GitHub topics: ols-regression

Repositories

shanuhalli/Assignment-Simple-Linear-Regression

Predict delivery time using sorting time and Build a prediction model for salary hike.

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fszymanski13/FIFA22-analysis

Determinants of the player's overall score in FIFA22

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imnikhilanand/Bayesian-Marketing-Mix-Modeling

The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression.

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adrian-io/pisa-clustered-ols

Prediction of all countries’ PISA scores with macroeconomic indicators using pooled OLS with clustered standard errors

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luke-davidson/TimeSeriesMotionClassification

Semester project for my Machine Learning course: Classification of human motion through custom time series positional data shapelet transformations.

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ppanko/orthogonalize

R package for residualizing covariates

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ZJW-92/Linear_Regression_RED

This is a case study of RED company based on user data and consumption behavior data. It uses Python to build a linear regression model to predict the changes in the user's purchasing amount and find the factors that have a greater impact on users' purchasing amount. The linear regression effect of the data provided is not good and it is only used for practicing the linear regression.

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MoinDalvs/Simple_Linear_regression_2

Building a prediction model for Salary hike using Years of Experience

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svmiller/eh6105

Quantitative Methods (EH6105)

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JacobJ215/Premier-League-Regression-Analysis

Basic Regression Analysis

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ayush-vatsal/Linear-Regression-for-not-dummies

Everything Linear Regression captured in one repository. Implementation of Ordinary Least Squares Regression (OLS Regression) from scratch.

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daksh-intwala/House-Price-Prediction--Regression-Anaylsis

A simple regression analysis of house prices in USA with 11 features selected on MECE Framework

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calosor/ols_regression

OLS regression with possibility of controlling for fixed effects and robust standard errors

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ellaclauz/Adelie-and-Chinstrap-Penguins

Conducting simple linear regression on the penguins dataset

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PatilSukanya/Assignment-05.-Multiple-Linear-regression-Q2

Used libraries and functions as follows:

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PatilSukanya/Assignment-04.-Simple-Linear-Regression-Q1

Used libraries and functions as follows:

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manasik29/Prediction-model-for-profit-of-50_startups-data

Prediction model for profit of 50_startups data

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manasik29/Multi_Linear_Regression_on_Cars_data_to_predict_MPG

Multi_Linear_Regression_on_Cars_data_to_predict_MPG

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manasik29/Simple-Linear-Regression-Newspaper-Data

Feasibility of staring a Sunday edition for a large Metroplitan newsapaper

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manasik29/Aim-is-to-study-how-well-the-WC-area-predict-AT

Business Case : The Waist Circumference - Adipose Tissue

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manasik29/Prediction-of-Delivery-Time-of-newspaper-using-Sorting-Time

Prediction of Delivery Time of newspapers using Sorting Time

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manasik29/Prediction-of-Salary-of-individuals-based-of-Years-of-Experience

Prediction of Salary of individuals based on years of experience

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bvtvusn/Magnet-based-encoder

Encoder using magnetometer on Arduino nano 33 BLE

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Cyanjiner/peer-tutoring-program

This study used the data collected from Lehigh University's peer tutoring program which focused on 20 courses involving problem-solving skills over three academic years, 2003-04 through 2005-06. An OLS model and generalized liner mixed-effects models were used to measure effect of participation in tutoring in terms of hours spent getting tutored on exogenous final grade on subset of sample. Exploratory data analysis was performed to examine correlations between students' academic performance and other attributes including previous term GPA, high school rank, SAT scores, and demographic characteristics.

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MoinDalvs/Simple_Linear_Regression_1

Predicting Delivery Time Using Sorting Time

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MoinDalvs/Learn_Simple_Linear_Regression

Learn about Simple Linear Regression for Data Science

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TylerJSimpson/machine_learning_frameworks

Machine learning frameworks

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stnamjef/SimpleML

A simple machine learning library.

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Elliott-dev/NYC_Bike_Counts_Retrospective_Analysis

I perform a retrospective analysis on the linear regression analysis that I previously performed on the NYC Bike Counts dataset. Specifically, I analyze my linear regression analysis to identify anything that I could have done differently.

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Elliott-dev/NYC_Bike_Linear_Regression-

I used the New York Bike Counts dataset to formulate a hypothesis about the number of bikes crossing the Brooklyn Bridge. This dataset contains the number of bikes that crossed each bridge during each day. I first used this dataset to formulate a hypothesis and then used linear regression to test if my hypothesis was correct.

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anas-araid/supervised-linear-regression

supervised linear regression from scratch in javascript

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George-Nyamao/Inside_Airbnb

Predict prices and/or availability of airbnbs in Amsterdam with OLS and XGBoost

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marblehub/PV_projekt22

This is photovoltaic project designed to be conducted for some PV plants in 2022. Comparative analysis of OLS and WLS techniques are proposed with a view to better P_out predictions

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rfmmonteiro99/SfDS-Project-Final

Understanding the COVID-19 situation in the USA using Statistical Analysis

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KatoPachi/RCTtoolbox

A package of wrapper functions that are useful when analyzing data from randomized controlled trials (RCTs, especially with three or more treatment assignments)

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Ismail-therap/OLS-Regression-Analysis

Ordinary least square (OLS) regression analysis carried out in this project. The selected dependent variables are some public health indicators like anxiety, diabetes. We tried to find the independent variables which are responsible for this health hazard.

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jeevankande/Time-Series-and-Survival-Analytics

Time series forecasting occurs when you make scientific predictions based on historical time stamped data. It involves building models through historical analysis and using them to make observations and drive future strategic decision-making. An important distinction in forecasting is that at the time of the work, the future outcome is completely unavailable and can only be estimated through careful analysis and evidence-based priors.

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