Лучшие презентации на тему «Математика» на английском

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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

Matrices - Introduction. Lecture 1-3

Matrices - Introduction. Lecture 1-3

Correlation and Regression

Correlation and Regression

Solution Methods Applied Computational Fluid Dynamics. Lecture 5

Solution Methods Applied Computational Fluid Dynamics. Lecture 5

Probabilistic Models. Chapter 11

Probabilistic Models. Chapter 11

The mean values

The mean values

Hypothesis Testing with Two Samples

Hypothesis Testing with Two Samples

Correlation and regression

Correlation and regression

Confidence interval estimation

Confidence interval estimation

Geometric Modeling - Parametric Representation of Synthetic Curves

Geometric Modeling - Parametric Representation of Synthetic Curves

Discrete mathematics. Sets

Discrete mathematics. Sets

Boolean algebra. Logic operations. Formula and their conversion

Boolean algebra. Logic operations. Formula and their conversion

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

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

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

Descriptive statistics

Exploring Assumptions Normality and Homogeneity of Variance

Exploring Assumptions Normality and Homogeneity of Variance

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

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

Forecasting with bayesian techniques MP

Forecasting with bayesian techniques MP

Normal Probability Distributions

Normal Probability Distributions

Combinational logic design

Combinational logic design

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

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

Inverse of a Square Matrix

Inverse of a Square Matrix

Exponentials and logarithms. Lecture 2.1

Exponentials and logarithms. Lecture 2.1

Discrete Mathematics Sets

Discrete Mathematics Sets

Hypothesis testing

Hypothesis testing

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

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

Introduction to normal distributions

Introduction to normal distributions

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)

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

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

Binary Variables

Binary Variables

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

$Index of Refraction$

Index of Refraction

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

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

4.2 Introduction to Limits

4.2 Introduction to Limits

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

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

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)

Mixed strategy Nash equilibrium. (Lecture 3)

Mixed strategy Nash equilibrium. (Lecture 3)

Using first derivative. Using second derivative

Using first derivative. Using second derivative

Math end algebra. Vector

Math end algebra. Vector

Method of undetermined coefficients

Method of undetermined coefficients

Modelling with Exponentials and Logarithms

Modelling with Exponentials and Logarithms

Modelling with exponentials and logarithms

Modelling with exponentials and logarithms

Scalars, vectors and tensors

Scalars, vectors and tensors

Measures of variation. Week 4 (2)

Measures of variation. Week 4 (2)

Stolz-Cesaro Theorem

Stolz-Cesaro Theorem

Theory without practice is empty, practice without theory is blind

Theory without practice is empty, practice without theory is blind

Basic arithmetic

Basic arithmetic

Ch8: Hypothesis Testing (2 Samples)

Ch8: Hypothesis Testing (2 Samples)

Sampling in quantitative research

Sampling in quantitative research

Measures of variation. Week 4 (1)

Measures of variation. Week 4 (1)

Probability Random Variables Preparatory Notes

Probability Random Variables Preparatory Notes

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

Introduction to Statistics

Introduction to Statistics

Random variables

Random variables

Object tracking using particle filter

Object tracking using particle filter

Sequential games. (Lecture 4)

Sequential games. (Lecture 4)

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

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

Differentiation. A “derivative”,

Differentiation. A “derivative”,

CENG 789 – Digital Geometry Processing

CENG 789 – Digital Geometry Processing

Discrete mathematics. Probability

Discrete mathematics. Probability

Probability theory. Probability Distributions Statistical Entropy

Probability theory. Probability Distributions Statistical Entropy

Evolutionary games. (Lecture 7)

Evolutionary games. (Lecture 7)

Matrix Equations and Systems of Linear Equations

Matrix Equations and Systems of Linear Equations

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

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

Сумма и разность синусов и косинусов

Сумма и разность синусов и косинусов

Arithmetic fundamentals of number systems

Arithmetic fundamentals of number systems

Vectors. Lecture 9

Vectors. Lecture 9

Geometric Transformations

Geometric Transformations

Auctions. (Lecture 10)

Auctions. (Lecture 10)

The travelling salesman problem

The travelling salesman problem

Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions

Chapter 3. Polynomial and Rational Functions. 3.1 Quadratic Functions

Correlation Regression

Correlation Regression

Economics of pricing and decision making. (Lecture 1)

Economics of pricing and decision making. (Lecture 1)

Mathematics for Computing. Lecture 2: Logarithms and indices

Mathematics for Computing. Lecture 2: Logarithms and indices

Solving linear recurrence relations

Solving linear recurrence relations

Matrices: Basic Operations

Matrices: Basic Operations

Santas sleigh. Game

Santas sleigh. Game

Mathematics for Computing 2016-2017. Lecture 1: Course Introduction and Numerical Representation

Mathematics for Computing 2016-2017. Lecture 1: Course Introduction and Numerical Representation

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

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

Matlab Linear Programming

Matlab Linear Programming

Differentiation. Sketching functions

Differentiation. Sketching functions

Simultaneous games. Oligopoly. (Lecture 2)

Simultaneous games. Oligopoly. (Lecture 2)

Russian mathematician. Sofia Kovalevskaya

Russian mathematician. Sofia Kovalevskaya

Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication

Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication

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

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

Introduction to vectors

Introduction to vectors

Recitation class

Recitation class

Empirical rule - Probabilities. Week 5 (1)

Empirical rule - Probabilities. Week 5 (1)

Propositional logic

Propositional logic

Introductory Statistics 1. AP Statistics

Introductory Statistics 1. AP Statistics

Review of Basic Concepts in Statistics

Review of Basic Concepts in Statistics

Graph transformation 1

Graph transformation 1

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