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      Yerim Oh

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Mathematics

  • [INDEX] Linear Algebra with example

    개념 체크 위주의 정리

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  • [Linear Algebra] 01. 일차 방정식과 행렬

    개념 체크 위주의 정리

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  • [11] [INDEX] Linear Algebra

    Are You Ready To Learn Linear Algebra?

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  • [00] [INDEX] STATISTICS

    Are You Ready To Learn STATISTICS?

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  • [01] STATISTICS: Defining and Collecting Data

    개념부터 문제로 이해하는 Definition Of Some Terms,Primary Sources, Secondary Sources, POPULATION, SAMPLE/Structured Data (정형데이터), Unstructured Data (비정형 데이터) 차이/Nonprobability Sample/probability Sample (Simple Random, Systematic, Stratified, Cluster) ,After Collection It Is Often Helpful To Recode,Types of Sample

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  • [02] STATISTICS: Defining and Collecting Data

    개념부터 문제로 이해하는 Categorical Data,Summary Table For One Variable (Bar Chart,pie chart,Pareto Chart)/Numerical Data,Ordered Array , Frequency Distributions and Cumulative Distributions(Histogram,polygon), Two Numerical Data (Time-Series Plot,Scatter Plot)

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  • [03] STATISTICS: Numerical Descriptive Measures 1 (수치적 기술 방법)

    central tendency(Mean,Median,Mode), variation(Range, Sample Standard Deviation, Sample Variance,Coefficient of Variation,Z-Score),shape(Skewness, Kurtosis)

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  • [04] STATISTICS: Numerical Descriptive Measures 2 (수치적 기술 방법)

    Exploring Numerical Data(Quartile Measures)/sample 과 population의 평균, 분산/Two Measures Of The Relationship_ 공분산, 상관계수

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  • [05] STATISTICS: Basic Probability

    Basic Probability Concepts(Assessing Probability,EVENT,Probability,Exclusive Events,Computing)/Conditional Probabilities/PLUS/Bayes’ Theorem/Counting Rules

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  • [06] STATISTICS: Discrete Probability Distributions

    문제와 영어 수학 용어로 이해하는 Discrete Variables 베르누이 분포 Bernoulli distribution, 이항분포, 포아송비Poisson Distributions

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  • [07] STATISTICS: The Normal Distribution

    문제로 익히는 Continuous Probability Distribution, The Normal Distribution, The Standardized Norma, Finding Normal Probabilities

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  • [08] STATISTICS: Sampling Distributions of the Mean

    예시와 그림, 문제로 쉽게 알아보는 Sampling Distributions, Sampling Distributions of the Mean, Standard Error of the Mean, Central Limit Theorem

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  • [09] STATISTICS: Sampling Distributions of the Proportion

    예시와 그림, 문제로 쉽게 알아보는 Sampling Distributions, Sampling Distributions of the Mean, Standard Error of the Mean, Central Limit Theorem

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  • [10] STATISTICS: One-Sample Tests_Hypothesis & Z-Test

    문제와 예시로 쉽게 배우는 Fundamentals of Hypothesis Testing: One-Sample Tests, The Null Hypothesis, $$H_0$$,The Alternative Hypothesis, $$H_1$$,The Hypothesis Testing Process,Critical Value approach,p-Value approach,Risks in Decision Making Using Hypothesis Testing

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  • [11] STATISTICS: One-Sample Tests_𝜎 Unknown (t test)

    𝜎 Unknown (t test)

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  • [12] STATISTICS: One-Sample Tests_one tail test

    One-Tail Tests 종류,Lower-Tail Tests,Upper-Tail Tests, Example: Upper-Tail t Test for Mean (𝜎 unknown)

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  • [13] STATISTICS: One-Sample Tests_Hypothesis Tests for Proportions

    Hypothesis Tests for Proportions, Proportions, Example: Z Test for Proportion

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  • [13] STATISTICS: Two-Sample Tests_Independent samples

    문제로 개념 응용까지 해보는 Fundamentals of Hypothesis Testing: Two-Sample Tests,Comparing the mean of Two Independent Populations, Pooled-Variance t-test, Separate-variance t-test ,Independent Sample

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  • [15] STATISTICS: Two-Sample Tests_Related Populations

    문제로 이해하는 Comparing the mean of Two Related Population: σ(퍼짐의 정도)를 모를 때, σ(퍼짐의 정도)를 알 때

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  • [16] STATISTICS: Two-Sample Tests_Population proportion

    문제로 이해하는 Fundamentals of Hypothesis Testing: Two-Sample Tests, Comparing the mean of Population proportion의 계산식,정규화 조건

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  • [17] STATISTICS: Two-Sample Tests_Population Variance

    문제로 개념 응용까지 해보는 Fundamentals of Hypothesis Testing: Two-Sample Tests,Comparing the mean of Two Population Variance , F Distribution

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  • [18] STATISTICS: ANOVA

    문제로 개념 응용까지 해보는 General ANOVA Setting, One-Way Analysis of Variance, Hypotheses of One-Way ANOVA, Partitioning the Variation,Partitioning the Variation , SST, SSA, SSW/ ANOVA F Test Statistic

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  • [11] Vector Spaces: 벡터란?

    벡터란, 벡터에 담긴 기하학적 의미, 벡터 합, 합성벡터, 벡터 합의 평행사변형 법칙 (parallelogram law), 벡터 합의 평행사변형 법칙의 성질, 스칼라 곱, 세 점 A, B, C 로 결정되는 평면

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  • [12] Vector Spaces: 벡터 공간

    대수적 구조로서 벡터의 개념, 벡터공간, 용어정리

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  • [13] Vector Spaces: 부분 공간, 행렬의 종류

    부분공간(subspace) 정의, 부분공간이기 위한 필요충분조건, 행렬의 종류(정방행렬, 전치행렬, 대칭행렬, 영행렬, 삼각행렬, 대각행렬, 항등행렬, 직교행렬

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  • [14] Vector Spaces: 일차결합과 연립일차방정식

    일차 결합 linear combination, 계수 coefficient, 일차결합 증명, 생성공간 span

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  • [15] Vector Spaces: 일차종속과 일차독립

    일차종속 linearly dependent, 일차독립 linearly independent

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  • [16] Vector Spaces: 기저와 차원

    기저 basis, 표준기저 standard basis, 기저의 성질, 대체정리 replacement theorem, 기저와 연관 개념, 부분공간의 차원, 라그랑주 보간법, 라그랑주 다항식 Lagrange polynomial]

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  • [17] Vector Spaces: 일차독립인 극대 부분집합

    극대 (Maximal), 멱집합 (Power Set), 사슬 (Chain), 하우스도르프 극대 원리 (Hausdorff Maximal Principle), 일차 독립인 극대 부분집합 (Maximal Linearly Independent Subset)

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  • [17] 선형대수: 선형변환

    기저 basis, 표준기저 standard basis, 기저의 성질, 대체정리 replacement theorem, 기저와 연관 개념, 부분공간의 차원, 라그랑주 보간법, 라그랑주 다항식 Lagrange polynomial]

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  • [21] Linear Transformation: 일차독립인 극대 부분집합

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  • [22] Linear Transformation: 선형변환의 행렬표현

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  • [23] Linear Transformation: 가역성과 동형사상

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  • [24] Linear Transformation: 쌍대공

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