Hiroshima University Syllabus

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Academic Year School/Graduate School Lecture Code 2022Year School of Integrated Arts and Sciences Department of Integrated Arts and Sciences ANM01001 Specialized Education データ解析序説 データカイセキジヨセツ Foundation of Date Analysis HASHIMOTO SHINTARO ハシモト　シンタロウ Higashi-Hiroshima 2nd-Year,  Second Semester,  4Term (4T) Thur5-8：IAS K205 Lecture Lecture 2.0 J : Japanese 2 : Undergraduate Low-Intermediate 25 : Science and Technology 01 : Mathematics/Statistics Students who are interested in data analysis Mathematical statistics, Data analysis This course is designed to allow students to understand the basics of mathematical statistics and to learn the meanings of the typical data analysis methods Integrated Arts and Sciences（Knowledge and Understanding）・Knowledge and understanding of the importance and characteristics of each discipline and basic theoretical framework.（Abilities and Skills）・The ability and skills to collect and analyze necessary literature or data among various sources of information on individual academic disciplines.・The ability and skills to specify necessary theories and methods for consideration of issues. Various factors are intertwined in the natural and social phenomena observed in our daily lives. To correctly understand these phenomena, it necessary to summarize the observed data in a simplified form or to examine the relationship between the factors that produce these phenomena. Data analysis is an important tool for this. In this series of lectures, I will introduce the basics of data analysis techniques. Lesson 1: IntroductionLesson 2: Correlation and regressionLesson 3: Definition of probabilityLesson 4: Random variableLesson 5: Probability distributionLesson 6: Multivariate normal distributionLesson 7: Random samplingLesson 8: Limit theoremLesson 9: Point estimation and interval estimationLesson 10: Hypothesis testingLesson 11: Linear regression model（I）Lesson 12: Linear regression model（II）Lesson 13: Logistic regression modelLesson 14: Principle component analysisLesson 15: ClusteringSeveral quiz will be given in the class and a final report will be required. Some reference books will be introduced in the first class. Projector (PC)，your own PC In order to adequately understand the data analysis techniques, it is important to apply them to real data. Prior knowledge of the basics of mathematics (Linear algebra and differential and integral calculus) and statistics is assumed. Class quiz 50% and final report 50%. Please bring your own PC in the class. In the exercise using R programming language, the multivariate data analysis methods are applied to some data. Please fill in the class improvement questionnaire which is carried out on all classes.Instructors will reflect on your feedback and utilize the information for improving their teaching.
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