A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Data Science Foundations II | Statistics Fundamentals for Data Science | Hypothesis Testing for Data Science

Statistics for Data Analysis | Sample Mean vs. Population Mean and P-Values

Analysis platform for large-scale dose-dependent data

Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t

Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.p

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

Q1.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 validit

python module, showcasing computation (as part of a learning process) of some common statistical methods including mininum sample size, confidence interval estimation methods for mean or proportion, hypothesis testing mehods and regression models witth metrics and test suites

pMoSS (p-value Model using the Sample Size) is a Python code to model the p-value as an n-dependent function using Monte Carlo cross-validation. Exploits the dependence on the sample size to characterize the differences among groups of large datasets

This aim of this project is to analyze globular star clusters in the Milky Way, in order to understand their dynamics. The conducted study examined the properties that affect the central velocity dispersion, their impact and the correlations between them.

Pharmaceutical company Sun Pharma

Logistic regression in R

Lean Six Sigma with Python — Kruskal Wallis Test

📋 List of practical works from Technologies and Tools for Big Data Analysis subject from university

Time Series Classification Part 2 Binary and Multiclass Classification. An interesting task in machine learning is classification of time series. In this problem, we will classify the activities of humans based on time series obtained by a Wireless Sensor Network.

🎯 Customer behaviour and sales analysis for a national bookstore library willing to adapt its digital vs. instore strategy - use of Python and JupyterLab (Business insights, Data collection, Cleaning, EDA, Market Segmentation, Time Series analysis, Statistical tests and Data Visualization)

Statistical Analysis of Insurance premium data