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1. www.scribbr.com › statistics › outliersHow to Find Outliers | 4 Ways with Examples & Explanation -...

   www.scribbr.com › statistics › outliers

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   30 lis 2021 · Learn how to identify outliers in a dataset using four methods: sorting, data visualization, statistical tests, and interquartile range. See examples of true and false outliers and how to deal with them in your analysis.

   • Chi-Square

     What is a chi-square test? Pearson’s chi-square (Χ 2) tests,...

   • Standard Deviation

     With samples, we use n – 1 in the formula because using n...

   • Simple Linear Regression

     Simple Linear Regression | An Easy Introduction & Examples....

   • Correlation Coefficient

     There are many different correlation coefficients that you...

   • Linear Regression in R

     Step 1: Load the data into R. Follow these four steps for...

2. statisticsbyjim.com › basics › outliers5 Ways to Find Outliers in Your Data - Statistics By Jim

   statisticsbyjim.com › basics › outliers

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   Learn what outliers are and why they are problematic for statistical analyses. Explore various methods to identify outliers, such as sorting, graphing, z-scores, interquartile range, and standard deviation.

3. www.scribbr.co.uk › stats › statistical-outliersHow to Find Outliers | Meaning, Formula & Examples - Scribbr

   www.scribbr.co.uk › stats › statistical-outliers

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   4 paź 2022 · Learn what outliers are, why they matter, and how to identify them in four ways: sorting, visualisation, statistical tests, and interquartile range. See examples, formulas, and tips for dealing with outliers in your data.

4. www.geeksforgeeks.org › detect-and-remove-the-outliers-using-pythonDetect and Remove the Outliers using Python - GeeksforGeeks

   www.geeksforgeeks.org › detect-and-remove-the-outliers-using-python

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   30 sie 2024 · Identifying outliers is important in statistics and data analysis because they can have a significant impact on the results of statistical analyses. The analysis for outlier detection is referred to as outlier mining.

5. medium.com › @aashish › how-to-identify-and-remove-outliers-in-yourHow to Identify and Remove Outliers in Your Dataset: A Guide for...

   medium.com › @aashish › how-to-identify-and-remove-outliers-in-your

   15 sie 2024 · The key is to handle outliers with care, ensuring that you strike the right balance between data accuracy and integrity. Why Should You Care About Outliers? Outliers can significantly...

6. builtin.com › data-science › how-find-outliers-examplesHow to Find Outliers (With Examples) - Built In

   builtin.com › data-science › how-find-outliers-examples

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   27 kwi 2022 · Learn how to use descriptive statistics and clustering techniques to detect outliers in data. See how to apply IQR and DBSCAN methods to a credit card fraud data set and compare the results.

7. towardsdatascience.com › how-to-detect-handle-and-visualize-outliers-ad0b74af4af7How to Detect, Handle and Visualize Outliers

   towardsdatascience.com › how-to-detect-handle-and-visualize-outliers-ad0b74af4af7

   6 cze 2021 · In statistics, an outlier is a data point that differs significantly from other observations. An outlier may be due to variability in the measurement or it may indicate experimental error; the latter are sometimes excluded from the data set. An outlier can cause serious problems in statistical analyses. Some Outlier Theory.