There are 1 repository under anova-analysis topic.
Introduction to statistics featuring Python. This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand.
Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.
End-to-end marketing and business analysis projects utilizing machine learning and statistical analysis techniques using the R programming language.
My Python learning experience 📚🖥📳📴💻🖱✏
about statistical techniques for Data Science
Residual analysis in Linear regression is based on examination of graphical plots which are as follows :: 1. Residual plot against independent variable (x). 2. Residual plot against independent variable()y. 3. Standardize or studentized residual plot 4. Normal probability plot
Perform a STEP by STEP multiple mean comparison analysis on R
Projet pour une banque présente dans plusieurs pays, l'objectif est de cibler les prospects les plus susceptibles d'avoir, plus tard dans leur vie, de hauts revenus.
This problem concludes which factor is significantly effecting the CAT Score out of College type,program type,and interaction factor type for sample data. Here factorial Experiment design and Two Way Anova is used.
For this Project, I first applied an analysis of variance (ANOVA) model to the Pymaceutical dataset and then did a post-hoc analysis of the results by using Tukey Honest Significant Difference (HSD) to determine which drug treatments in the dataset significantly reduce tumor volume and metastasis. I then wrote a summary of my findings.
This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.
Tutorials for BSE classes.
A few statistical methods appropriate for applications in the biological and social sciences.
Econometrics project that aims to analyze the relationship between Reservoir Water Level and various Power Inequalities in different states of India.
Here I have collected two scripts written in Python and SQL, designed for analyzing data related to physiological parameters derived from experimental measurements. These tools were created to expedite the statistical analysis process, extracting and sorting data from tabular-format datasets, in my specific case studies.
Se realiza un análisis estadístico descriptivo de datos obtenidos en 3 viñedos diferentes con el objetivo de encontrar diferencias y relaciones entre las variables medidas, para concluir las características del vino de cada viñedo.
Executed Regression modelling, hypothesis testing and statistical analysis to predict factors affecting credit card balances in a firm. Tools & technologies: ANOVA, p-value, R square
Data for publication on how juvenile house crickets adjust adult calling songs and aggressive behaviors based on developmental exposure to population density, potentially adopting alternative mating tactics to maximize success in varying social environments.
CROWN PROSECUTION SERVICE CASE OUTCOMES BY PRINCIPAL OFFENCE CATEGORY (POC) DATA ANALYSIS AND VISUALIZATION REPORT
Regression models for predicting customer acquisition costs (CAC) and the effectiveness of univariate and lasso feature selection techniques in improving the accuracy.
Exploratory Data Analysis in R on UN Happiness Report and World Bank Metrics from 2019
Gain hands-on experience with ANOVA analysis, understanding its assumptions, and applying it to real-world datasets to understand differences among group means.
See Readme.md
The data, R programming, and outputs for the research paper testing glucose consumption and cognitive factors. I used R to clean, process, model, and visualize the data. The outputs folder contains the finished products. Link to paper pending.
Regression | Analysis | Modelling | Bayesian Search CV | Data Leakage | Overfit/Underfit | End-to-End Project
This Design of Experiments (DOE) study for SCM 517 optimizes a Lego race car’s performance by analyzing the impact of tire size, windscreen size, axle length, and car slant. Using Minitab, factorial design, and statistical analysis, the project identifies the optimal configuration for maximizing travel distance.
Analytics performed on the fisher iris dataset
Diabetes Classification Using KNN Model
This repository contains R projects focused on statistical analysis, using techniques like EDA, Hypothesis Testing, ANOVA, Normalization, and Linear Regression. Each project includes datasets, R scripts, results (plots, tables), and a detailed README for insights and methodology.
Shiny-Based Statistical Solutions for Agricultural Research
Explore multivariate statistics through hands-on university projects. Each project delves into real-world datasets, applying statistical techniques like ANOVA, two-factor analysis, and binary logistic regression. Understand data analysis, interpretation, and modeling with R.