Understanding Skewness: An Essential Concept in Data Science Welcome to the Data Science and AI Lecture Series by PostNetwork Academy! In this blog post, we’ll dive deep into the concept of skewness, a critical aspect of understanding data distribution in statistics. Whether you’re a beginner or an advanced learner, this post will help clarify the […]
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Understanding Quartile Deviation: Step-by-Step Calculation & Visualization Quartile deviation, also known as the semi-interquartile range, is a useful measure in statistics that helps to understand the spread or dispersion of the middle 50% of a dataset. This post explains how to calculate quartile deviation using a sample dataset, and how to visualize it on
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Data Science and A.I. Lecture Series: Computing the 70th Percentile Welcome to our Data Science and A.I. lecture series! In this post, we’ll cover a fundamental concept in statistics – percentiles. Specifically, we’ll learn how to compute the 70th percentile, or P70, for a grouped data set. Understanding Percentiles Percentiles divide a data set
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From the Following Data, Compute the Value of P27 Given Data xi 0 1 2 3 4 5 6 7 8 fi 1 9 26 59 72 52 29 7 1 Solution Percentile divides the dataset into 100 equal parts. To compute P27, we use the following formula: Formula: P27 = 27N/100 Given N
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Numerical Example to Compute Percentile Given the data set: 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, 54, 57, 60, calculate the 30th and 60th percentiles. Percentile Percentiles are those values of the variate which divide the distribution into 100 equal parts, therefore the number of
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Computing Deciles from Frequency Distribution From the following data, we compute the values of the deciles: Class Intervals and Frequencies Class Interval (C.I.) Frequency (fi) 0-10 3 10-20 10 20-30 17 30-40 7 40-50 6 50-60 4 60-70 2 70-80 1 Total N = 50 Cumulative Frequency Class Interval (C.I.) Frequency (fi) Cumulative Frequency
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How to Compute Deciles In this lesson, we are going to learn how to calculate the values of deciles, a using the given data. This guide will walk you through the computation process. Example Data The data provided is: Variable (xi) Frequency (fi) Cumulative Frequency (C.F.) 58 2 2 59 3 5 60
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Hello everyone! Welcome back to Postnetwork Academy. I’m Bindeshwar Singh, and today we’re going to uncover a key concept in statistics that helps you understand data more deeply—deciles! Have you ever wondered how to break down a data set into smaller, meaningful parts? Deciles allow us to split data into 10 equal sections, giving us
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Quartiles help to divide a dataset into four equal parts. In this post, we will compute the values of the lower quartile (Q₁), median (Q₂), and upper quartile (Q₃) from a given set of grouped data. Data: | C.I. | fᵢ | |——-|—–| | 5-10 | 5 | | 10-15 | 6 | | 15-20
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How to Compute Quartiles from Given Data In this post, we will learn how to compute the quartiles \( Q_1 \), \( Q_2 \) (Median), and \( Q_3 \) using the provided data set. Quartiles help in dividing a data set into four equal parts, making it easier to understand the distribution of data.
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