Multiple Regression Analysis
Multiple Regression Analysis
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DOI：
10.1007/978-1-4842-0043-8_10
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Venkat Reddy Konasani;Shailendra Kadre
中科院分区：
文献类型：
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作者：
Venkat Reddy Konasani;Shailendra Kadre
在第9章中，我们讨论了相关性，它用于量化一对变量之间的关系。我们还讨论了简单回归，它有助于在给定自变量时预测因变量。在简单回归中，您使用单个自变量来预测因变量。这是一种过于简单的方法，在实践中，一些因变量可能需要一个以上的自变量才能进行准确的预测。例如，你能通过只看出口来预测一个国家的国内生产总值（GDP）吗？显而易见的答案是，这是不可能的。预测GDP可能需要其他一些变量，如人均收入、自然资源价值、国家债务等;同样，个人的健康取决于许多变量，如吸烟或饮酒习惯、饮食习惯、工作压力、日常锻炼、遗传、睡眠习惯等。
In Chapter 9, we discussed correlation, which is used for quantifying the relation between a pair of variables. We also discussed simple regression, which helps predict the dependent variable when an independent variable is given. In simple regression, you use a single independent variable to predict the dependent variable. This is a simplistic approach, and in practice some dependent variables may require more than one independent variable for accurate predictions. For example, can you predict the gross domestic product (GDP) of a nation by looking just at exports? The obvious answer is that it can’t be done. Predicting the GDP may need several other variables, such as per-capita income, value of natural resources, national debt, and so on. Likewise, the health of an individual depends upon many variables, such as smoking or drinking habits, eating habits, job pressure, daily workouts, genetics, sleeping habits, and more.