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Inha University




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Course Description

* Academic Year
BIO1001 Introductory Biology
This subject is for the non-biology majors and studies the basic knowledge for overall fields of biology. Consider the importance of novel biological phenomena found in various fields of current biological sciences.
CBA1102 Principles of Business Administration
CBA1103 Economics
CHM1023 General Chemistry
‘General Chemistry’ is the course introducing the basic principles of chemistry for undergraduate students majoring non-chemical sciences or engineering. It covers the following topics; The components of matter, Stoichiometry, classes of chemical reactions, Properties of gases, Thermochemistry, Quantum theory and atomic structure, chemical periodicity, Models of chemical bonding, Intermolecular forces, Properties of solutions, Chemical equilibrium, Acid-base equilibria, and Electrochemistry.
FAN1003 Introduction to Food and Nutrition
This course teaches characteristics of foods, characteristics and components of major food groups, and basics of food storage and manufacturing. This course also introduce major nutrients and phytochemicals, including functions in human body and source foods.
GEB1107 English Communication: Pre-Intermediate
This course is a Pre-intermediate level English course for the 1st year students. It is designed to improve students’ communication skills in English in the academic settings.
GEB1108 English Communication: Intermediate
This course is an intermediate level English course for the 1st year students. It is designed to improve students’ communication skills in English in the academic settings.
GEB1109 English Communication: Advanced
This course is an advance level English course for the 1st year students. It is designed to improve students’ communication skills in English in the academic settings.
GEB1111 Inha Freshman Seminar
This seminar is a required course for all freshmen. It is designed to support a successful transition to campus life and provide an opportunity for freshmen to understand their aptitude and potential, and to set academic and career goals. This course focuses on the university’s philosophy and vision, campus life, curriculum and specific features of chosen academic fields, and provides students with the tools for academic success.
GEB1112 Crossover Course 1: Humanities
The series of crossover courses is planned to offer underclassmen the opportunity to explore other academic fields. This course is designed for science and engineering students with a focus on humanities - history, philosophy, and literature. This course provides students with a better understanding of the human experience and nurtures creative and critical thinking skills.
GEB1114 Crossover Course 3: Economics, Business and Law
The series of crossover courses is planned to offer underclassmen the opportunity to explore other academic fields. This course is open to students across all departments with a focus on economics, business and law. This course provides students with the skills and knowledge to become an active member of society and to participate in a professional community.
GEB1124 Writing and Discussion in the Natural Sciences and Engineering
This class will study basic abilities about reading, speaking, and writing. It also intends to cultivate students as cultured people, who have integrated thought capabilities, to learn practical discussion.
GEB1131 Common Chinese Character
This class will study practical Chinese character to meet present-day needs and to develop knowledge as cultured person.
GEB1201 Practical English : Listening and Speaking
The aim of this English listening and speaking course is to challenge students to consider present-day questions in modern society. Students will have many opportunities to improve all areas of their English language skills on the intermediate level.
GEB1202 Practical English: Reading and Writing
The course aims to give English learners practical knowledge of English to help them to adapt to the real work environment. Handsome knowledge of vocabulary, correct use of English language (grammar), understanding of audio-visual materials as well as reading contents, and the ability to write different types of documents or essays are needed to make the goal a real thing. Besides, it aims to help English learners to function properly and actively in the business world in terms of communication.
GEB1203 Advanced College English
This course is an upper-intermediate level English course for the 2nd year students. It is designed to improve students’ proficiency in English so that they can communicate in English based on what they read on various topics.
MTH1001 Calculus 1
MTH1002 Calculus 2
MTH1011 Calculus Recitation 1
MTH1012 Calculus Recitation 2
OCN1005 General Oceanography
This lecture introduces a basic knowledge of the oceans in terms of geology, physics, chemistry and biology in marine environments and provides the dynamic marine processes, which gives an opportunity to understand the oceans for the future of humankind.
PHY1005 General Physics
STS1101 Elementary Statistics I
This course covers the following topics: types of data; describing and summarizing data using plots, tables, and numerical quantities; basic probability theory including calculations of (conditional) probabilities, random variables, probability distributions and expectations; discrete probability distributions; Normal distribution; sampling distribution and central limit theories.
STS1102 Elementary Statistics II
This course covers statistical inference and some useful applications: point estimation and interval estimations; concepts and methods of statistical hypotheses tests including hypotheses, types of errors, test statistics, rejection region, significance level and significance probability; simple linear regression models; one-way analysis of variances; categorical data analysis.
STS1103 Elementary Statistics Lab I
Parallel to Elementary Statistics I, this course is designed to excercise statistical methods studied at Elementary Statistics I using the software, Excel. Drawing plots, charts, making tables and calculating statistical quantities are covered.
STS1104 Elementary Statistics Lab II
Parallel to Elementary Statistics Ⅱ, this course is designed to excercise statistical methods studied at Elementary Statistics Ⅱ using the software, Excel. Statistical inference; linear regression models; analysis of variance; categorical data analyses are covered.
STS1106 Programming Language
The basic structure of programming language(PASCAL, C, etc) and their Logic, Syntax, Semantic are to be studied. Moreover, basic algorithm for problem soving, and Modular Structure Program techniques are to be practiced through Lab exercises using PC or Work-station.
STS2001 Statistical Software and Lab
Designed to introduce students to the languages and conventions required for the use of the leading software systems, SAS and S-Plus, in statistical computing.
STS2004 Regression Analysis
This course covers the following topics: simple linear regression model, multiple linear regression models, properties of least squares estimation, regression diagnostics-detection of model violations, qualitative predictors, transformation of variables, weighted least squares, multi-collinearity problems, variable and model selection.
STS2006 Regression Analysis Lab
Parallel to Regression Analysis, this course is designed to excercise regression analysis methods studied at Regression Analysis using the software, SAS. This course starts with intensive SAS data step exercises and covers regression analysis methods including estimation and prediction, testing, drawing plots, diagnostics, transformation, variable selection.
STS2008 Statistical Computing
We learn many useful statistical algorithms, and apply them to real problems.
STS2017 Methods of Statistical Analysis
This course introduces statistical methods to analyze data sets. The examples are used to illustrate statistical tools including regression analysis, analysis of variance, categorical data analysis and etc.
STS2018 Probability
This course covers the following elementary probability theory: combinatorics and permutation; conditional probabilities; probability distributions including binomial distribution, geometric distribution, Poisson distribution, negative binomial distribution, normal distribution, exponential distribution, gamma distribution; joint probability distribution; (conditional) expectation; large sample theories.
STS2019 Statistical Mathematics
This course is composed of two parts: analysis and linear algebra. The first part covers set theory, convergences of sequence and series, continuity of functions, Taylor expansion, integrations in statistics. The second part covers vector and matrix operations, inverse matrix, vector spaces, basis, rank, eigen vectors and eigen values.
STS2021 Social Research Methods
Learning the basin concepts of social survey, underlying meaning of the survey, how to interprete the output, and a scientific approach to analysyze. Social survey is a part of ssmpling survey, so we have to learn to make connections between the two fields.
STS2040 Database
Introduction to database concepts, data models (relational, hierarchical, and network models), data manipulation languages, data description languages, system implementation issues, security and data integrity.
STS2041 Data Structure
An object-oriented approach to data structure and algorithms. Object-oriented programming. Program correctness. Stacks, queues, trees, searching, sorting, analysis of algorithms, graphs, and file processing emphasis on writing and programs.
STS2044 Statistical Computing Lab
This course is for practicing statistical algorithms using R (or C) language. Basic matrix analysis, Monte-Carlo algorithms, variance reduction techniques and optimization algorithms are main topics.
STS3003 Experimental Design (Capstone Design)
The main role of the course of Experimental Design is to planning and conducting experiments so that valid and objective conclusions are obtained through the studying statistical principles and techniques of experiment.
STS3005 Mathematical Statistics I
Basic concepts of probability, discrete and continuous random variables, random samples, limiting distributions, and estimation are covered.
STS3012 Time Series Analysis and Lab
Methods for analyzing data collected over time; review of multiple regression analysis. Elementary forecasting methods: moving averages and exponential smoothing. Autoregressive-moving average (Box-Jenkins) models: identification, estimation, diagnostic checking, and forecasting. Transfer function models and intervention analysis.
STS3014 Sampling Theory and Lab
Understaing the basic concepts of survey sampling via 4 fundamental sampling design, simple random sampling, stratified random sampling, systematic random sampling, cluster random sampling. Also studying the various errors of sampling, sampling error and nonsmapling error. Learning how to determine efficient sample size, which is the key to conduct the survey.
STS3015 Experimental Design Lab
Generating experimental designs and analyzing data with statistical software so that the significant factors are identified and optimum results are obtain.
STS3016 Categorical Data Analysis
We study statistical models to deal with discrete data such as log-linear model and logit model. Parameter interpretation, statistical estimation, hypothesis testing and model diagnostic for those models are important topics, and we analyze various contingency tables. Some discussion of exact small-sample problem will be provided.
STS3019 Multivariate Statistics and Lab
Emphasis is on concepts and computer-intensive methods. Topics include comparisons of mean vectors, multivariate linear regression models, principal components, factor analysis, canonical correlation, and etc.
STS3030 Actuarial Statistics I
Based on understaning the basic conceppts of interest theory, annuity certain, life insurance, benefit reserve will be studied. Determining the parcing of premium of various insurance policy will be the key goal during this course. Two approach will be studied to achieve the above goals. One is probabilistic approach and the other is a deterministic approach based on computational formula.
STS3050 Statistical Quality Control
Concepts and methods for process and acceptance control. Control charts for variables and methods for process and acceptance control; acceptance sampling. Continuous sampling plans. Life tests. Use of experimental design and Taguchi methods for offline control.
STS3060 Mathematical Statistics II
Various estimation methods, confidence intervals, hypotheses testing, theory for categorical data analyses, and non-parametric statistics are covered.
STS4010 Nonparametric Statistics
Statistical methods derived without any distributional assumptions are studied. Topics that we cover are binomial test, quantize test, sign test, contingency tables, methods based on ranks and Kolmogorov-Smirnov type test.
STS4011 Introduction to stochastic process
This course covers the following topics: conditional probabilities, conditional expectation, random graph, Markov chain, Chapman and Kolmogorov’s equation, limiting probability, branching process, decision process with Markov chain, counting process, relationship between exponential distribution and Poisson process, waiting time
STS4020 Statistical Consultation
Practical consulting on real world statistical problems. Under the supervision, students hear problems presented by clients and collaborate in proposing statistical methods, analysing the data, and interpreting results. Statistical computing will be used as needed.
STS4021 Data Analysis for capstone design
Emphasized topics include data analysis, problem solving, report writing, and communication skills (e.g., presentations) Statistical methodologies such as exploratory data analysis, linear regression, experimental design, and multivariate analysis
STS4022 Topics in Applied Statistics
This course is designed to introduce various types of data sets and applicable analyzing methods. Using basic statistical analyzing tools we learn to extract meaningful information from data.
STS4026 Bio-informatics
Due to the rapid growth in the field of Bio-engineering, huge amount of gene and protein information accumulation force us to store those information more systemetically into database. More important task than just storing is how to extract useful information from such a massive data set. This course focuses on developing statistical techniques necessary to analyse gene expression data efficiently. Brief introduction of genetics and probability theory will be handled and computing program skills
STS4027 Directed Research in Statistics
Select from the list of topics suggested by professors and work together to solve various challenging statistical problems and thereafter completing a research report.
STS4031 Actuarial Statistics II
Based on the acturial statistic-I , learning the advanced theory of risk theory based benefit reserve and net annual premium and several survial models will be studied. Multiple decrement models also will be dealt with based on probability based approach.
STS4033 Financial Statistics
This course covers statistical tools for financial derivatives. Basic terminology, mechanics of options and futures markets, and pricing model for option and futures will be taught.
STS4034 Survival Analysis and Lab
We learn basic concepts (censoring, truncation) frequently used in survival analysis, and study statistical techniques such as Kaplan-Meier curve and Cox’s proportional hazard model. Various real applications will be provided.
STS4035 Statistics for risk management
Learning about the life-time distribution and loss-type distribution, which are the basic ingredients of risk theory. Individual risk modelling and group risk theory will also be dealt with in this course. Credibility theory will be studied, espiciallt Buhlmann-Straub Credibility Model will be studied in details. Finally general insurance thoery will be briefly introduced.
STS4042 Data Mining(Capstone Design)
Decision theory based on traditional methods and the Bayesian decision theory will be introduced sude by side. Learing how to formulate given problem in terms of Bayesian context and how to solve and find a maximum output. Optimization theory based on several criterion will be studied and their performances.
STS4043 Data Mining
This course focuses on classification, association, clustering and exploration of the volume data. The main topics are neural network and decision tree.
STS4044 Big Data Analysis
We introduce the basic concept of big-data, and study how to manage and analyze it. Various statistical algorithms and analysis techniques for big-data will be provided. Real challenges in the field will be illustrated with big-data problems from various areas such as manufacturing business and medical science.
STS4051 Reliability theory
Several probability distributions models will be studied to handle the reliability theory. Especially, parametric models like exponential model, Weibull model, log-normal model, and so forth will be studied case by case. Testing life under several censored or truncated situation will be introduced. Computing avalibility and maintanability will also be studied and the renewal process will bw briefly introduced to handle reliability processes.
STS4053 6- sigma quality management
The concepts, background, and theoretical facets of Six sigma; Phases of Six Sigma such as Define, Measure, Analyze, Improve, and Control; Case studies will be emphasized and discussed in the class.
STS4432 Financial data analysis
This course focus on the empirical statistical techniques used most often in the analysis of financial markets. Especially, how they are applied to actual market data will be learned in the class.
STS9423 Statistics field work 1
STS9427 Statistics field work 2
STS9428 Statistics field work 3
STS9429 Statistics Fields Work 5
INHA UNIVERSITY, 100 Inharo, Nam-gu Incheon 22212, KOREA Tel : +82-32-860-7114, Fax : +82-32-863-1333