Course number：M11355
Class Hours：48 Credits：3
After-class Hours: 12
Principles of Statisticsis a compulsory course; its prerequisites areMathematics Thinking and Culture, Principles of Economics; it is suitable for undergraduates majoring in public management. This course mainly describes the concept and nature of statistics; the basic problems of statistics, including the types of data, commonly used terms of statistics, statistical indicators and statistical indicator systems, statistical calculation tools; the basic content of statistics, including statistical data Collection, sorting and display, descriptive analysis of data, sampling estimation, hypothesis testing, analysis of variance, correlation regression analysis, time series analysis, statistical index analysis, statistical comprehensive evaluation, etc. Through the study of this course, students will be able to combine social practice, understand statistical thinking, cultivate data application thinking, conform to the needs of big data analysis, use statistical analysis theories and methods, explore the data performance, quantitative relationships and changing laws behind social economic phenomena, and learn to use statistical methods and data processing techniques to analyze and solve social economic problems.
I Course objectives
1. General course objectives：
The overall teaching goal of this course is to enable students to understand the basic knowledge of statistics, master the basic theories and basic methods of statistics, train students to collect data, organize data, analyze data and process data, use statistical thinking to think about problems, and make students be able to use certain statistical tools to solve practical problems, understand social and natural phenomena from the perspective of quantitative analysis, explore the inherent quantitative laws of objective things, improve students' ability to use statistical methods to explore the unknown, and provide theories, principles and methods for the investigation and research of social and economic phenomena, and provide a basis for quantitative analysis for in-depth exploration of the laws of social and economic development and other related courses learning.
2. Course sub-objectives：
Course objective 1：
This course can make students master statistical methods in the social, economic, and life fields, to explore the laws of changes in social and economic phenomena; make students learn how to collect and organize statistical data and information, and to analyze data using the basic theories and methods of statistics. It will lay the foundation of quantitative analysis for further study of other related subjects, strengthen students' practical ability of quantitative analysis of social and economic problems, and improve students' general skills. (Support the graduation requirement of this major 25.4)
Course objective2：
Starting from practical applications, this course explains the methods of collecting and displaying statistical data, and the methods of using statistical data to analyze actual problems, so that students can master and use basic statistical methods and techniques to collect data, organize data, and analyze data. Then students can have correct understanding of economic issues, so as to cultivate students' statistical analysis ability to solve practical problems and improve students' professional skills. (Support the graduation requirement of this major 25.5)
Course objective3：
Through the construction of statistical theory system, students can cultivate their statistical thinking ability, use statistical techniques and statistical models to carry out data analysis, explore the inherent quantitative regularity of data, so as to achieve a scientific understanding of objective things, and guide students to study the internal connections of complex social phenomena. Reveal the internal laws of social phenomena and then make scientific decisions to enhance students' research capabilities. (Support the graduation requirement of this major 25.6)
Course objective4：
Using inquiry-based and seminar-style teaching methods, through theoretical lectures, case analysis, computer experiments and other forms, this course will guide students to learn independently with both brains and hands, theory and practice, and improve students’ ability to explore the complexity of public management with big data, and then enhance students' innovative consciousness and ability. (Support the graduation requirement of this major 25.7)
Course objective5：
Statistics is the science of collecting, processing, analyzing and interpreting data and drawing conclusions from the data. Around all aspects of statistics, the education function of classroom teaching is penetrated into it, which includes cultivating students’ rigorous and realistic attitudes in collecting data, the craftsman's spirit of excellence in processing data, the materialist and dialectical scientific thinking in analyzing data, the cautious exploration of rational empirical analysis of data. (Course ideological and political teaching objectives)
II Curriculum content, requirements and time allocation
1．Curriculum content
Num |
Contents |
Requirements |
Class hours |
Ideological and political education contents |
Note |
1 |
Chapter 1 Into Statistics |
Understand the generation and development of statistics, the nature and research methods of statistics; Master several basic concepts in statistics; Understand the meaning of statistics and the characteristics of statistical research objects; Be familiar with the basic links and content of the whole statistical process. |
4 |
|
|
2 |
Chapter 2 Collection, Sorting and Display of Statistical Data |
Understand various statistical survey forms and their characteristics; Understand the basic principles of statistical collation; Master the statistical survey plan design and the collection methods of original data; Understand the compilation method of statistical grouping and distribution series; Be familiar with the drawing methods of various statistical charts; Be familiar with the concept and classification of variables and data; Master the use of statistical software to make statistical charts. |
4 |
Guide students to pay attention to the stories behind the data with a sense of review responsibility, pay attention to China's economic development figures, appreciate China's rapid development and institutional advantages, strengthen students' national awareness and political identity, and increase national pride and self-confidence. |
|
3 |
Chapter 3 Descriptive Analysis of Data |
Understand descriptive statistics, central tendency, and arithmetic mean; Understand harmonic mean and geometric mean; Be familiar with the location mean, median, and quantile; Master standard deviation, dispersion coefficient and standardization; Be familiar with the mode and its relationship with the median of the mean; Master the range of dispersion, interquartile range, and average range; Master skewness and kurtosis. |
4 |
|
|
4 |
Chapter 4 Sampling Estimation |
Understand the basic concepts of sampling inference; Understand the probability of sampling error; Be familiar with sampling organization; Master sampling error; Be familiar with parameter estimation; Grasp the factors affecting sample size; Master the determination of sample size. |
4 |
Through situational discussions, students are guided to analyze problems with correct positions, viewpoints and methods. Through statistical sampling, students are inspired to correctly recognize the phenomenon of biased views and statistical abuse, spread positive energy, and establish correct values. |
After-class Hours: 2 |
5 |
Chapter 5 Hypothesis Testing |
Understand hypothesis testing ideas and principles; Understand the relationship between parameter estimation and hypothesis testing; Be familiar with hypothesis testing of single population mean; Master the hypothesis test of the overall mean difference; Master the hypothesis test of the overall proportion; Be familiar with the steps of hypothesis testing; Understand the two types of errors in hypothesis testing; Master the hypothesis test of the variance of a single normal population; Master the hypothesis test of the ratio of the variance of the binormal population. |
6 |
|
After-class Hours: 2 |
6 |
Chapter 6 Analysis of Variance |
Understand the basic concepts of analysis of variance; Understand the basic principles of analysis of variance; Master single factor and double factor analysis of variance; Master the analysis of variance table. |
6 |
|
After-class Hours: 2 |
7 |
Chapter 7 Correlation Regression Analysis |
Understand the significance of correlation analysis, related types, and significance of regression analysis; Understand the characteristics of commonly used nonlinear functions; Master the calculation and application of correlation coefficients; Be familiar with the difference and connection between regression and related; Master multiple linear regression models; Master the establishment, application and analysis methods of simple linear regression equations. |
6 |
Through the explanation of data processing and analysis, students are guided to pursue the craftsman spirit of excellence, internalize the spirits of rigor, focus, and dedication into personal qualities, and establish good professional qualities of public managers. |
After-class Hours: 2 |
8 |
Chapter 8 Time Series Analysis |
Understand the concepts and types of time series; Understand the time series level analysis index, development level and average development level; Master the speed analysis index of time series; Master long-term trend analysis; Be familiar with time series level analysis indicators-growth and average growth. |
6 |
|
After-class Hours: 2 |
9 |
Chapter 9 Statistical Index Analysis |
Understand the application of statistical indexes in socio-economic issues; Master the compilation methods and characteristics of the comprehensive index and the average index; Be familiar with the factor analysis methods of composite index and total average index; Grasp the basic concepts and basic principles of the index. |
4 |
|
|
10 |
Chapter 10 Statistical Comprehensive Evaluation |
Understand the basic issues of comprehensive evaluation; Understand the preprocessing of evaluation indicators; Master the weighting method of comprehensive evaluation index; Master the synthesis method of comprehensive evaluation. |
4 |
|
|
Total |
|
48 |
|
|
2．After-classcurriculum content
Num |
Contents |
Requirements |
Class hours |
Styles |
Note |
1 |
Chapter4：Course Q&A |
Master what have learned |
2 |
Online or offline guidance |
|
2 |
Chapter5：Course Q&A |
Master what have learned |
2 |
Online or offline guidance |
|
3 |
Chapter6：Course Q&A |
Master what have learned |
2 |
Online or offline guidance |
|
4 |
Chapter7：Course Q&A |
Master what have learned |
2 |
Online or offline guidance |
|
5 |
Chapter8：Course Q&A |
Master what have learned |
2 |
Online or offline guidance |
|
6 |
Course tutor |
Master course content systematically |
2 |
Online or offline guidance |
|
Total |
|
12 |
|
|
3．Experiment arrangement content
Num |
Experiment name |
Content and requirements |
Class hours |
Note |
1 |
Descriptive statistics |
Mean, median, quantile; Standard deviation, dispersion coefficient and standardization; Descriptive statistics, central tendency, degree of dispersion; Skewness and kurtosis. |
2 |
|
2 |
Variance analysis |
Use SPSS software for variance analysis |
2 |
|
3 |
Correlation analysis |
Use SPSS software forcorrelation analysis |
2 |
|
4 |
Regression analysis |
Use SPSS software for regression analysis |
2 |
|
Total |
|
8 |
|
III Teaching staff
The person in charge of the course requires a doctorate degree, a senior professional title, a professional education background in economics, management or statistics, and more than three years of teaching experience.
Course teachers are required to have a doctoral degree or an intermediate professional title, and have a professional education background or teaching experience in economics, management, or statistics.
IV Teaching materials and teaching reference
1. Main material
Statistics, Li Jinchang, Higher Education Press, 2018
2. Reference materials
[1] Statistics, Guan Yuhua, 3rd edition, Higher Education Press, 2013
[2] Statistics, Jia Junping, He Xiaoqun and Jin Yongjin, 7th edition, Renmin University of China Press, 2018
[3] Management Statistics, Li Jinlin, 3rd edition, Tsinghua University Press, 2016
V Teaching arrangement
This course adopts heuristic, discussion, case analysis and other teaching methods, makes full use of modern teaching methods such as multimedia, optimizes the teaching process and teaching content as a whole, and mobilizes students' enthusiasm for learning; It uses the exercise library of the online platform to complete the application and mastery of knowledge. Combining the application of SPSS statistical software, it starts from case analysis to improve students learning efficiency. Teachers implement the principle of combining theory and practice, assign a certain amount of thinking questions to students, require students to complete a certain amount of homework, and improve students' understanding of the basic concepts of statistics courses.
This course arranges at least 5 formal online or offline intensive Q&A, and 3-4 course assignments are carried out according to the actual teaching process. The assignments can be Q&A, right and wrong judgment, essay, software operation, etc. The teacher's review feedback can be in the form of PPT classroom presentations, personal express feedback, online courses, etc.
VI Course assessment
Process assessment (40%) + Result assessment (60%)
1. Process assessment (40%)
Attendance, class performance, homework, class test, experiment report, etc.
2. Result assessment (60%)
Closed-book test
VII Instruction
This course standard starts to be used since the 2020 grade.
The change of teaching quality standard of the course should be submitted by the person in charge of the course. After the approval of the head of subject and the approval of the teaching dean of the college, it shall be reported to the Academic Affairs Department for record. The teaching quality standard of the course is implemented by the main teacher who undertakes this course.
