Use of Linear Regression to Discrete Data

S. Jozová, I. Nagy
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Abstract

Data analysis is very important tool for acquiring information about object of our interest. It involves a lot of various methods, mainly from the area of data mining or statistical analysis. However, most of these methods aim at continuous data. In real applications, especially in the field of Smart Cities, questionnaires are a frequent source of data. They are mainly a source of discrete data. As commonly used data analysis methods, such as regression analysis, naturally work with continuous data, complications can occur. However, the linear regression analysis can be carefully used to to analyze discrete data, but carefully.The paper wants to give a warning before a direct mindless use of regression analysis for discrete data, especially when the independent variables are nominal. Also some ways how to modify values of the independent variables to achieve sensible results with linear regression applied to measured discrete data from the Smart City area are sketched.
离散数据线性回归的应用
数据分析是获取我们感兴趣的对象信息的重要工具。它涉及许多不同的方法,主要来自数据挖掘或统计分析领域。然而,这些方法大多针对连续数据。在实际应用中,尤其是在智慧城市领域,问卷调查是一种常见的数据来源。它们主要是离散数据的来源。由于常用的数据分析方法(如回归分析)自然会处理连续数据,因此可能会出现并发症。然而,线性回归分析可以谨慎地用来分析离散数据,但要谨慎。本文想在对离散数据,特别是自变量是名义变量的情况下,直接盲目地使用回归分析之前提出警告。本文还概述了如何修改自变量的值,使线性回归应用于智慧城市地区的实测离散数据得到合理的结果。
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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