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Chiziqli algebraik tenglamalar sistemasini Kramer
Numbers 11-20
Matrices - Introduction. Lecture 1-3
Determinants
Solution Methods Applied Computational Fluid Dynamics. Lecture 5
Cmpe 466 computer graphics. 3D geometric transformations. (Сhapter 9)
Correlation and Regression
Modeling non-stationary variables
Treasure and numbers
Confidence interval estimation
The mean values
Hypothesis Testing with Two Samples
Geometric Modeling - Parametric Representation of Synthetic Curves
Normal Probability Distributions
Discrete mathematics. Sets
Correlation and regression
Boolean algebra. Logic operations. Formula and their conversion
Descriptive statistics
Statistics. Data Description. Data Summarization. Numerical Measures of the Data
Hypothesis testing
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)
Rehabilitation
Probabilistic Models. Chapter 11
Exploring Assumptions Normality and Homogeneity of Variance
Descriptive statistics. Elementary statistics. Larson. Farber. (Chapter 2)
System of linear equations. Lecture 4-5
Inverse of a Square Matrix
Scalars, vectors and tensors
Numeral system
Matlab Linear Programming
Trigonometriýa
4.2 Introduction to Limits
Measures of variation. Week 4 (2)
Introduction to normal distributions
Using first derivative. Using second derivative
Random variables – discrete random variables. Week 6 (2)
Binary Variables
Ch8: Hypothesis Testing (2 Samples)
Mixed strategy Nash equilibrium. (Lecture 3)
Review of Basic Concepts in Statistics
Index of Refraction
Exponentials and logarithms. Lecture 2.1
Matrices: Basic Operations
Stolz-Cesaro Theorem
Introduction to Statistics
Chapter 3. Polynomial and Rational Functions. 3.2 Polynomial Functions and Their Graphs
Matrix Equations and Systems of Linear Equations
Calculating the probability of a continuous random variable – Normal Distribution. Week 9 (1)
Using numerical measures to describe data. Measures of the center. Week 3 (2)
Linear Regression. Regression model evaluation metrics. Lecture 5
Method of undetermined coefficients
N-ary relations and their applications. (Rosen 8.2)
Vectors. Lecture 9
Modelling with Exponentials and Logarithms
Sampling in quantitative research
Types of Data – (continued). Week 2 (2)
Inscribed and circumscribed circles of a triangle
Chapter 3. Polynomial and Rational Functions. 3.4 Zeros of Polynomial Functions
Empirical rule - Probabilities. Week 5 (1)
Probability Random Variables Preparatory Notes
Math end algebra. Vector
Forecasting with bayesian techniques MP
Differentiation. A “derivative”,
Basic arithmetic
The binomial model for option pricing
Сумма и разность синусов и косинусов
Vectors and the geometry of space. Lecture 10.b
Russian mathematician. Sofia Kovalevskaya
Combinational logic design
Measures of variation. Week 4 (1)
Chapter 1. Polynomial and Rational Functions. 3.3. Dividing Polynomials; Remainder and Factor Theorems
The Normal and other Continuous Distributions
Probabilities. Week 5 (2)
Discrete random variables – expected variance and standard deviation. Discrete Probability Distributions. Week 7 (1)
Correlation Regression
Volume
Probability theory. Probability Distributions Statistical Entropy
Discrete Probability Distributions: Binomial and Poisson Distribution. Week 7 (2)
Math signs
Economics of pricing and decision making. (Lecture 1)
Auctions. (Lecture 10)
Introduction to vectors
Sequential games. (Lecture 4)
Discrete Mathematics Sets
Introductory Statistics 1. AP Statistics
Probability Concepts
Комплексные корни квадратных уравнений. Основная теорема алгебры
GCSE Circle Theorems
Practical application of the method of Kona-Shema. Pseudopotentials method
Types of Data – categorical data. Week 2 (1)
Displaying data – shape of distributions. Week 3 (1)
CENG 789 – Digital Geometry Processing
Repeated games. (Lecture 6)
The Gilbert-Johnson-Keerthi (GJK) Algorithm
Solving linear recurrence relations
Vectors and the geometry of space
Random variables
Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication
Geometric Transformations
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