ols-regression | Topic | Ecosyste.ms: Repos

Topic: "ols-regression"

varungopithallapelly/Effect-of-Apps-on-Users

Applying econometric analysis to observe the effect of paid & free apps developed by small, medium & large firms app developers on total number of active users

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lorenzoridolfi9/Apple

Apple revenue forecast

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shanuhalli/Assignment-Simple-Linear-Regression

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

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TylerJSimpson/machine_learning_frameworks

Machine learning frameworks

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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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LazarosAntonios/Step-by-Step-OLS-regression

This is a simple Excel file that explains thoroughly, all the steps to a Simple Linear Regression model via the OLS method. I use basic excel commands for matrix multiplication and matrix inversion. The input data are not drown from anywhere and are used as an example for the better understanding of the procedure.

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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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piyush-multiplexer/Machine_Learning_Data

ML algorithms in Python

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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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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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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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George-Nyamao/Inside_Airbnb

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

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ashishyadav24092000/Transform_Dep_Vars_regression

In this notebook we would try to modify or transform our dependent variable to rectify the model and at last create a better suited regression model as compared to other. We will just take the natural logarithm of the dependent variable and it will solve the problem of conical spread of datapoints in standard residual plot. It means that our current model has varying variance and needs to be rectified.

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ashishyadav24092000/Curvilinear_models

Here we will learn how to identify a curvilinear model and how to do the modelling for that using OLS(Ordiniary Least Square) method. Plotting residual plots for the models.

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ashishyadav24092000/MAximumLIkelihoodEstimator2_TVads_and_carsold

Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of reisduals.At the end we can conclude that both the methods of estimation produces the same result.

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ashishyadav24092000/MultipleLinearRegression_CategoricalVariables2

This explains the code for multiple regression model for a sample data saved as dummy2.xlsx. It explains the variability of model i.e. dependency of salary on Experience of Employee and their Gender. It also clarifies whether the average salary for the female employees are lesser than male employees or not.And if yes than by how much.

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ashishyadav24092000/MultipleLinearRegression_CategoricalVariables

This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.

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Ashutosh27ind/Data_Deciphers---Unilever-Sales-EQ-Data-Science-POC-Use-Case---Deep-Tech-Machine-Learning

Determination of major drivers of sales and forecasting sales for next 6 periods

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ashishyadav24092000/MultipleLinearRegression_TruckingCompany

Multiple Linear Regression modelling for a sample data trucking.xlsx

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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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ashishyadav24092000/TensileStrength_VS_hardness_DieCastAluminium

This regression model subtly explain how much the variability in tensile strength of the die cast alumnium can be explained with the help of its hardness.It gives an overall regression model as well as a training,tetsing regression models. It uses various python libraries and methds like -sklearn,statsmodel.api,train_test_split,sklearn.metrics,pandas,numpy,scipy,linear_model,OLS,regression.

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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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Rortizri/Econometrics

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martell-n-tardy/Red-Wine-Case-Study

This case study uses exploratory data analysis (EDA) and regression to predict alcohol levels in wine by modeling several linear regression models with varying parameters.

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ranjiGT/BatchLinearRegor

A py3 code that implements batch linear regressor using gradient descent.

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Marcus-V-Freitas/Regressao_Linear_E_Nao_Linear

Exemplo de Regressão Linear e Não Linear (BoxCox) utilizando com visualizações gráficas do ggplot.

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swarnava-96/Linear-Ridge-and-Lasso-Regression

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chiru30/Dr.Crypto Fork of Timsal123/HTM

An interactive site to all crypto investors out there where it connects the broken bridge of market research . To invest on any crypto coin a ton of factors contribute for right , safe and secure investment .

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