Statistics for Data Analysis | Quartiles, Quantiles and Interquartile Range
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Updated
May 20, 2024 - Jupyter Notebook
Statistics for Data Analysis | Quartiles, Quantiles and Interquartile Range
Data analysis and outliers detection of air quality data.
Description of outliers
Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
simple IQR & Z-score normalization script
Data Science Foundations I | Exploratory Data Analysis in Python | Summarizing Single Feature
A outlier removal tool, removes outlier row-wise using z-score or InterQuartile Range method
The following data are annualized returns on a group of 15 stocks. 12.5, 13, 14.8, 11, 16.7, 9, 8.3, -1.2, 3.9, 15.5, 16.2, 18, 11.6, 10, 9.5
Following are the numbers of daily bids received by the government of a developing country from firms interested in winning a contract for the construction of a new port facility
Métodos para extração de outliers
1-Outlier detection and removal of the outlier by Using IQR The Data points consider outliers if it's below the first quartile or above the third quartile 2-Remove the Outliers by using the percentile 3-Remove the outliers by using zscore and standard deviation
Similar image retrieval using distance measure coded in MATLAB
This repository contains the source code for Statistics.JS.
Solution to Aczel problems practice (1-74, 1-75)
The following data are numbers of passengers on flights of Delta Air Lines between San Francisco and Seattle over 33 days in April and early May. 128, 121, 134, 136, 136, 118, 123, 109, 120, 116, 125, 128, 121, 129, 130, 131, 127, 119, 114, 134, 110, 136, 134, 125, 128, 123, 128, 133, 132, 136, 134, 129, 132
Uma análise exploratória dos dados do airbnb sobre a cidade de Vancouver. Limpeza de dados, análises estatísticas, mapas interativos.
Data: 23, 26, 29, 30, 32, 34, 37, 45, 57, 80, 102, 147, 210, 355, 782, 1209
Classification problem using multiple ML Algorithms
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