Statistical analysis comparing metal accumulation levels in three macroinvertebrate groups
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Updated
Sep 26, 2017 - R
Statistical analysis comparing metal accumulation levels in three macroinvertebrate groups
Determined the best regression model which represents the data
Statistics on App usage data
DsFeatFreqComp – Dataset Feature-Frequency Comparison R Package
A repository created to explore and understand Statistics through coding.
Exploratory Data Analysis of the Pre-Election Polls of the European Election 2019 as well as an Evaluation of Their Predictive Power
Strategies for analyzing the distribution of datasets, switching the data towards a normal distribution testing different manual transformations and Box-Cox transformation.
Fundamental Concept for Hypothesis Testing, such as Parametric vs Non Parametric Statistical Tests , Various T-tests ,
Package for automation of statistics that are widely used in metabolomics.
This is a group project for MTH416A: Regression Analysis at IIT Kanpur
In this notebook, I applied statistical methods for imbalanced data analysis. In terms of basics, it starts with null check, data description and handling missing values. There exists right skewness in data for numerical columns. Shapiro-Wilk and Anderson darling tests are applied to prove that data is not distributed normally. Outlier detection…
The data relates to several user actions or interests recorded on two variants of landing pages for an online news portal. The objective is to analyse these interests by performing statistical analyses to determine if one variant is more effective based on chosen metrics (A/B testing).
Build a statistical model based customer satisfaction dataset from Qualtrics survey
Build personal music AI assistant
Easy statistical testing on the web
In this project, a regression-based performance prediction model was developed to estimate building energy consumption based on simplified façade attribute information and weather conditions.
Research on the topic 'Time Pressure'
This project aims to analyze the heart failure dataset to build a classifier that identifies the most important factors and allows predicting death from heart failure.
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