statmodels
There are 0 repository under statmodels topic.
xxl4tomxu98 / econometrics-gdp-dpi-VAR
Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).
Language:Jupyter Notebook 9- Crop-yield-prediction
Hamid-abdellaoui / Crop-yield-prediction
Crop yield Forecasting on the basis of meteorological predictions using some Time series & ML models
Language:Jupyter Notebook 7 KentaItakura / blog-post-about-conjoint-analysis-
This repo contains files for the blog post about conjoint analysis
Language:Jupyter Notebook 7Emon-ProCoder7 / Data-Driven-Decision-Making-With-Statistics
My this project repository focused on hypothesis testing involving T-test, Chi-square test, Binomial Test, ANOVA, Sample Size Determination with scipy, statmodels modules.
Language:Jupyter Notebook 1nick-gould / design-of-experiments
Using Python to work up a Design of Experiments
Language:Jupyter Notebook 1philsaurabh / Tutorials
Tutorials for BSE classes.
Language:Jupyter Notebook 1shanuhalli / Assignment-Basic-Statistics-Level-1
ExcelR Data Science Assignment No 1
Language:Jupyter Notebook 1ExcelR Data Science Assignment No 2
Language:Jupyter Notebook 1Forecast the Airlines Passengers and CocaCola Prices data set. Prepare a document for model explaining. How many dummy variables you have created and RMSE value for model. Finally which model you will use for Forecasting.
Language:Jupyter Notebook 1ExcelR Data Science Assignment No 3
Language:Jupyter Notebook 1Prepare a prediction model for profit of 50 startups data and Consider only the some columns and prepare a prediction model for predicting Price.
Language:Jupyter Notebook 1Predict delivery time using sorting time and Build a prediction model for salary hike.
Language:Jupyter Notebook 1BECHEUR / Detection_de_faux_billets
Explorer, nettoyer et analyser pour effectuer une modélisation des données
Language:Jupyter Notebook 0ChangZero / Hyundai_Heavy_Industries_DT
업무프로세스 개선을 위한 관리자의 의사결정 프로그램(현대중공업 DT 프로젝트)
Language:Jupyter Notebook 0DelRene / Detecteur_de_faux_billets
Apprentissage supervisé : Création de modèles prédictifs
Language:Jupyter Notebook 0dennyalp / Statistics
Exploration of descriptive and inferential statistical methods using Python and Jupyter Notebook.
Language:Jupyter Notebook 0- Language:Jupyter Notebook 0
Fuenj / E-commerce-Performance-Optimization-with-AB-Testing
Analysing the results of an A/B test run for an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.
Language:HTML 0HayaAlmutairi / A-B-testing
Tried to understand whether the company should implement a new page or keep the old page with some statistical techniques.
Language:HTML 0izharul-haque / Boom_bikes_case_study
Created model using Linear regression to predict variables impacting demand.
Language:Jupyter Notebook 0kamileyagci / project-house-sales-prediction
Multiple Linear Regression Study to predict King County House Sale Prices
Language:Jupyter Notebook 0nihar-phadnis / Time-Series-with-ARIMA
Time Series forecasting using Seasonal ARIMA. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots. Transformed series to make it stationary
Language:Jupyter Notebook 0PatilSukanya / Assignment-04.-Simple-Linear-Regression-Q1
Used libraries and functions as follows:
Language:Jupyter Notebook 0ZeyadMoawad / Udacity-Analyze-A-B-Test-Results-Project
Udacity Data Analyst Nanodegree - Project III
Language:Jupyter Notebook 0abouchard-ds / STL_TimeSeries_Anomaly
Implementation of an anomaly detection algorithm using "Seasonal and Trend decomposition using Loess"
amruta33 / Telecom-Churn-Case-Study
Building a classification model for reducing the churn rate for a telecom company.
Language:Jupyter Notebook- Language:Python
Model created using Logistic Regression to identify potential leads
Language:Jupyter Notebook
