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A combination of codes developed for the calculation of the cross-correlation confidence intervals, making use of a pair of light-curves. The code conducts a bootstrap random sampling with replacement method to generate artificial light-curves. The code determines the cross-correlation of the artificial light-curves, and uses them for significance.

License: MIT License

Python 13.96% Shell 0.78% Fortran 85.25%

bootstrap_resample_with_replacement's Introduction

Hi 👋, I'm Tekano Mbonani

A passionate Data | Statistical | Quantitative Analyst from South Africa

Enthusiastic about merging data insights with the realm of education, I'm currently a Jnr Data Analyst, incharge of everything data related for the Academic Student Tutorial and Excellence Programme (A_STEP) at the Centre for Teaching and Learning (CTL), University of the Free State. Armed with a Bachelor of Science (BSc) Honours degree in Astrophysics and currently completing my Master of Science (MSc) in the same field, I bring a dynamic blend of academic knowledge and practical expertise to the table. My role encompasses selecting and applying advanced statistical methodologies, crafting robust research proposals, and translating intricate data into actionable insights. By doing so, I actively contribute to refining project outcomes and facilitating well-informed decision-making through data.

Additionally, I am a Lecturer and a Researcher. In my previous role, I was a Teaching Assistant for the first entry level modules UFSS1514 and UFSS1526, at the University of the Free State. I have also been a Student Assistant, a Tutor, as well as a Research Assistant at CLT and the Deparment of Physics, University of the Free State.