Introduction

Hi there, my name is Drew and this blog will feature some of my data analysis and analytics. So before reading any of my post, I would like to make some disclaimers. 

-  All data extracted for all my post are from an open source

- All my analysis and analytics are done based on my own interest at my own free time, I do not perform any of these for anyone or any organization.

- All my post are also done objectively with no harmful intention to anyone or anything. 

Any feedback to any of my post to help me to improve my skills or methods that I have performed incorrectly is welcome, I am here to learn too.  

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1. Post Secondary Education

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  In Singapore Education system, a child usually goes through nursery education at the age of 4, kindergarten at the age 5 t0 6, primary school from age 7 to 12, secondary school from 13 to 16 or 17 depending on their stream, and proceed to post-secondary education, be it Polytechnic, Junior College (JC) or  Institute of Technical Education (ITE) or they might start working.  This data set I obtained from data gov Singapore consist a set of primary school student’s data:  - Year: The year the student educate in  primary 1 - Race: The race of the student - Percentage of P1 Cohort, the percent of the cohort that went on to post-secondary education.  This short analysis is to provide a regression analysis to predict the percentage of the cohort’s entering post-education.  We first import the data into Python. There are 120 rows in this data with 3 columns. Each year has 5 rows, 4 consisting data with individual race and 1 with the overall (Race= ‘Al...
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