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 […]
Data Science and A.I. : How to Calculate Percentiles Step-by-Step Guide Read More »
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
Data Science and A.I. : Computing Quartiles from Grouped Data: Step-by-Step Guide Read More »
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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Numerical Example to Compute Quartile Problem Statement: Given the data set: 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, calculate the first quartile, second quartile, and third quartile using the quartile formulas. Understanding Quartiles: Quartiles divide the data set into four equal parts. There are three quartiles, denoted by \( Q_1 \), \(
Data Science and A.I. : Numerical Related to Quartile Read More »
“`html PostNetwork Academy guides us through three crucial statistical measures: Quartiles, Deciles, and Percentiles These measures are used to divide a data distribution into equal parts, making them essential tools in data analysis. Hello everyone! Welcome to another educational post from PostNetwork Academy. I’m Bindeshwar, and before we begin, make sure to follow us on
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In this post, we dive into one of the core statistical concepts used in data science and artificial intelligence—calculating the variance of a continuous frequency distribution. Breaking down the steps If you have data distributed across class intervals with frequencies, the goal is to find the variance. The video explains the columns in the table:
Data Science and A.I. – Measures of Dispersion: Variance of Discrete Frequency Distribution In this post from PostNetwork Academy’s Data Science and A.I. Lecture Series, Bindeshwar Singh Kushwaha walks us through the process of calculating the variance of a discrete frequency distribution. This is an essential statistical measure for understanding the spread of data
How to Calculate Variance for a Given Distribution Introduction: In this post, we will explore the step-by-step process of calculating the variance and standard deviation for a given frequency distribution. Understanding these concepts is crucial for analyzing data variability and distribution spread. Example: Given the following frequency distribution, we will calculate both the variance and
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Panda’s Series- In the last post, I explained how to create a panda’s series. Further, a pandas series has a lot of you often need to analyze, visualize and clean data. In this post, I will be explaining min(), max(), mean(), median(), and mode functions. min() Function- import pandas as pd lst=[2, 4, 6, 8,
Pandas Series Functions min(), max(), mean(), median() and mode() Read More »