Suicide is a complex and devastating phenomenon that has far-reaching impacts on individuals, families, and communities worldwide. Despite significant efforts to increase awareness and prevention, suicide remains a serious public health issue. The aim of this study is to investigate the correlation between sex, location, and time period and suicide rates in the global population in the hopes of providing insights to the public and possibly contributing to the mental health community. To accomplish this, we will use R for data cleaning, data analysis, and statistical correlations, use Pearson correlations to find to detect correlation, use ARIMA prediction model to predict trends, visualize data using R and Tableau and utilize Tableau and R pubs to publish the findings. Our ultimate goal is to publish our findings to share the analysis with others in the hopes of contributing to the development of more effective suicide prevention strategies and policies. Before the start of this study, we assume that There was an uptrend in the suicide rate, there was no correlation between suicide rate and gender, and all countries or regions are equally impacted.

This study aims to investigate possible correlations that may contribute to suicide rates such as Sex, location, and time period.

This study aims to investigate possible correlations that may contribute to suicide rates such as Sex, location, and time period.

This is a case study focused on the possible correlation between suicide with regard to Gender and location. Please note that the values are age-standardized per 100000 population. based on the most recent Data from WHO. This study also aims to know if there is an increase or decrease in the recorded global suicide rates.