Exemplo de Regressão Linear e Não Linear (BoxCox) utilizando com visualizações gráficas do ggplot.
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Updated
Aug 12, 2021 - Jupyter Notebook
Exemplo de Regressão Linear e Não Linear (BoxCox) utilizando com visualizações gráficas do ggplot.
This repo contains various projects and assignments I worked on in my Economics Courses
Basic Regression Analysis
This assignment relates to my 6th assignment in Econ 323 - Econometrics Analysis 2. It deals with GDP time series data.
Data Science Foundations II | Statistics Fundamentals for Data Science | Simple Linear Regression for Data Science
Statistical analysis of potential association between a NBA team’s number and type of injuries to their record from the 2010-15 seasons. Prediction of 2016 season records given injury types and numbers.
STUDY PROJECT ON REGRESSION FOR EXTENT OF FOREIGN OWNERSHIP
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.
Task 4 with Codsoft for my data science internship to predict the sales of electronic device or media
Multiple Linear Regression modelling for a sample data trucking.xlsx
Used libraries and functions as follows:
supervised linear regression from scratch in javascript
Goal is to find the Prediction of Protein content, so used All Regression Algorithms of Machine Learning
Multi_Linear_Regression_on_Cars_data_to_predict_MPG
Conducting simple linear regression on the penguins dataset
Data Science Project : A digital media company (similar to Voot, Hotstar, Netflix, etc.) had launched a show. Initially, the show got a good response, but then witnessed a decline in viewership. The company wants to figure out what went wrong.
Can we forecast accurately the revenues of Moncler Genius with ML OLS? Facebook's Prophet or Bayesian Inference?
Implemented Multiple Linear Regression using Backward Elimination Method. This code will work for all dependencies of the form y=b0+b1x1+b2x2+b3x3....bnxn
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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