Measurement of Central Tendencies

M. Sial, A. Abid
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Abstract

The main purpose of this article is to understand central tendencies, its application, its types, as well as to learn how to achieve arithmetic mean from grouped and ungrouped data. We will be able to understand geometric and harmonic means and way to calculate them from grouped and ungrouped data. In addition, we will learn which types of mean tends to have more errors and which one to use in which circumstances. We will also be able to know median and mode that are located at the center of data. This article will elucidate the differences between arithmetic mean, median and mode as well as explain ways to calculate mode and median, and pros and cons of median. Preface: In statistical analysis, we sometimes need to analyze the data with respect to a specific characteristic. This characteristic or number should represent the whole set of data. In statistics, central tendency is a central value for data. Measures of central tendencies are often called averages. The most common measure of central tendency are the arithmetic mean, the median, and the mode. Averages can be divided into two groups. The first type is the average with respect to location and second one is mathematical average. We will explain each one in more detail in this article. Objectives: The main objective of this article is to understand mean, its types, and usage in daily life. Methodology: In this article, I have used library research and I have collected data from reliable resources and internet sites.
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集中趋势的测量
本文的主要目的是理解集中趋势、集中趋势的应用、集中趋势的类型,以及学习如何从分组和未分组的数据中获得算术平均值。我们将能够理解几何和调和均值,以及从分组和未分组数据中计算它们的方法。此外,我们将学习哪种类型的均值倾向于产生更多的误差,以及在哪种情况下使用哪种均值。我们还可以知道位于数据中心的中位数和众数。本文将阐明算术平均、中位数和众数的区别,解释众数和众数的计算方法,以及中位数的利弊。前言:在统计分析中,我们有时需要根据特定的特征来分析数据。这个特征或数字应该代表整个数据集。在统计学中,集中趋势是数据的中心值。集中趋势的度量通常称为平均值。集中趋势最常用的度量方法是算术平均值、中位数和众数。平均数可以分为两类。第一种是相对于位置的平均,第二种是数学平均。我们将在本文中更详细地解释每一个。目的:本文的主要目的是了解mean,它的类型,以及在日常生活中的用法。方法:在本文中,我使用了图书馆研究,并从可靠的资源和互联网站点收集了数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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