Discipline ID
97ac1514-598d-4ae9-af20-fdf75b940953
COURSE DETAIL
STATISTICS FOR LIFE AND SOCIAL SCIENCE
Country
Australia
Host Institution
University of New South Wales
Program(s)
University of New South Wales
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
Mathematics
UCEAP Course Number
10
UCEAP Course Suffix
UCEAP Official Title
STATISTICS FOR LIFE AND SOCIAL SCIENCE
UCEAP Transcript Title
STATS: LIFE&SOC SCI
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course provides an introduction to statistics: the study of collecting, analysing, and interpreting data, which is fundamental to doing any form of quantitative research. Students learn to recognize which analysis procedure is appropriate for a given research problem involving one or two variables; understand principles of study design; and apply probability theory to practical problems. They apply statistical procedures on a computer using RStudio/R; interpret computer output for statistical procedure; calculate confidence intervals and conduct hypothesis tests by hand for small datasets; and understand the usefulness of statistics in their professional area.
Language(s) of Instruction
English
Host Institution Course Number
MATH1041
Host Institution Course Title
STATISTICS FOR LIFE AND SOCIAL SCIENCES
Host Institution Campus
sydney
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematics & Statistics
COURSE DETAIL
QUALITATIVE METHODS
Country
Japan
Host Institution
Meiji Gakuin University
Program(s)
Global Studies, Japan
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
105
UCEAP Course Suffix
Q
UCEAP Official Title
QUALITATIVE METHODS
UCEAP Transcript Title
QUALITATIVE METHODS
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
Qualitative research means research that concentrates on acquiring a subtle, in-depth understanding of a relatively small group of subjects, as opposed to quantitative research, which emphasizes large sample-size and acquisition of statistical data. Qualitative methods are often used by social for anthropological fieldwork, but also for market research, opinion polling and customer satisfaction surveys. This course shows how to acquire high-quality data on social behavior and attitudes. Topics: introduction to social science methods; what is fieldwork; choosing a topic and planning research; writing a research proposal; interview techniques; focus groups; participant observation; alternative methods; from field notes to data; and writing up and interpreting qualitative data. Units: The regular version of this course is worth 3.0 UC quarter units. The Q version of this course is worth 4 or 4.5 UC quarter units. Students must submit a special study project form which outlines the requirements for the additional units. This is typically an additional paper graded by the instructor of the course.
Language(s) of Instruction
English
Host Institution Course Number
KC3030
Host Institution Course Title
QUALITATIVE METHODS
Host Institution Campus
Yokahama
Host Institution Faculty
Host Institution Degree
Host Institution Department
International Studies
COURSE DETAIL
STATISTICAL ESTIMATION I
Country
Spain
Host Institution
Complutense University of Madrid
Program(s)
Complutense University of Madrid
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
122
UCEAP Course Suffix
UCEAP Official Title
STATISTICAL ESTIMATION I
UCEAP Transcript Title
STAT ESTIMATION I
UCEAP Quarter Units
5.00
UCEAP Semester Units
3.30
Course Description
This course discusses parametric estimation and the different techniques of parametric estimation. The course is divided into two units. The first unit covers point estimation including: properties of estimators; estimation of the mean, variance, and proportion of a population; procedures for the construction of estimators. The second unit covers interval estimation including: confidence intervals; pivotal quantity method.
Language(s) of Instruction
Spanish
Host Institution Course Number
801582
Host Institution Course Title
ESTIMACIÓN I
Host Institution Campus
Moncloa
Host Institution Faculty
Facultad de Estudios Estadísticos
Host Institution Degree
GRADO EN ESTADÍSTICA APLICADA
Host Institution Department
Departamento de Estadística y Ciencia de los Datos
COURSE DETAIL
BUSINESS STATISTICS
Country
Hong Kong
Host Institution
Hong Kong University of Science and Technology (HKUST)
Program(s)
Hong Kong University of Science and Technology
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
Business Administration
UCEAP Course Number
25
UCEAP Course Suffix
UCEAP Official Title
BUSINESS STATISTICS
UCEAP Transcript Title
BUSINESS STATISTICS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
The course introduces basic statistical techniques and terminology used in analyzing business data and their application to functional areas of business. The course is divided into seven areas: descriptive statistics, probability and probability distribution, discrete and continuous probability distribution models, sampling distributions, hypothesis testing, two-population inferences, and regression analysis and modeling. Topics covered include collection, tabulation, and presentation of numerical data; concepts of probability and probability distributions; sampling; statistical estimation and hypothesis testing; and correlation and regression analysis.
Language(s) of Instruction
English
Host Institution Course Number
ISOM2500
Host Institution Course Title
BUSINESS STATISTICS
Host Institution Campus
HKUST, Business
Host Institution Faculty
Host Institution Degree
Host Institution Department
Information Systems, Business Statistics, and Operations Management
COURSE DETAIL
MACHINE LEARNING
Country
Italy
Host Institution
University of Commerce Luigi Bocconi
Program(s)
Bocconi University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
Computer Science
UCEAP Course Number
116
UCEAP Course Suffix
UCEAP Official Title
MACHINE LEARNING
UCEAP Transcript Title
MACHINE LEARNING
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course offers an introduction to the fundamental concepts and tools of modern machine learning techniques. These tools are at the root of data science and data analytics, which are among the main pillars of the education program. The course discusses topics including the theory of machine learning; probability tools; statistical interference and regression techniques; unsupervised methods such as Principal Component Analysis, hierarchical cluster, and k-means; supervised methods such as K-nearest neighbors, Support Vector Machines, and Multi-Layer Neural Networks; and associative memories. The course consists of lectures, individual and group assignments, and participation in external competitions. The course requires students to have background knowledge in Python programming, elementary calculus, and basic statistics as a prerequisite.
Language(s) of Instruction
English
Host Institution Course Number
30412
Host Institution Course Title
MACHINE LEARNING
Host Institution Campus
University of Commerce Luigi Bocconi
Host Institution Faculty
Host Institution Degree
Host Institution Department
Decision Sciences
COURSE DETAIL
PROBABILITY AND STATISTICS
Country
Japan
Host Institution
Keio University
Program(s)
Keio University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
145
UCEAP Course Suffix
A
UCEAP Official Title
PROBABILITY AND STATISTICS
UCEAP Transcript Title
PROBABILITY & STAT
UCEAP Quarter Units
3.00
UCEAP Semester Units
2.00
Course Description
The course is an introduction to mathematical statistics, fundamental to econometrics and related areas.
Language(s) of Instruction
English
Host Institution Course Number
N/A
Host Institution Course Title
PROBABILITY & STATISTICS A
Host Institution Campus
Keio University
Host Institution Faculty
Host Institution Degree
Host Institution Department
Economics
COURSE DETAIL
DATA ANALYTICS: LEARNING FROM DATA
Country
Australia
Host Institution
University of Sydney
Program(s)
University of Sydney
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
114
UCEAP Course Suffix
UCEAP Official Title
DATA ANALYTICS: LEARNING FROM DATA
UCEAP Transcript Title
DATA ANALYTICS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This is an intermediate course in statistics and data sciences, teaching data analytic skills for a wide range of problems and data. In this course, students learn how to ingest, combine, and summarize data from a variety of models which are typically encountered in data science projects, and they reinforce their programming skills through experience with statistical programming language. Students are exposed to the concept of statistical machine learning and analyze various types of data in order to answer a scientific question. Students learn to embrace data analytic challenges stemming from everyday problems.
Language(s) of Instruction
English
Host Institution Course Number
DATA2002
Host Institution Course Title
DATA ANALYTICS: LEARNING FROM DATA
Host Institution Campus
sydney
Host Institution Faculty
Host Institution Degree
Host Institution Department
Statistics & Data Science
COURSE DETAIL
STATISTICS: PRINCIPLES, METHODS AND R (I)
Country
China
Host Institution
Fudan University
Program(s)
Fudan University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
123
UCEAP Course Suffix
UCEAP Official Title
STATISTICS: PRINCIPLES, METHODS AND R (I)
UCEAP Transcript Title
STATS: METHODS&R
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
The topics covered in this course include introduction of R, probability, independence, conditional probability, Bayes' formula, random variables and distributions, moment generating functions, probability inequalities, law of large numbers, central limit theorem, point estimation, maximum likelihood estimation, Fisher's information, asymptotic efficiency, Hypothesis testing, Wald's test, t-tests, likelihood ratio tests, permutation tests, confidence intervals.
Language(s) of Instruction
Chinese
Host Institution Course Number
DATA130005
Host Institution Course Title
STATISTICS: PRINCIPLES, METHODS AND R (I)
Host Institution Campus
Host Institution Faculty
Gao Fengnan
Host Institution Degree
Host Institution Department
Data science
COURSE DETAIL
MULTIVARIATE TECHNIQUES FOR DATA ANALYSIS
Country
Spain
Host Institution
Carlos III University of Madrid
Program(s)
Carlos III University of Madrid
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
Business Administration
UCEAP Course Number
113
UCEAP Course Suffix
UCEAP Official Title
MULTIVARIATE TECHNIQUES FOR DATA ANALYSIS
UCEAP Transcript Title
MULTIVAR/DATA ANLS
UCEAP Quarter Units
5.00
UCEAP Semester Units
3.30
Course Description
This course offers an advanced study of business analytics techniques. Topics include: fundamentals of statistical software; multidimensional data; review of elements of statistics; simulation techniques; case studies. Students are expected to have completed coursework in statistics and math for economics.
Language(s) of Instruction
Host Institution Course Number
13179,13475
Host Institution Course Title
TÉCNICAS MULTIVARIANTES DE ANÁLISIS DE DATOS
Host Institution Campus
Getafe
Host Institution Faculty
Facultad de Ciencias Sociales y Jurídicas
Host Institution Degree
Grado en Administración de Empresas
Host Institution Department
Estadística
COURSE DETAIL
INTRODUCTION TO STATISTICS
Country
New Zealand
Host Institution
University of Auckland
Program(s)
University of Auckland
UCEAP Course Level
Lower Division
UCEAP Subject Area(s)
Statistics
UCEAP Course Number
10
UCEAP Course Suffix
UCEAP Official Title
INTRODUCTION TO STATISTICS
UCEAP Transcript Title
INTRO TO STATISTICS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This is an introductory course in statistics intended for students in a wide variety of areas of study. Topics discussed include displaying and describing data, the normal curve, regression, probability, statistical inference, confidence intervals, and hypothesis tests with applications in the real world. Students also have the opportunity to analyze data sets using technology in their weekly laboratory discussions.
Language(s) of Instruction
English
Host Institution Course Number
STATS 101
Host Institution Course Title
INTRODUCTION TO STATISTICS
Host Institution Campus
Auckland
Host Institution Faculty
Host Institution Degree
Host Institution Department
Statistics