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We will learn about the properties of vectors and matrices as these are basic concepts. We will also learn how to solve simultaneous equations using matrices. After that, we will learn about the uses of linear algebra used in our lives, including applications to technology such as computer search, computer graphics, error correction and quantum computing. Linear algebra is among the most fundamental and useful fields of mathematics, and the material here will benefit learners in many other classes at SFC.
この授業で、データの操作と解釈の基礎を習得します。統計学を勉強したことのない学生を対象としています。学生の研究やキャリアに活用出来ることを目的として、統計学の概念・手法・ 最良の実践を中心に授業を展開していきます。「数学が苦手」と思っている学生に特に勧められます。
具体的に、データの種類・データ収集・データの記述・関係の分析・確率・仮説検定・相違の分析を扱います。
By the end of the course, students will gain basic understanding of statistics as well as methods to analyze data using statistical software.
This class is an introduction to calculus. Differential and integral calculus is a theory for analyzing changes and accumulations of targets, respectively, and has many applications in data science, economics, science and engineering, etc. In fact, calculus and linear algebra are considered as the most important mathematics at universities. In this class, we will learn not only calculus of one variable functions but also polynomial approximation of one variable functions and calculus of multivariate functions.
This course will cover fundamentals of calculus, which is essentially important for various research fields. Beginning with some preliminaries, we will study derivatives and integrals. For either topic, we will start from single function, and then it will be extended to multiple functions. A number of practices are prepared for deeper understanding and practical usage of derivatives and integrals.
この授業で、データの操作と解釈の基礎を習得します。統計学を勉強したことのない学生を対象としています。学生の研究やキャリアに活用出来ることを目的として、統計学の概念・手法・ 最良の実践を中心に授業を展開していきます。「数学が苦手」と思っている学生に特に勧められます。
具体的に、データの種類・データ収集・データの記述・関係の分析・確率・仮説検定・相違の分析を扱います。
By the end of the course, students will gain basic understanding of statistics as well as methods to analyze data using statistical software.
This class is an introduction to calculus. Differential and integral calculus is a theory for analyzing changes and accumulations of targets, respectively, and has many applications in data science, economics, science and engineering, etc. In fact, calculus and linear algebra are considered as the most important mathematics at universities. In this class, we will learn not only calculus of one variable functions but also polynomial approximation of one variable functions and calculus of multivariate functions.
This course will cover fundamentals of calculus, which is essentially important for various research fields. Beginning with some preliminaries, we will study derivatives and integrals. For either topic, we will start from single function, and then it will be extended to multiple functions. A number of practices are prepared for deeper understanding and practical usage of derivatives and integrals.
By the end of the course, students will gain basic understanding of statistics as well as methods to analyze data using statistical software.
This class is an introduction to calculus. Differential and integral calculus is a theory for analyzing changes and accumulations of targets, respectively, and has many applications in data science, economics, science and engineering, etc. In fact, calculus and linear algebra are considered as the most important mathematics at universities. In this class, we will learn not only calculus of one variable functions but also polynomial approximation of one variable functions and calculus of multivariate functions.
This course will cover fundamentals of calculus, which is essentially important for various research fields. Beginning with some preliminaries, we will study derivatives and integrals. For either topic, we will start from single function, and then it will be extended to multiple functions. A number of practices are prepared for deeper understanding and practical usage of derivatives and integrals.
この授業で、データの操作と解釈の基礎を習得します。統計学を勉強したことのない学生を対象としています。学生の研究やキャリアに活用出来ることを目的として、統計学の概念・手法・ 最良の実践を中心に授業を展開していきます。「数学が苦手」と思っている学生に特に勧められます。
具体的に、データの種類・データ収集・データの記述・関係の分析・確率・仮説検定・相違の分析を扱います。
This class is an introduction to linear algebra. Linear algebra is a theory about vectors and matrices, and has many applications in data science, economics, engineering etc. In fact, linear algebra and calculus are considered as the most important mathematics at universities. In this class, we will learn the basic ideas of linear algebra from both algebraic and geometric point of views.
This class is an introduction to linear algebra. Linear algebra is a theory about vectors and matrices, and has many applications in data science, economics, engineering etc. In fact, linear algebra and calculus are considered as the most important mathematics at universities. In this class, we will learn the basic ideas of linear algebra from both algebraic and geometric point of views.
This class is an introduction to linear algebra. Linear algebra is a theory about vectors and matrices, and has many applications in data science, economics, engineering etc. In fact, linear algebra and calculus are considered as the most important mathematics at universities. In this class, we will learn the basic ideas of linear algebra from both algebraic and geometric point of views.
In this class, students are expected to study about basic statistics by analyzing data empirically. Basic techniques such as data collection, statistical analysis and presentation are introduced.
Lectures include (1) description of data such as average, variance and correlation, (2) basics of probability theories such as population and samples, stochastic distributions and sample distributions, and (3) statistical models such as regression analysis and analysis of variance.
Lecturers might change contents of syllabus.
In this class, students are expected to study about basic statistics by analyzing data empirically. Basic techniques such as data collection, statistical analysis and presentation are introduced.
Lectures include (1) description of data such as average, variance and correlation, (2) basics of probability theories such as population and samples, stochastic distributions and sample distributions, and (3) statistical models such as regression analysis and analysis of variance.
Lecturers might change contents of syllabus.
In the first half we study set theory and mathematical logic. These are useful of logical thinking. In the latter half we study probability. We overview permutation and combination, which you have learned at high school, and then, we study probability. Our goal is Bayesian Theory. This is new for all. Mathematics in university is different from one in high school. Even if you are no good at calculation and memory, you have a chance to enjoy mathematics in university.
In the first half we study set theory and mathematical logic. These are useful of logical thinking. In the latter half we study probability. We overview permutation and combination, which you have learned at high school, and then, we study probability. Our goal is Bayesian Theory. This is new for all. Mathematics in university is different from one in high school. Even if you are no good at calculation and memory, you have a chance to enjoy mathematics in university.
This class is an introduction to probability. Probability is a theory that quantifies uncertain phenomena and is the fundamental mathematics in a wide range of fields such as data science, economics, and engineering. After covering some basics of probability (joint probability, conditional probability, Baye's theorem etc), we will learn quantitate aspects of probability distributions (random variable, expectation values, variance etc).
This class is an introduction to probability. Probability is a theory that quantifies uncertain phenomena and is the fundamental mathematics in a wide range of fields such as data science, economics, and engineering. After covering some basics of probability (joint probability, conditional probability, Baye's theorem etc), we will learn quantitate aspects of probability distributions (random variable, expectation values, variance etc).
In the first half we study set theory and mathematical logic. These are useful of logical thinking. In the latter half we study probability. We overview permutation and combination, which you have learned at high school, and then, we study probability. Our goal is Bayesian Theory. This is new for all. Mathematics in university is different from one in high school. Even if you are no good at calculation and memory, you have a chance to enjoy mathematics in university.
In the first half we study set theory and mathematical logic. These are useful of logical thinking. In the latter half we study probability. We overview permutation and combination, which you have learned at high school, and then, we study probability. Our goal is Bayesian Theory. This is new for all. Mathematics in university is different from one in high school. Even if you are no good at calculation and memory, you have a chance to enjoy mathematics in university.
This class is an introduction to probability. Probability is a theory that quantifies uncertain phenomena and is the fundamental mathematics in a wide range of fields such as data science, economics, and engineering. After covering some basics of probability (joint probability, conditional probability, Baye's theorem etc), we will learn quantitate aspects of probability distributions (random variable, expectation values, variance etc).