The science of statistics involves collecting, analyzing, interpreting, and presenting data. The method of collecting, organizing, and summarizing data is called descriptive statistics. The systematic method of drawing inferences from the sample data and predicting unknown characteristics of a population is called inferential statistics.
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population and study that portion (sample) to gain information about the population. Data are the result of sampling from a population.
Sampling is an efficient technique because it takes a lot of time and money to examine an entire population. For example, if the overall grade point average of all students in a school needs to be computed, it would make sense to select a few students and calculate their grade point average.
From the sample data, a statistic can be calculated. A statistic is a number that represents the property of the sample and gives an estimate of the population parameter. A parameter is a numerical characteristic of the whole population that a statistic can estimate. In the above example, the students from a particular class can be considered a sample of the entire school population. The grade point average of students in a single class is an example of a statistic. Since the students in the entire school were considered to be the population, then the average grade points earned per student in a class is an example of a parameter.
This text is adapted from Openstax, Introductory Statistics, Section 1.1 Definitions of Statistics, Probability, and Key Terms
统计学是从数据中收集、组织和提取有意义信息的科学。Statistics 广泛用于分析数据,例如政府人口普查或天气报告。
让我们进行一个统计练习来计算地球上所有人的平均心率。
在统计学中,所有被研究的个体或对象都称为总体。
由于无法伸出手来测量每个人的心率,因此只绘制了一部分人或一部分人口。这称为样本。
样本的平均心率称为统计量,即描述样本特性的数值测量值。
这种系统地从个人收集数据并总结的方法称为描述性统计。
最后,可以外推样本统计量以确定平均心率或总体特征,也称为参数。
这种从样本数据中得出推论并预测总体未知特征的系统方法称为推论统计。
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