第1章 数据与统计
Alternatively, a numeric code could be used for the class standing variable (e.g. 1 denotes Freshman, 2 denotes Sophomore, and so on).
17
Scales of Measurement
All the data collected in a particular study are referred to as the data set for the study.
10
Elements, Variables, and Observations (个体、变量和观察值)
Elements are the entities on which data are collected. A variable is a characteristic of interest for the elements. The set of measurements obtained for a particular
Ratio(比率)
The data have all the properties of interval data and the ratio of two values is meaningful.
Variables such as distance, height, weight, and time use the ratio scale.
统计学(statistics)
• Office hour: 每周二 、周四12:00 –13:00, • 或其它预约时间 2231 • 教学信箱: • sisustatistics@ • password:ilovestatistics • 傅军和 • E-mail: fjhjf2013@
21
Categorical and Quantitative Data
The statistical analysis that is appropriate depends on whether the data for the variable are categorical or quantitative.
Interval(区间) The data have the properties of ordinal data, and the interval between observations is expressed in terms of a fixed unit of measure.
18
Scales of Measurement
7
1.1 Applications in Business and Economics
• Accounting Public accounting firms use statistical sampling procedures when conducting audits for their clients.
Quantitative(数值型,定量): 1 Interval(区间) 2 ratio(比率)
The scale determines the amount of information contained in the data.
The scale indicates the data summarization and statistical analyses that are most appropriate.
8
Applications in Business and Economics
Marketing Electronic point-of-sale scanners at retail checkout counters are used to collect data for a variety of marketing research applications.
Production
A variety of statistical quality control charts are used to monitor the output of a production process.
9
Data and Data Sets
Data are the facts and figures collected, analyzed, and summarized for presentation and interpretation.
This scale must contain a zero value that indicates that nothing exists for the variable at the zero point.
20
Scales of Measurement
Ratio
Example: Melissa’s college record shows 36 credit hours earned, while Kevin’s record shows 72 credit hours earned. Kevin has twice as many credit hours earned as Melissa.
Interval
Example: Melissa has an SAT score of 1205, while Kevin has an SAT score of 1090. Melissa scored 115 points more than Kevin.
19
Scales of Measurement
2 continuous, if measuring how much
Quantitative data are always numeric.
14
Scales of Measurement
Nominal
Example: Students of a university are classified by the school in which they are enrolled using a nonnumeric label such as Business, Humanities, Education, and so on. Alternatively, a numeric code could be used for the school variable (e.g. 1 denotes Business, 2 denotes Humanities, 3 denotes Education, and so on).
5
Statistics for Business and Economics
6
Chapter 1 Data and Statistics
Statistics Applications in Business and Economics Data Data Sources Descriptive Statistics Statistical Inference Computers and Statistical Analysis Data Mining Ethical Guidelines for Statistical Practice
• 数学的主要研究方法是: • 统计学的主要研究方法:
演绎
• 归纳
统计学家必须习惯于接受一些不完美的事实
现代统计学的理论几乎用到所有最高深的数学的各个 分支,我们会碰到许许多多的结论,这些结论我们不 清楚其严格证明,但是必须要理解,并且能够运用所 学统计方法。
4
学习目的
•1 这是什么问题?该用什么方法?(方法学得越多, 这个问题越难,有些问题应该用多种方法结合,统计 方法的应用理论上需要满足一些严格的条件,但现实 不可能完全满足) •2 怎么实施? • (掌握统计软件SPSS) •3 结合问题的背景和统计计算的结果合理解释!概括 起来是:掌握方法解决问题,而不是机械地记住方法 的步骤。 • (以上都需要对统计方法有良好的理解)
element is called an observation. A data set with n elements contains n observations. The total number of data values in a complete data
set is the number of elements multiplied by the number of variables.
16
Scales of Measurement
Ordinal
Example: Students of a university are classified by their class standing using a nonnumeric label such as Freshman, Sophomore, Junior, or Senior.
EnergySouth
N
74.00 1.67
Keystone
N
365.70 0.86
LandCare
NQ
111.40 0.33
Psychemedics
N
17.60 0.13
Data Set
12
Scales of Measurement (测量尺度)
Categorial(分类、定性、非数值型 ): 1 Nominal名义 ;2 Ordinal 顺序
15
Scales of Measurement
Ordinal(顺序)
The data have the properties of nominal data and the order or rank of the data is meaningful.