Analytics Vidhya

SEPTEMBER 9, 2021

This article was published as a part of the Data Science Blogathon What is Hypothesis Testing? Any data science project starts with exploring the data. When we perform an analysis on a sample through exploratory data analysis and inferential statistics we get information about the sample.

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Mlearning.ai

MARCH 5, 2023

Photo by Joshua Sortino on Unsplash Data analysis is an essential part of any research or business project. Before conducting any formal statistical analysis, it’s important to conduct exploratory data analysis (EDA) to better understand the data and identify any patterns or relationships.

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Data Science Dojo

JANUARY 22, 2023

In this blog, we will discuss exploratory data analysis, also known as EDA, and why it is important. We will also be sharing code snippets so you can try out different analysis techniques yourself. EDA is an iterative process of conglomerative activities which include data cleaning, manipulation and visualization.

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Women in Big Data

APRIL 17, 2024

Hypothesis Testing in Action: We learned how to formulate a null hypothesis (no difference exists) and an alternative hypothesis (a difference exists) and use statistical tests to evaluate their validity. This allows us to make generalizations about populations based on samples.

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Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

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Pickl AI

FEBRUARY 22, 2024

Data Science Bootcamp Pickl.AI This bootcamp includes a dedicated Statistics module covering essential topics like types of variables, measures of central tendency, histograms, hypothesis testing, and more. You will learn by practising Data Scientists. Data Science Job Guarantee Course Pickl.AI

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Pickl AI

MARCH 3, 2023

Prescriptive Analysis : Significantly, the use of Prescriptive Analysis helps in prescribing the best possible outcome for assessing datasets. Exploratory Data Analysis : Significantly, the use of exploratory data analysis in Statistics studies the datasets to highlight the major features of the data.

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