 83
30-34 18294 134
35-39 20314 292
40-44 21095 500
45-49 20248 720
50-54 23856 124
1
55-59 25916 213
8
60-64 29129 328
9
65-69 28849 458
5
70-74 25262 584
1
75-79 15799 490
6
80+ 16061 621
0
INFERENCE
From the total sample of 308854 people, people who aged
above 80 are having more skin cancer.
People from age group between 40-44 to 80+ the count of
people with skin cancer is increasing
6.Age group Vs People with other cancer
We can infer what age group of people have more other
cancer.
Count of
Other_Cancer 35000
Count of cancer people
Row Labels No Yes 30000
18-24 18571 110 25000
20000
25-29 15308 186
15000
30-34 18084 344 10000 No
35-39 20064 542 5000 Yes
40-44 20865 730 0
45-49 20005 963 4 4 4 4 4 4 +
-2 -3 -4 -5 -6 -7 80
50-54 23577 152 18 30 40 50 60 70
0 Age
55-59 25784 227
0
60-64 28988 343
0
65-69 28801 463
3
70-74 25568 553
5
75-79 16295 441
0
80+ 17066 520
5
INFERENCE
From the total sample of 308854 people, people who aged
between 70-74 and 80+ are having more other cancer.
People from age group between 40-44 to 80+ the count of
people with other cancer is increasing.
7.BMI vs Fruit, vegetables, alcohol consumption and smoking
Using regression we can infer how these factors contributing
to BMI
I. Diagnosis of the model
The model is weak since r
square is just 2 %
II. Anova
Reject null hypothesis.
Atleast one factor is not zero.
III. T test
Each and every factors are contributing to BMI
INFERENCE
Surprisingly consuming fruit ,vegetables, alcohol and
smoking is negative effect over BMI.
8.BMI Vs heart and cancers
Diagnosis
The model is very negligible so we are not further processing
9.BMI Vs all other factors
Diagnosis
The model is 14% strong so we are going to find anova and also
find what are all other are contributing
Anova
Reject null hypothesis
So atleast one factor is not 0.
T test
Check up with the past exercise is the only thing which is not
contributing to BMI.
PARAMETER ESTIMATES are given below
From this we can infer that people who checked up before 5 years
is not at all contributing to evaluvate the health.
