21 items found.
By the end of the course, students will gain basic understanding of statistics as well as methods to analyze data using statistical software.
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.
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.
Probability and statics are well established branches of mathematics that has applications in all areas of technology today. This course mainly presents a solid foundation for probability and the introduction of statics, explaining its ideas and techniques necessary for a firm understanding of the topic.
We overview differential and integral calculus learned at high school. Our aim is to generalize these to functions of several variables. For functions with one variable, first we extend the concept of tangent (linear approximation) to the theory of Taylor (polynomial approximation). As an application, we can solve the extreme problem in detail. For functions of several valuables, derivative is called partial derivative. We extend the theory of Taylor and the extreme problem to functions with several variables. Moreover, we consider integral of functions of several variables, which is called multiple integral. By using this we can obtain volume and area of high dimensional objects.
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.
We overview differential and integral calculus learned at high school. Our aim is to generalize these to functions of several variables. For functions with one variable, first we extend the concept of tangent (linear approximation) to the theory of Taylor (polynomial approximation). As an application, we can solve the extreme problem in detail. For functions of several valuables, derivative is called partial derivative. We extend the theory of Taylor and the extreme problem to functions with several variables. Moreover, we consider integral of functions of several variables, which is called multiple integral. By using this we can obtain volume and area of high dimensional objects.
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.
We study matrices and vectors, in particular, how to solve the simultaneous equation, how to calculate the determinant and the inverse matrices. Moreover,
by abstracting these concepts, we study linear spaces and linear mapping.
Then a matrix can be regarded as a linear mapping. Especially, eigenvalues and eigenvectors of the matrix, and the matrix diagonalization characterize the mapping. We often encounter these concepts in other mathematical fields including statistics.
We study matrices and vectors, in particular, how to solve the simultaneous equation, how to calculate the determinant and the inverse matrices. Moreover,
by abstracting these concepts, we study linear spaces and linear mapping.
Then a matrix can be regarded as a linear mapping. Especially, eigenvalues and eigenvectors of the matrix, and the matrix diagonalization characterize the mapping. We often encounter these concepts in other mathematical fields including statistics.
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。
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.
This is an introduction to the mathematical theory of probability. We begin with basics of set theory, mathematical logic and combinatorics, based on which we develop probability theory. After introducing the concept of probability, we cover basic topics of probability theory: conditional probability, independency, Bayes' theorem, random variables, probability distributions, expectation, variation, central limit theorem, etc.
We overview differential and integral calculus learned at high school. Our aim is to generalize these to functions of several variables. For functions with one variable, first we extend the concept of tangent (linear approximation) to the theory of Taylor (polynomial approximation). As an application, we can solve the extreme problem in detail. For functions of several valuables, derivative is called partial derivative. We extend the theory of Taylor and the extreme problem to functions with several variables. Moreover, we consider integral of functions of several variables, which is called multiple integral. By using this we can obtain volume and area of high dimensional objects.
We review the calculus studied in a high school and generalize it for functions with several variables. Tangent lines (linear approximation) are generalized to Taylor expansions (polynomial approximation). For their applications, we consider extreme problems. We then study calculus with several variables - partial differentials, extreme problems, and extreme problems with restrains. Furthermore, we refer to multiple integrals and repeated integrals.
We study matrices and vectors, in particular, how to solve the simultaneous equation, how to calculate the determinant and the inverse matrices. Moreover,
by abstracting these concepts, we study linear spaces and linear mapping.
Then a matrix can be regarded as a linear mapping. Especially, eigenvalues and eigenvectors of the matrix, and the matrix diagonalization characterize the mapping. We often encounter these concepts in other mathematical fields including statistics.
行列とベクトルを学習します。連立一次方程式の解法、行列式、逆行列など行列やベクトルに関するいろいろな計算を習得すると共に、線形空間とその間の線形写像という抽象的な概念を理解します。行列は一次変換とみなされ、その固有値と固有ベクトル、行列の対角化はそのは一次変換を特徴付けます。統計学を含む多くの分野で現われる概念です。