Discipline ID
97ac1514-598d-4ae9-af20-fdf75b940953
COURSE DETAIL
SAMPLE SURVEYS
Country
New Zealand
Host Institution
Victoria University of Wellington
Program(s)
Victoria University of Wellington
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
104
UCEAP Course Suffix
UCEAP Official Title
SAMPLE SURVEYS
UCEAP Transcript Title
SAMPLE SURVEYS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course provides an introduction to practical aspects of survey sampling. Topics include proposal writing, costing, non-sampling errors, rudiments of sampling theory, questionnaire design, fieldwork, basic analytic techniques, and report writing. This course is co-taught with STAT 392.
Language(s) of Instruction
English
Host Institution Course Number
STAT439
Host Institution Course Title
SAMPLE SURVEYS
Host Institution Course Details
Host Institution Campus
Wellington
Host Institution Faculty
Host Institution Degree
Host Institution Department
Statistics
Course Last Reviewed
COURSE DETAIL
INTRODUCTORY STATISTICS
Country
South Africa
Host Institution
University of Cape Town
Program(s)
Explore South Africa,University of Cape Town
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
10
UCEAP Course Suffix
UCEAP Official Title
INTRODUCTORY STATISTICS
UCEAP Transcript Title
STATISTICS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This introductory statistics course develops a sense of numeracy and presents a number of principles and tools to support appropriate quantitative analysis. There is a strong emphasis on using Excel to perform calculations, to manipulate data, and also to demonstrate principles of statistics. Topics include statistical modeling; exploratory data analysis and summary statistics; probability theory; random variables; probability mass and density functions; binomial, Poisson, exponentials, normal, and uniform distributions; sampling distributions; confidence intervals; hypothesis testing; determining sample size; simple linear regression; and measures of correlation. Assessment: classwork (30%), final exam (70%).
Language(s) of Instruction
English
Host Institution Course Number
STA1000F/S
Host Institution Course Title
INTRODUCTORY STATISTICS
Host Institution Course Details
Host Institution Campus
Commerce
Host Institution Faculty
Host Institution Degree
Host Institution Department
Statistical Sciences
Course Last Reviewed
COURSE DETAIL
LINEAR REGRESSION
Country
China
Host Institution
Tsinghua University
Program(s)
Tsinghua University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
106
UCEAP Course Suffix
UCEAP Official Title
LINEAR REGRESSION
UCEAP Transcript Title
LINEAR REGRESSION
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
"Linear Regression" is a professional basic course for the undergraduates' probability and statistics in mathematics. Students are required to learn "Statistical Inference" in advance. The goal of the course is to learn how to perform simple linear regression, multiple regression analysis, regression diagnosis, goodness of fit test, data transformation, variable selection, and generalized linear model, and require correct calculation and interpretation of results, using statistical software R to obtain practical experience. At the same time, it is required to learn some basic theories in the regression.
Language(s) of Instruction
Chinese
Host Institution Course Number
40420814
Host Institution Course Title
LINEAR REGRESSION
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematics
Course Last Reviewed
COURSE DETAIL
CAUSALITY
Country
Denmark
Host Institution
University of Copenhagen
Program(s)
University of Copenhagen
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
106
UCEAP Course Suffix
UCEAP Official Title
CAUSALITY
UCEAP Transcript Title
CAUSALITY
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course introduces concepts and theories behind causal inference in order to predict and analyze a system’s behavior under manipulations. Topics include causal models versus observational models; observational distribution, intervention distribution, and counterfactuals; graphical models and Markov conditions; and identifiability conditions for learning causal relations from observational and/or interventional data. Working with graphs and graphical models, students derive causal effects, predict the result of interventional experiments, perform variable adjustments for computing causal effects, and gain an understanding of and ability to apply different methods for causal structure learning.
Language(s) of Instruction
English
Host Institution Course Number
NMAK17001U
Host Institution Course Title
CAUSALITY
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Faculty of Science
Host Institution Degree
Master
Host Institution Department
Department of Mathematical Sciences
Course Last Reviewed
2021-2022
COURSE DETAIL
STATISTICAL MODELING II
Country
United Kingdom - England
Host Institution
University of London, Queen Mary
Program(s)
University of London, Queen Mary
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
114
UCEAP Course Suffix
UCEAP Official Title
STATISTICAL MODELING II
UCEAP Transcript Title
STAT MODELLING II
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course introduces generalized linear models, which can be used for modeling data such as binary data and count data, where a normal distribution would not be appropriate. These developments dramatically extend the range of problems that can be studied. The methods are implemented using R.
Language(s) of Instruction
English
Host Institution Course Number
MTH6134
Host Institution Course Title
STAT MODELING 2
Host Institution Course Details
Host Institution Campus
Queen Mary University of London
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematical Sciences
Course Last Reviewed
2019-2020
COURSE DETAIL
DATA SCIENCE I: DATA INTEGRATION AND DATA PRIVACY
Country
Korea, South
Host Institution
Yonsei University
Program(s)
Yonsei University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
104
UCEAP Course Suffix
UCEAP Official Title
DATA SCIENCE I: DATA INTEGRATION AND DATA PRIVACY
UCEAP Transcript Title
DATA INTEGRATN&PRIV
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
This course introduces several data integration methods and basic materials for data privacy. From this course, students can integrate multiple data sources by handling data privacy issues. This course provides statistical methodology on data integration and statistical disclosure control.
Language(s) of Instruction
English
Host Institution Course Number
STA4116
Host Institution Course Title
DATA SCIENCE I: DATA INTEGRATION AND DATA PRIVACY
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Course Last Reviewed
2022-2023
COURSE DETAIL
INTRODUCTION TO BUSINESS STATISTICS
Country
Denmark
Host Institution
Copenhagen Business School
Program(s)
Copenhagen Business School Summer
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
Business Administration
UCEAP Course Number
10
UCEAP Course Suffix
UCEAP Official Title
INTRODUCTION TO BUSINESS STATISTICS
UCEAP Transcript Title
INTRO BUSINESS STAT
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This introductory statistics course focuses on data analysis. It begins with the essential concepts that are necessary for understanding data analysis, such as probability and their distributions. It then covers sampling, confidence intervals, hypothesis testing, analysis of variance, correlation, and linear regression analysis. Additional topics include probability concepts, probability distributions, sampling distributions, and two group comparisons.
Language(s) of Instruction
English
Host Institution Course Number
BA-BHAAI1091U
Host Institution Course Title
INTRODUCTION TO BUSINESS STATISTICS
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
International Summer University Programme
Course Last Reviewed
2022-2023
COURSE DETAIL
PROBABILITY AND STATISTICS
Country
United Kingdom - England
Host Institution
University College London
Program(s)
University College London
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
Mathematics
UCEAP Course Number
119
UCEAP Course Suffix
UCEAP Official Title
PROBABILITY AND STATISTICS
UCEAP Transcript Title
PROBABILITY & STATS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course explains the theory of probability and some of the statistical methods based upon it. The course begins with the basic ideas of probability theory: events, probabilities, random variables and the notion of independence. It continues with the two crucial principles: the law of large numbers and the central limit theorem. Using these, the course covers the fundamental concepts of statistical inference (estimation and hypothesis testing), and illustrates these concepts using the most important statistical models.
Language(s) of Instruction
English
Host Institution Course Number
MATH0057
Host Institution Course Title
PROBABILITY AND STATISTICS
Host Institution Course Details
Host Institution Campus
University College London
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematics
Course Last Reviewed
2019-2020
COURSE DETAIL
QUANTITATIVE RESEARCH METHODS
Country
Netherlands
Host Institution
Leiden University College
Program(s)
Leiden University College
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
100
UCEAP Course Suffix
UCEAP Official Title
QUANTITATIVE RESEARCH METHODS
UCEAP Transcript Title
QUANT RESRCH MTHDS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
Today's world relies much on the accumulation, presentation, and interpretation of large quantities of information. Statistics is a tool that enables us to organize our data in an efficient manner, and provides us with methods that help us understand the relationships that occur in our data and our increasingly complex world. This course draws on examples from multiple disciplines, such as political science, economics, medical sciences, and biology to demonstrate how to search for and evaluate patterns in large amounts of data, as well as to interpret what these patterns tell us about the world. The material in this course covers data display, statistical inference, regression and experimental design. The course primarily focuses on developing substantive and precise understanding of the various quantitative research designs and corresponding statistical methods. Students develop individual projects, applying their knowledge to real-world problems using elementary computer programming in the R statistical programming package. This course is designed to be accessible for students at all levels of mathematical skill. The focus is on developing conceptual understanding of statistics without heavy reliance on rigorous mathematical background. The knowledge obtained from this course should provide solid background for students who wish to continue their statistical education with more advanced courses as well as prepare students to perform their own statistical analyses in their coursework and beyond. Upon completion the course aims to provide the students with the following skills: apply scientific research process, including theory formulation and hypothesis testing; critically analyze various types of data and learn to select most appropriate elementary statistical technique to answer their research question; use statistical programming to enter data, generate descriptive statistics and graphs, and estimate basic statistical models; communicate and present statistical results to a variety of audiences – academic experts and policy-makers.
Language(s) of Instruction
English
Host Institution Course Number
8002GED19Y
Host Institution Course Title
QUANTITATIVE RESEARCH METHODS
Host Institution Course Details
Host Institution Campus
Leiden University College, The Hague
Host Institution Faculty
Host Institution Degree
Host Institution Department
Various Departments
Course Last Reviewed
COURSE DETAIL
STATISTICAL MATHEMATICS
Country
Korea, South
Host Institution
Korea University
Program(s)
Korea University
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
21
UCEAP Course Suffix
UCEAP Official Title
STATISTICAL MATHEMATICS
UCEAP Transcript Title
STATISTICAL MATH
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
This course introduces the subject of calculus, including the study of limits and derivatives, and their applications, which is essential and crucial for advanced statistic courses, such as probability theory, mathematical statistics. Specific topics include the limits of functions, derivatives of algebraic, trigonometric, exponential and logarithmic functions and their inverses and the definite integral and its application to area problems. Also, included are applications of the derivative including maximum and minimum problems, and curve sketching using calculus, techniques of integration, indeterminate forms and infinite series.
Language(s) of Instruction
English
Host Institution Course Number
STAT201
Host Institution Course Title
STATISTICAL MATHEMATICS
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Statistics
Course Last Reviewed
2021-2022