anova-test
There are 1 repository under anova-test topic.
- Language:Python 14
Statistics-and-Machine-Learning-with-R / Statistical-Methods-and-Machine-Learning-in-R
This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.
Language:R 13edaaydinea / OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).
Language:Jupyter Notebook 12pleonova / stat-tests
A 30+ node flowchart for selecting the right statistical test for evaluating experimental data.
raj-shr-git / Statistical_testing_python
This repository is created for storing the components of Statistical Tests of One Pop, Two Pops and Three or more pops using Python.
Language:Jupyter Notebook 10gnu-octave / statistics-resampling
A statistics package with a variety of bootstrap and other resampling tools
Language:MATLAB 9Praveen76 / ANOVA-Test-COVID-19
In this repository, discover the intricacies of the ANOVA test and its various types, essential for informed decision-making. Dive into practical demonstrations of each ANOVA test using Python, with a focus on visualizing their application on COVID-19 data. Let's embark on a journey to explore and understand statistical analysis in Python!!
Language:Jupyter Notebook 6DataSpieler12345 / python-for-ds-ml
My Python learning experience 📚🖥📳📴💻🖱✏
beautifulsoupmatplotlib-pyplotnumpy-librarypandas-libraryscipysckit-learnseabornscikitlearn-machine-learningmachine-learning-algorithmsanova-analysismonte-carlo-methodst-distributionanova-testmatplotlibrandomforestclassifierrandomforestregressorpolynomial-regressionridge-regressionlasso-regressionnltk-pythonLanguage:Jupyter Notebook 5SahilJatoi744 / DS
DataScience
Language:Jupyter Notebook 4sashahafner / CCPDA
This short free book provides a concise introduction to data analysis meant to address common problems faced by graduate students in engineering and science.
Language:TeX 4MoinDalvs / Assignment_Hypothesis_test
A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validity of the assumptions.
Language:Jupyter Notebook 3acpennlab / statistics-resampling
A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.
Language:MATLAB 2- Statistics_Multiple-Mean-Comparison_ANOVA_and_Non-Parametric-Tests
David-B3 / Statistics_Multiple-Mean-Comparison_ANOVA_and_Non-Parametric-Tests
Perform a STEP by STEP multiple mean comparison analysis on R
Language:R 2 narjesno / Statistical-Inference
This repository contains all of the statistical Inference-related projects I've worked on. The projects are part of the graduate course at the University of Tehran.
Language:R 2- Language:Jupyter Notebook 2
aldimeolaalfarisy / Hypothesis-Testing-Concept-ANOVA-
ANOVA test using python to find out if survey or experiment results are significant and the impact of one or more factors by comparing the means of different samples
Language:Jupyter Notebook 1ankit-verma2000 / Business-Case-Yulu
This project analyzed factors affecting the demand for shared electric cycles in the Indian market. Using EDA and hypothesis testing, I found no significant effect of "working day" on rental count but confirmed that seasonality influences demand. The insights provide valuable guidance for optimizing shared cycle availability.
Language:Jupyter Notebook 1astonglen / Statistical-Methods-Project
Performed rigorous preprocessing, and data cleaning, and conducted exploratory data analysis to identify trends, patterns, and outliers, leading to valuable insights. Employed various statistical methods concepts to get insights about the data for prediction.
Language:Jupyter Notebook 1BoiniGanesh / DATS_6101_11_Team3
This project aims to analyze a dataset of sales transactions from a UK-based e-commerce store specializing in gifts and homewares over one year. With 500,000 rows and 8 columns, including transaction numbers, dates, product details, prices, quantities, customer identifiers, and countries, the analysis focuses on understanding customer behavior
Language:HTML 1datagirlz19 / Predict-Emerging-Data-Scientist
What are the odds of “success” in data science for people who use different platforms, languages, and software?
debanikchakraborty / Multiple-Linear-Regression-on-Bike-Rental
Applied MLR with 5-year bike rental data, incorporating model diagnostics, hypothesis testing, ANOVA and step-wise AIC, identified a significant impact of winter rainfall variation.
Language:R 1- Language:Jupyter Notebook 1
Honey28Git / Advanced-Statistics
This study delves into the intricate dynamics between salary, education, and occupation, employing both one-way and two-way ANOVA techniques to uncover their relationships. Additionally, it explores the multifaceted dataset on colleges through Principal Component Analysis (PCA).
Language:Jupyter Notebook 1Kishawn-Dorman / Student-and-Client-Satisfaction-Report
first business data analysis - factors affecting student satisfaction and bank clients
Language:R 1manjit-baishya-datascience / NYC-Taxir-Fair-Prediction
This project aims to predict taxi fare amounts in New York City using a dataset of historical taxi rides. We employ machine learning techniques to create models that can estimate the total fare amount based on various features of the trips.
Language:Jupyter Notebook 1TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5% significance level and help the manager draw appropriate inferences
Language:Jupyter Notebook 1A hospital wants to determine whether there is any difference in the average Turn Around Time (TAT) of reports of the laboratories on their preferred list. They collected a random sample and recorded TAT for reports of 4 laboratories. TAT is defined as sample collected to report dispatch. Analyze the data and determine whether there is any difference in average TAT among the different laboratories at 5% significance level.
Language:Jupyter Notebook 1Hypothesis for Data Science
Language:Jupyter Notebook 1naailrch / Alzheimers-Mental-Health-and-Healthy-Aging-Project
This project attempted to analyze if race and age had any effects on the frequency of mental health issues in older adults.
Language:R 1Quantum-Software-Development / Bovespa-Banks-Value-Analysis
This repository analyzes wealth distribution among Brazilian banks, highlighting disparities between national and foreign institutions.
Language:Jupyter Notebook 1ragztigadi / Hypothesis-Testing-in-Data-Analysis
Hypothesis Testing in Data Analysis This repository contains a Jupyter Notebook demonstrating various hypothesis testing techniques using Python. It covers statistical tests such as t-tests, ANOVA, chi-square, and non-parametric methods, with real-world examples and visualizations.
Language:Jupyter Notebook 1Risanaparvin00 / spss-projects
This repository contains an SPSS analysis project, performed to derive insights from the data while maintaining confidentiality. The repository includes an SPSS worksheet and a Word file summarizing the results.
RishiDarkDevil / Statistical-Inference-Functions
Implementation of Statistical Inference Concepts for learners.
Language:R 1ShaikRiyazSandy / Hypothesis-Testing
Hypothesis Testing
Language:Jupyter Notebook 1vanylush / Diabetes_Prediction_Model
Embark on a journey of data-driven insights with our diabetes research project. Leveraging Python's pandas, matplotlib, and scikit-learn, we preprocess, visualize, and analyze 330 health features. Employing logistic regression, decision trees, KNN, and SVM, we predict diabetes with precision.
Language:Jupyter Notebook 1- Language:Python 1
