Weight-Height
Correlation: A
Statistical Analysis
SLE Group – A2
Ansh A Agarwal – HBFC008
Gautam R Agarwal - HBFC009
Mohit S Agarwal - HBFC010
Ansh D Agrawal - HBFC011
Chhavi M Agrawal - HBFC012
Nityam S Agrawal - HBFC013
Sneha Y Agrawal - HBFC014
“There are three kinds of lies:
lies, damned lies, and
statistics.”
—Mark Twain
TABLE OF CONTENTS
01
03
Introduction
Brief Intro to the
definations required to
understand this project
02
Data Collection
The process which we
used to collect data
Calculating the Correlation Coefficient
The Formulas Used and Analysis conducted to obtain the
coefficient
TABLE OF CONTENTS
04
06
Results
What we understand from
this analysis
05
Conclusion
Our Conclusion to this
presentation
References
The Articles, Websites and books that we refered in order to make
this presentation happen
01
INTRODUCTION
INTRODUCTION
Karl Pearson's correlation coefficient is a powerful tool for
analyzing data sets. In this project, we will use this coefficient to
investigate the correlation between height and weight of a sample
of 150 people.
We will use the coefficient to measure the strength of the
relationship between the two variables and to determine if there is
a correlation between them.
DATA
02 COLLECTION
The methods that we used
to obtain data for this
analysis
Data Collection
The data for this project was collected from a sample
of 150 people. Each person was asked about their
weight and height. If they did not know it themselves
our surveyors did a little measurement and give their
best estimates.
The data collected from both google form and
physical survey was then organized into a singular
data set, which was used to calculate the Pearson
correlation coefficient.
Means of Collecting Data
Google Forms
Physical Survey
Google forms, is an online forms
platform developed and owned
Alphabet Inc. that allows people to
easily conduct surveys with thousands
of participants with great ease
Since, We felt like that the data
we obtained on google forms was
not just not enough. So, a few of
the members of our group, went
into the field and collected data
using a pen and paper
questionnaire
Preliminary Facts
about the Data
Gender Ratio
Age Ratio
03 CALCULATION
How the correlation
coeffiecient was calculated
Important Formulas
Karl Pearson’s Coeff.
2nd Formula for it
Covariance
Standard Deviation
Working of the Calculation
The correlation coefficient was calculated using Karl
Pearson's correlation coefficient formula. This
formula uses the data set to calculate the strength of
the relationship between the two variables.
First the sum of deviations from mean of all the
values of weight and height is individually calculated.
In the denominator, the sum of the absolute values
of the deviations of both the variables are multiplied.
In the denominator, the root of the product of the
sum of both variable’s squared deviation is taken.
Working of the Calculation
Extract of data
04
Results
What we can understand
from this analysis
From our analysis we can conclude that
There Is An Extremely
Close correlation between
Height and Age
0.980206
Is the Karl Pearson’s Coeffiecient of Correlation for this
data set
414.56
Is the Covariance
21.25 Cms
Is the Standard Deviation of Height
19.903 kgs
Is the Standard Deviation of Weight
05 CONCLUSION
Our Conclusion to this
presentation
Conclusion
●
●
We Can conclude through this data that in the
sample population of 130 that we surveyed,
height and weight are extremely closely
correlated.
But we must be aware that the data set we
used contained mostly males that are between
the ages of 26-40, so they may not completely
representative of the general population
06
REFERENCES
The Articles, Websites and
books that we referred in
order to make this
presentation happen
References
Here’s an assortment references that we used to put this presentation together.
Wesbites
●
●
●
●
https://www.khanacademy.org/math/statistics-probability/describing-relationshipsquantitative-data/scatterplots-and-correlation/a/correlation-coefficient-review
Investopedia. (n.d.). Correlation.
https://www.investopedia.com/ask/answers/032515/what-does-it-mean-if-correlationcoefficient-positive-negative-or-zero.asp
Statisticshowto. (n.d.). Correlation coefficient.
https://www.statisticshowto.com/probability-and-statistics/correlation-coefficientformula/10.
NIST/SEMATECH e-Handbook of Statistical Methods. (n.d.). Correlation.
https://www.itl.nist.gov/div898/handbook/eda/section3/eda35c.htm
References
Papers And Textbooks
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Pearson, K. (1895). Note on regression and inheritance in the case of two parents.
Proceedings of the Royal Society of London, 58(347-352), 240-242.2.
Pearson, K. (1901). On lines and planes of closest fit to systems of points in space.
Philosophical Magazine, 2(11), 559-572.3.
Pearson, K. (1909). On the criterion that a given system of deviations from the probable in
the case of a correlated system of variables
Manan Publications (2022). Mathematics and Statistics for Second Semester of Bachelors
of Commerce
Spiegel, M. R. (1999). Theory and problems of statistics (4th ed.). New York: McGraw-Hill.
THANK
YOU!!