Functions to analyse compositional data and produce confidence intervals for relative increases and decreases in the compositional components

Functions to analyse compositional data and produce confidence intervals for relative increases and decreases in the compositional components

Statistical model on NBA basketball players' performance using multiple linear regression and stepwise search.

Project using multiple linear regression to model prices of houses in Ames, IA.

Multiple Linear Regression (MLR) on Wave 6 of the World Values Survey (WVS) data

Descriptive Statistics and Regression Analysis on Used Vehicle Dataset.

Data: Boston Housing Dataset (HousingData.csv) Programming language(s): R Tool(s): RStudio Business problem: To understand the drivers behind the value of houses in Boston and provide data-driven recommendation to the client on how they can increase the value of housing.The Boston housing dataset consisted of 506 observations and 14 variables. P…

Now you can visualize dataset, fit the model without knowing any programming language

Assignments for Statistical Data Analysis course at UPM including performing statistical analysis, multiple linear regression, and time series analysis.

Time Series Model, Simple Linear Regression Model, Multiple Linear Regression Model, Polynomial Regression Model,Logistic Regression Model

Full machine learning practical with R.

Multi Linear regression to calculate HDI

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.

Implementing different flavors of Classification and Regression Machine Learning Algorithms on different datasets in the US region.

This repository contains coursework for the Data Mining course in the MS Applied Business Analytics program at Boston University.

Using a linear regression method, we build a model to determine the relationship between independent and dependent variable, and then predict the sales. In the process, we will use a statistical point of view for validation.

The purpose of this analysis is to help Mechacar's Manufacturing team to understand what car features impact car performance the most. The manufacturing team will incorporate the insights into the manufacturing process aiming to produce the best performing cars in the market, rebrand the company image, and regain market share.

Analyzing automotive production data to gather insights on production troubles for the purpose of assisting the manufacturing team.

Statistical analysis of a product prototype using R and tidyverse. Multiple linear regressions, statistical summaries, and t-tests are used for analysis and predictions. A study is also designed to compare this product to the competition.