Using boxplots to investigate US hospitals healthcare costs
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Updated
Feb 7, 2023 - Jupyter Notebook
Using boxplots to investigate US hospitals healthcare costs
The Following problems showcase different Statistical Methods used for Decision Making. The purpose of this project is to experiment and execute statistical methods, which are required to conduct data analysis, derive insights and inferences and arrive at business decisions.
This repository includes all the assignments completed for the IDS702: Modelling & Representation of Data at Duke MIDS program.
Using pandas and numpy to explore London weather data to find the best time to visit.
Using matplotlib to look at distributions of flowers and flights to plan a trip.
collection of Jupyter Notebooks in both English and Spanish, dedicated to performing data quality analysis using the R programming language
Summary of Assignment Two from the first semester of the MSc in Data Analytics program. This repository contains the CA2 assignment guidelines from the college and my submission. To see all original commits and progress, please visit the original repository using the link below.
[Statistics for Data Science] Data Science | Studi Independen | MyEduSolve X Kampus Merdeka
A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
This repository contains a collection of Jupyter Notebooks for conducting Exploratory Data Analysis (EDA) and Statistical Analysis on various datasets.
Statistics for Data Science Assignment
Statistics for Data Science Hackathon
Statistics for Data Science Assignment
WHO LIFE EXPECTANCY: Studying the factors that affect/contribute to life expectancy and analyzing the changes over the last 15years, that is between 2000-2015.
A simple data science project/hackathon done as part of SDS course
Statistics for Data Science Assignment
Excel calculating the probability distribution simulated data
Book of Demythologize Durbin-Watson Test Statistic | Correct the critical values of DW statistic
The R code authored below goes through cleaning, visualizing and modeling data as well as some useful simulations for concepts in Research Statistics and markdown reports. Some code is shell code for the participant to complete; some are examples of the completed shell code. For more advanced R methods, see Dashboards_DataScience repo
All Statistics concepts
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