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Md Sohel Mahmood
Md Sohel Mahmood

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Published in Towards Data Science

·Pinned

Outlier Detection (Part 1)

IQR, Standard Deviation, Z-score and Modified Z-score — Introduction It is risky to include outliers in data driven models. The existence of one single misleading value has the potential to change the conclusion implied by the model. Is is therefore, important to detect and then decide whether to remove it or not from the dataset. Sometimes the data…

Outliers

6 min read

Outlier Detection (Part 1)
Outlier Detection (Part 1)

Published in Towards Data Science

·Pinned

Outlier Detection (Part 2)

Adjusted Boxplot for skewed distribution — Introduction In the pervious article, I have discussed about outlier detection procedures for mostly normal distributions. The procedures include IQR (Inter-Quartile Range) Standard deviation Z-score Modified Z-score We have gone through the boxplots after these abovementioned procedures are implemented and shown the number of outliers in each case. In real…

Outliers

5 min read

Outlier Detection (Part 2)
Outlier Detection (Part 2)

Published in Towards Data Science

·Pinned

Simple Linear and Polynomial Regression

Use of Statsmodels, Polyfit, and Linear Regression and Polynomial Features — Introduction Regression is one of the most essential subject for prediction analytics and business forecast. It can be implemented both in linear fashion and by using higher order polynomials. There are instances where the model can be generated using multiple linear regression but many of the real world cases have…

Linear Regression

3 min read

Simple Linear and Polynomial Regression
Simple Linear and Polynomial Regression

Published in Towards Data Science

·Pinned

Outlier Detection in Regression Analysis

Use of Cook’s Distance in Scikit-Learn and Statsmodel for Regression Outlier Detection — Introduction Outliers are defined as abnormal values in a dataset that don’t go with the regular distribution and have the potential to significantly distort any regression model. Therefore, outliers must be carefully handled in order to get the right insight from the data. Usually, the data collected from real-world, consists…

Outliers

5 min read

Outlier Detection in Regression Analysis
Outlier Detection in Regression Analysis

Published in Towards Data Science

·Pinned

Practical implementation of outlier detection in python

IQR, Hampel and DBSCAN method — Outliers, one of the buzzwords in the manufacturing industry, has driven engineers and scientists to develop newer algorithms as well as robust techniques for continuous quality improvement. If the data include even if one outlier, it has the potential to dramatically skew the calculated parameters. Therefore, it is of utmost…

Interquartile Range

7 min read

Practical implementation of outlier detection in python
Practical implementation of outlier detection in python

Published in Learning from Data

·3 days ago

BOXPLOT

Tool to detect outliers —

Boxplot

1 min read

BOXPLOT
BOXPLOT

BOXPLOT

Tool to detect outliers

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Published in Learning from Data

·4 days ago

ANOVA

Telling the story of variance among groups —

Statistics

1 min read

ANOVA
ANOVA

ANOVA

Telling the story of variance among groups

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Published in Learning from Data

·5 days ago

T-test

Compare means between groups —

1 min read

T-test
T-test

T-test

Compare means between groups

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Jun 22

Mean and Median for Skewed Distribution

Statistics for long tailed distribution Introduction In this article, I am going to show skewed distribution statistics. Most importantly I am going to talk about mean and median which are the basic statistics for skewed distributions. I guess mostly we are familiar with normal distribution. Normal distribution is ideal. Normal…

Mean

3 min read

Mean and Median for Skewed Distribution
Mean and Median for Skewed Distribution

Published in Towards Data Science

·Apr 22

Simple Explanation of Statsmodel Linear Regression Model Summary

Statsmodel library model summary explanation — Introduction Regression analysis is the bread and butter for many statisticians and data scientists. We perform simple and multiple linear regression for the purpose of prediction and always want to obtain a robust model free from any bias. …

Multiple Linearregression

7 min read

Simple Explanation of Statsmodel Linear Regression Model Summary
Simple Explanation of Statsmodel Linear Regression Model Summary
Md Sohel Mahmood

Md Sohel Mahmood

Data Science Enthusiast. Linkedin: https://www.linkedin.com/in/mdsohelmahmood/

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