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Лучшие презентации на тему «Математика» на английском
Cmpe 466 computer graphics. 3D geometric transformations. (Сhapter 9)
Cmpe 466 computer graphics. 3D geometric transformations. (Сhapter 9)
Modeling non-stationary variables
Modeling non-stationary variables
Wide-angle X-ray scattering (WAXS) geometries. In-plane diffraction geometry
Wide-angle X-ray scattering (WAXS) geometries. In-plane diffraction geometry
Discrete Mathematics Sets
Discrete Mathematics Sets
Forecasting with bayesian techniques MP
Forecasting with bayesian techniques MP
Решение уравнений sinx=a. Понятие арксинуса числа
Решение уравнений sinx=a. Понятие арксинуса числа
The mean values
The mean values
Probabilistic Models. Chapter 11
Probabilistic Models. Chapter 11
Combinational logic design
Combinational logic design
Theory without practice is empty, practice without theory is blind
Theory without practice is empty, practice without theory is blind
Evolutionary games. (Lecture 7)
Evolutionary games. (Lecture 7)
The travelling salesman problem
The travelling salesman problem
Sequential games. (Lecture 4)
Sequential games. (Lecture 4)
Recitation class
Recitation class
Correlation and Regression
Correlation and Regression
Object tracking using particle filter
Object tracking using particle filter
N-ary relations and their applications. (Rosen 8.2)
N-ary relations and their applications. (Rosen 8.2)
Geometric Modeling - Parametric Representation of Synthetic Curves
Geometric Modeling - Parametric Representation of Synthetic Curves
Boolean algebra. Logic operations. Formula and their conversion
Boolean algebra. Logic operations. Formula and their conversion
Repeated games. (Lecture 6)
Repeated games. (Lecture 6)
Statistics. Data Description. Data Summarization. Numerical Measures of the Data
Statistics. Data Description. Data Summarization. Numerical Measures of the Data
Mechanism design. (Lecture 9)
Mechanism design. (Lecture 9)
Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions
Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions
Chapter 3. Polynomial and Rational Functions. 3.2 Polynomial Functions and Their Graphs
Chapter 3. Polynomial and Rational Functions. 3.2 Polynomial Functions and Their Graphs
Simultaneous games. Oligopoly. (Lecture 2)
Simultaneous games. Oligopoly. (Lecture 2)
Descriptive statistics. Elementary statistics. Larson. Farber. (Chapter 2)
Descriptive statistics. Elementary statistics. Larson. Farber. (Chapter 2)
Chapter 3. Polynomial and Rational Functions. 3.4 Zeros of Polynomial Functions
Chapter 3. Polynomial and Rational Functions. 3.4 Zeros of Polynomial Functions
Evolutionary game theory. (Lecture 11)
Evolutionary game theory. (Lecture 11)
Solving linear recurrence relations
Solving linear recurrence relations
Confidence interval and Hypothesis testing for population mean (µ) when is known and n (large)
Confidence interval and Hypothesis testing for population mean (µ) when is known and n (large)
Correlation and regression
Correlation and regression
Arithmetic fundamentals of number systems
Arithmetic fundamentals of number systems
Sequential games. Empirical evidence and bargaining. (Lecture 5)
Sequential games. Empirical evidence and bargaining. (Lecture 5)
Descriptive statistics. Frequency distributions and their graphs. (Section 2.1)
Descriptive statistics. Frequency distributions and their graphs. (Section 2.1)
Trigonometriýa
Trigonometriýa
The Aerodynamics Of A Single-Blade Rotor
The Aerodynamics Of A Single-Blade Rotor
Mathematics for Computing. Lecture 2: Logarithms and indices
Mathematics for Computing. Lecture 2: Logarithms and indices
Elements of probability. (Lecture 3)
Elements of probability. (Lecture 3)
Discrete random variables – expected variance and standard deviation. Discrete Probability Distributions. Week 7 (1)
Discrete random variables – expected variance and standard deviation. Discrete Probability Distributions. Week 7 (1)
Drawing triangles
Drawing triangles
Ryspekov’s Fibonacci sequence formula Global Revival
Ryspekov’s Fibonacci sequence formula Global Revival
Mathematics for Computing 2016-2017. Lecture 1: Course Introduction and Numerical Representation
Mathematics for Computing 2016-2017. Lecture 1: Course Introduction and Numerical Representation
Auctions. (Lecture 10)
Auctions. (Lecture 10)
Calculating the probability of a continuous random variable – Normal Distribution. Week 9 (1)
Calculating the probability of a continuous random variable – Normal Distribution. Week 9 (1)
Descriptive statistics
Descriptive statistics
Random variables
Random variables
Probability Concepts
Probability Concepts
Communication and signaling. (Lecture 8)
Communication and signaling. (Lecture 8)
Math end algebra. Vector
Math end algebra. Vector
Discrete mathematics. Probability
Discrete mathematics. Probability
ორი სიბრტყის თანაკვეთა
ორი სიბრტყის თანაკვეთა
Mixed strategy Nash equilibrium. (Lecture 3)
Mixed strategy Nash equilibrium. (Lecture 3)
Digital Image Stabilization
Digital Image Stabilization
Quiz 1
Quiz 1
Time quiz
Time quiz
Measures of variation. Week 4 (2)
Measures of variation. Week 4 (2)
Graph theory irina prosvirnina. Definitions and examples. Paths and cycles
Graph theory irina prosvirnina. Definitions and examples. Paths and cycles
Irrational Numbers
Irrational Numbers
Methods of proof
Methods of proof
Inverse of a Square Matrix
Inverse of a Square Matrix
Matrix Equations and Systems of Linear Equations
Matrix Equations and Systems of Linear Equations
Parametric Linear Programming
Parametric Linear Programming
Functions and graphs. Chapter 2. Combinations of functions; composite functions
Functions and graphs. Chapter 2. Combinations of functions; composite functions
The binomial model for option pricing
The binomial model for option pricing
Количественные и порядковые числительные
Количественные и порядковые числительные
Index of Refraction
Index of Refraction
Displaying data – shape of distributions. Week 3 (1)
Displaying data – shape of distributions. Week 3 (1)
Measures of variation. Week 4 (1)
Measures of variation. Week 4 (1)
Random variables – discrete random variables. Week 6 (2)
Random variables – discrete random variables. Week 6 (2)
Introduction to normal distributions
Introduction to normal distributions
Hypothesis Testing with Two Samples
Hypothesis Testing with Two Samples
Basics of functions and their graphs
Basics of functions and their graphs
Intro to Geometric Modeling (GM)
Intro to Geometric Modeling (GM)
Economics of pricing and decision making. (Lecture 1)
Economics of pricing and decision making. (Lecture 1)
Time series models. Static models and models with lags
Time series models. Static models and models with lags
Sampling in quantitative research
Sampling in quantitative research
Mathematics for еconomists. (Week 1-12)
Mathematics for еconomists. (Week 1-12)
Chapter 1. Polynomial and Rational Functions. 3.3. Dividing Polynomials; Remainder and Factor Theorems
Chapter 1. Polynomial and Rational Functions. 3.3. Dividing Polynomials; Remainder and Factor Theorems
Empirical rule - Probabilities. Week 5 (1)
Empirical rule - Probabilities. Week 5 (1)
Conditional Probabilities Statistical Independence. Week 6 (1)
Conditional Probabilities Statistical Independence. Week 6 (1)
Ryspekov’s Fibonacci sequence formula
Ryspekov’s Fibonacci sequence formula
Discrete mathematics. Sets
Discrete mathematics. Sets
Panel.Methods
Panel.Methods
Introduction to Statistics. Week 1 (2)
Introduction to Statistics. Week 1 (2)
Introduction to Statistics. Week 1 (1)
Introduction to Statistics. Week 1 (1)
Types of Data – categorical data. Week 2 (1)
Types of Data – categorical data. Week 2 (1)
Types of Data – (continued). Week 2 (2)
Types of Data – (continued). Week 2 (2)
Using numerical measures to describe data. Measures of the center. Week 3 (2)
Using numerical measures to describe data. Measures of the center. Week 3 (2)
George Boole
George Boole
An over view of statistics
An over view of statistics
The Gilbert-Johnson-Keerthi (GJK) Algorithm
The Gilbert-Johnson-Keerthi (GJK) Algorithm
Collision Detection
Collision Detection
Derivatives of Products and Quotients
Derivatives of Products and Quotients
Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication
Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication
Common Probability Distributions
Common Probability Distributions
Probability theory. Probability Distributions Statistical Entropy
Probability theory. Probability Distributions Statistical Entropy
Mathematical Induction
Mathematical Induction
The Taylor Formula
The Taylor Formula
Mathematical Induction
Mathematical Induction
Hypothesis testing
Hypothesis testing
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