《Statistics》Syllabus

Course Number:           2110010807

Course Name:               Statistics

Instructors:                    Yu Dongdong

Required Text:            Jia Junping, He Xiaoqun, Jin Yongjin. Statistics (8th Ed.) [M]. Beijing: China Renmin University Press, 2021.

Course Description:      This course is an elective within the Marketing major, focusing on the fundamental theories and methods of statistical quantitative analysis. It closely integrates with social practices to analyze the quantitative manifestations, relationships, and changes in social and natural phenomena. As a methodological science, this course is a foundational and core component within the entire Marketing curriculum, aligning with business administration disciplines. The course covers key topics such as statistical concepts, graphical data representation, descriptive statistics, parameter estimation, hypothesis testing, analysis of variance, linear regression, time series forecasting, and index methods. It builds upon the preliminary course in Probability Theory and Mathematical Statistics, providing a foundation and analytical methods for subsequent courses in Market Research and Analysis. By completing this course, students will enhance their statistical literacy and abilities in data collection, processing, and analysis. This course not only benefits statistics majors in mastering other advanced professional courses but also helps students from other disciplines develop statistical thinking and research methods. This broadens their perspectives and improves their adaptability to developments in their respective fields.

                                                                                                   Credit/Teaching Hours

Outline of UG CPC Topics Covered in this Course:  (2.5Credits/40 Teaching Hours)

I. Introduction to Statistics                                         2Teaching Hours

-Basic Concepts in Statistics

-Types of Statistical Data

-Data Collection

II. Data Presentation Using Charts                                4Teaching Hours

-Data Preprocessing

-Organizing and Displaying Categorical Data

-Organizing and Displaying Numerical Data

-Effective Use of Charts

III. Descriptive Statistics                                          4Teaching Hours

-Measures of Central Tendency

-Measures of Dispersion

-Skewness and Kurtosis

IV. Parameter Estimation                                         4Teaching Hours

-General Issues in Parameter Estimation

-Interval Estimation of Population Parameters

-Determining Sample Size

V.   Hypothesis Testing                                           4Teaching Hours

-Overview of Hypothesis Testing

-Testing Population Parameters

VI. Chi-Square Tests                                             4Teaching Hours

-Categorical Data and χ⟡ Statistic

-Goodness-of-Fit Tests

-Contingency Table Analysis

VII. Analysis of Variance (ANOVA)                                4Teaching Hours

-Introduction to ANOVA

-One-Way ANOVA

-Two-Way ANOVA

-Assumptions and Tests of ANOVA

VIII. Correlation and Regression Analysis                          4Teaching Hours

-Measuring Relationships Between Variables

-Simple Linear Regression

-Multiple Linear Regression

IX. Time Series Analysis and Forecasting                           4Teaching Hours

-Time Series Decomposition

-Descriptive Analysis of Time Series

-Time Series Forecasting

-Seasonal Forecasting Methods

-Trend Forecasting Methods

X. Indices                                                      2Teaching Hours

-Meaning and Classification of Indices

-Weighted Indices

Total (Teaching Hours)                                                                               40  

Summary of UG CPC Topics Covered in this Course:                   (48Teaching Hours)