COURSE SYLLABUS QUANTITATIVE ANALYSIS Course code: VJU6311 Number of credits: 02 Prerequisite courses: None Teaching language: English Lecturers 5.1 Lecturer 1: (Yasushi Narushima; Associate Professor; Dr (Sci); Yokohama National University) 5.2 Lecturer 2: (Tohru Inoue; Professor; Master（Econ）; Yokohama National University) Course objective This course introduces scientific approaches using in various situation of the corporate management Students will learn basic contents of scientific approaches and get skills to solve problems to support business decision making Expected learning outcomes 7.1 Knowledge competence Students will be introduced basic contents of scientific approaches This includes Mathematical programming Data Description Statistical Inference 7.2 Skills Students will get problem-solving skills using scientific approaches This includes Formulation of managerial issues as mathematical or statistic models Solve the formulated problems by using scientific methods Analyze managerial issues by using the solutions of mathematical or statistic models 7.3 Ethics Solve and analyze managerial issues by using spreadsheet Assessment methods/Grading system 8.1 Attendance & class participation Regular attendance and participation in class discussion will account for 20% of the class grade 8.2 Midterm & final exams Students will be evaluated based on their homework submitted to the lecturer The grade will count for 20% of the class grade A writing exam will be given at the end of the class The grade will account for 60% of the class grade Leaning materials 9.1 Required textbook and other material: none 9.2 Reference material Hillier and Hillier, Introduction to Management Science, McGraw-Hill, 2004 David M Lane, et.al., Introduction to Statistics (on line edition), http://onlinestatbook.com/Online_Statistics_Education.pdf 10 Course description Students will learn basic contents of scientific approach in various situation of the corporate management Student will get skills that they formulate managerial issues as resource allocation problem or decision making problem Moreover, they will learn scientific method for solving the formulated problem 11 Course contents Part Class1 Describing Data The Properties of the Variable : Study Frequency Distribution, Tendency and Dispersion Class Describing Data The Relation between the Variables : Study Scatter gram, Covariance and Correlation Class Introduction of Statistical Inference : Study Population and Sample Sample Distribution and Central Limit Theorem Class Estimation : Study Point Estimation and Interval Estimation Class Hypothesis Testing : Study Hypothesis Testing for the Population Mean, for the Population Proportion, for the Difference between Two Populations Means Class Analysis of Variance (ANOVA) : Study Way ANOVA and way ANOVA Class Regression Analysis : Study Simple Linear Regression and Multiple Regression Class Exercise and Midterm Examination Part Class Linear Programming Study formulations and basic concepts of the linear programming Class Linear Programming Study modeling with spreadsheets, and get skills to solve the formulated problems Class Linear Programming Study basic concepts of What-If analysis to analyze managerial issues Class Transportation and Assignment Problems As applications of linear programming problems, study transportation and assignment problems Class Integer Programming Study integer programming Formulate 0-1 decision problem as binary integer programming Class Nonlinear Programming Study basic concepts of nonlinear programming Class Nonlinear Programming Study applications of nonlinear programming Class Final Examination Note: The course of study can be changed according to the background of the students ... methods/Grading system 8.1 Attendance & class participation Regular attendance and participation in class discussion will account for 20% of the class grade 8.2 Midterm & final exams Students will be