Principles of Data Science (Semester 2, 2018/2019)
Save A Life! App by 4feet
Members :
Nurul Syafiqah Binti Md Khairi WQD180090
Sarah Nur Syaza Binti Mohd Yunos WQD180095
Nuraini Afiqah Binti Rohanip WQD180115
Nurfarhana Binti Omar WQD180089
This apps is about an analysis of suicide rates and its correlation with few factors below.
Data gathered from 2006 - 2015. All datasets obtained from :
We would like to investigate the factor(s) that contribute to suicide.
Once relevant data collected, we proceed with cleaning. This stage include filtering, imputation, remove duplicate values and etc. Once data is cleaned, we proceed with analyzing the data.
Once data is cleaned, we proceed with analyzing the data. We use Tukey - ANOVA analysis, which is an analysis tool used in statistics that could help us to check if the means of two or more groups are significantly different from each other.
From the algorithm, we can see the trends of suicide for each country and factor(s) contribute to it.
The app will have three main tabs labelled as Country View, Comparison View and Correlation.
Using Country View tab, we should be able to display suicide rate for each country based on year, age range and sex.
From Comparison View tab, we can show a comparison between country's suicide rate by year.Tukey-Anove test result is displayed on the right side of page.
Using Correlation tab, we can explore global correlations between suicide rates to several financial and climate factors.
There are some difficulties we encounter during the project:
Link to the app: https://4feet.shinyapps.io/Suicide_Rate_Worldwide/
Link for coding and other materials: https://github.com/sarahnursyaza/Suicide-Rates-Worldwide