General
My Current Level in Data Analysis
Before now i
use to think that Data analysis was a walk
in the park. Social media advertisers are more to blame for this impression i
had. you might want to ask me why i think so? Well, if you continue to scroll
through the streets of Instagram, LinkedIn facebook and google search engines,
you will see a whole lot of ads from online Tutors with the flyers
saying, ” become a certified data analyst in 3 months” some will even
promise you 2 weeks. The truth is, i have fallen for their scam ones. i paid
the fees. half way into the programme i started telling myself that this thing
is no for me. i quickly realized that data analytics isn’t a walk in the park.
About four months
ago, I thought I could rate myself a
7/10 in Excel, but my few months here in LBS has shown me that i am still very
far away from being a pro.
Professor
Francis has been kind enough to tell me to share my screen on two occasions.
honestly, this is the best form of learning because he is practically holding
my hand all the way. nothing beats this type of learning.
Here are
some of the tricks I know in excel
Pivot table,
correlation and regression, short cuts etc.
For
this article, i will be sharing the intricacies and problems the correlation
and regression analysis helps us to solve.
The word
correlation is used in everyday life to denote some type of relationship. We
also assume that the association is linear, that one variable increase or
decreases a fixed amount for a unit increase or decrease in the other. The
other technique that is often used in these circumstances is regression, which
involves estimating the best straight line to summarize the association.
The degree
of association is measured by a correlation coefficient, denoted by r. It is
sometimes called Pearson’s correlation coefficient after its originator and is
a measure of linear association. If a curved line is needed to express the
relationship, other and more complicated measures of the correlation must be
used.
The
correlation coefficient is measured on a scale that varies from + 1 through 0
to – 1. Complete correlation between two variables is expressed by either + 1
or -1. When one variable increases as the other increases the correlation is
positive; when one decreases as the other increases it is negative. Complete
absence of correlation is represented by 0.
The relationship can be positive, negative or perfect.
Depending on how close the value is to 1 determines
the strength or weakness of the relationship.
Now this can be calculated manually, but excel has
automated functions that makes it very easy to run.
If your skills in excel is not sharpened, there is no
way to correctly apply the formular and procedures to get the accurate readings
and analysis.
I am still a work in progress. I will be penning down
my progress from time to time on my progress on data analysis.
#mmba4
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