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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

The mean values

The mean values

Probabilistic Models. Chapter 11

Probabilistic Models. Chapter 11

Hypothesis Testing with Two Samples

Hypothesis Testing with Two Samples

Matrices - Introduction. Lecture 1-3

Matrices - Introduction. Lecture 1-3

Correlation and Regression

Correlation and Regression

Forecasting with bayesian techniques MP

Forecasting with bayesian techniques MP

Discrete mathematics. Sets

Discrete mathematics. Sets

Correlation and regression

Correlation and regression

Boolean algebra. Logic operations. Formula and their conversion

Boolean algebra. Logic operations. Formula and their conversion

Descriptive statistics

Descriptive statistics

Geometric Modeling - Parametric Representation of Synthetic Curves

Geometric Modeling - Parametric Representation of Synthetic Curves

Confidence interval estimation

Confidence interval estimation

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)

Descriptive statistics. Frequency distributions and their graphs. (Section 2.1)

Descriptive statistics. Frequency distributions and their graphs. (Section 2.1)

Statistics. Data Description. Data Summarization. Numerical Measures of the Data

Statistics. Data Description. Data Summarization. Numerical Measures of the Data

Combinational logic design

Combinational logic design

Discrete Mathematics Sets

Discrete Mathematics Sets

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)

Solution Methods Applied Computational Fluid Dynamics. Lecture 5

Solution Methods Applied Computational Fluid Dynamics. Lecture 5

Inverse of a Square Matrix

Inverse of a Square Matrix

N-ary relations and their applications. (Rosen 8.2)

N-ary relations and their applications. (Rosen 8.2)

Normal Probability Distributions

Normal Probability Distributions

Exploring Assumptions Normality and Homogeneity of Variance

Exploring Assumptions Normality and Homogeneity of Variance

Hypothesis testing

Hypothesis testing

$Wide-angle X-ray scattering (WAXS) geometries. In-plane diffraction geometry$

Wide-angle X-ray scattering (WAXS) geometries. In-plane diffraction geometry

Exponentials and logarithms. Lecture 2.1

Exponentials and logarithms. Lecture 2.1

4.2 Introduction to Limits

4.2 Introduction to Limits

Descriptive statistics. Elementary statistics. Larson. Farber. (Chapter 2)

Descriptive statistics. Elementary statistics. Larson. Farber. (Chapter 2)

Random variables – discrete random variables. Week 6 (2)

Random variables – discrete random variables. Week 6 (2)

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)

$Index of Refraction$

Index of Refraction

Sequential games. (Lecture 4)

Sequential games. (Lecture 4)

The travelling salesman problem

The travelling salesman problem

Using first derivative. Using second derivative

Using first derivative. Using second derivative

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

Theory without practice is empty, practice without theory is blind

Theory without practice is empty, practice without theory is blind

Introduction to normal distributions

Introduction to normal distributions

Chapter 3. Polynomial and Rational Functions. 3.4 Zeros of Polynomial Functions

Chapter 3. Polynomial and Rational Functions. 3.4 Zeros of Polynomial Functions

Binary Variables

Binary Variables

Mixed strategy Nash equilibrium. (Lecture 3)

Mixed strategy Nash equilibrium. (Lecture 3)

Measures of variation. Week 4 (2)

Measures of variation. Week 4 (2)

Modelling with Exponentials and Logarithms

Modelling with Exponentials and Logarithms

Modelling with exponentials and logarithms

Modelling with exponentials and logarithms

Evolutionary games. (Lecture 7)

Evolutionary games. (Lecture 7)

CENG 789 – Digital Geometry Processing

CENG 789 – Digital Geometry Processing

Scalars, vectors and tensors

Scalars, vectors and tensors

Object tracking using particle filter

Object tracking using particle filter

Discrete Probability Distributions: Binomial and Poisson Distribution. Week 7 (2)

Discrete Probability Distributions: Binomial and Poisson Distribution. Week 7 (2)

Types of Data – (continued). Week 2 (2)

Types of Data – (continued). Week 2 (2)

Stolz-Cesaro Theorem

Stolz-Cesaro Theorem

Math end algebra. Vector

Math end algebra. Vector

Basic arithmetic

Basic arithmetic

Matrix Equations and Systems of Linear Equations

Matrix Equations and Systems of Linear Equations

Sampling in quantitative research

Sampling in quantitative research

Auctions. (Lecture 10)

Auctions. (Lecture 10)

Measures of variation. Week 4 (1)

Measures of variation. Week 4 (1)

Recitation class

Recitation class

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

Economics of pricing and decision making. (Lecture 1)

Economics of pricing and decision making. (Lecture 1)

Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions

Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions

Differentiation. A “derivative”,

Differentiation. A “derivative”,

Sequential games. Empirical evidence and bargaining. (Lecture 5)

Sequential games. Empirical evidence and bargaining. (Lecture 5)

Simultaneous games. Oligopoly. (Lecture 2)

Simultaneous games. Oligopoly. (Lecture 2)

Probability theory. Probability Distributions Statistical Entropy

Probability theory. Probability Distributions Statistical Entropy

Discrete mathematics. Probability

Discrete mathematics. Probability

Introductory Statistics 1. AP Statistics

Introductory Statistics 1. AP Statistics

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)

Сумма и разность синусов и косинусов

Сумма и разность синусов и косинусов

Trigonometriýa

Repeated games. (Lecture 6)

Repeated games. (Lecture 6)

Introduction to Statistics

Introduction to Statistics

Types of Data – categorical data. Week 2 (1)

Types of Data – categorical data. Week 2 (1)

Probability Random Variables Preparatory Notes

Probability Random Variables Preparatory Notes

Propositional logic

Propositional logic

Graph transformation 1

Graph transformation 1

Foundation Year Program NUFYP Mathematics

Foundation Year Program NUFYP Mathematics

3.5 Trigonometry 5

3.5 Trigonometry 5

Differentiation. Sketching functions

Differentiation. Sketching functions

Communication and signaling. (Lecture 8)

Communication and signaling. (Lecture 8)

Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication

Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication

Mechanism design. (Lecture 9)

Mechanism design. (Lecture 9)

Correlation Regression

Correlation Regression

Empirical rule - Probabilities. Week 5 (1)

Empirical rule - Probabilities. Week 5 (1)

Displaying data – shape of distributions. Week 3 (1)

Displaying data – shape of distributions. Week 3 (1)

Matlab Linear Programming

Matlab Linear Programming

Practical application of the method of Kona-Shema. Pseudopotentials method

Practical application of the method of Kona-Shema. Pseudopotentials method

Expert judgment method. (Lecture 1-4)

Expert judgment method. (Lecture 1-4)

Vectors and the geometry of space

Vectors and the geometry of space

Matrices: Basic Operations

Matrices: Basic Operations

Arithmetic fundamentals of number systems

Arithmetic fundamentals of number systems

Elements of probability. (Lecture 3)

Elements of probability. (Lecture 3)

Probabilities. Week 5 (2)

Probabilities. Week 5 (2)

Random variables

Random variables

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