Foreign Language Math Science Social Science Business Engineering & Technology Arts & Humanities History Miscellaneous Standardized tests
  1. Math
  2. Statistics And Probability
Histograms
Probability
Normal Distribution
Statistics
Biostatistics
Counting
Lecture 1: Random Walks, Distribution Functions
Lecture 1: Random Walks, Distribution Functions
Lecture 1: Probability theory
Lecture 1: Probability theory
Lecture 1: Pass out sign-up sheet
Lecture 1: Pass out sign-up sheet
Lecture 1: Inverse Crimes, Model Discrepacy and Statistical Error Modeling Erkki Somersalo
Lecture 1: Inverse Crimes, Model Discrepacy and Statistical Error Modeling Erkki Somersalo
Lecture 1: Introduction
Lecture 1: Introduction
Lecture 1:
Lecture 1:
Lecture 19: UGC-hardness of Max Cut 1 UGC-hardness of MAX-CUT
Lecture 19: UGC-hardness of Max Cut 1 UGC-hardness of MAX-CUT
lecture 19 notes
lecture 19 notes
Lecture 19
Lecture 19
Lecture 18: Recall: } a finite measble. partition Let α = {A
Lecture 18: Recall: } a finite measble. partition Let α = {A
Lecture 18
Lecture 18
Lecture 17 - Notes Of Engineering Statistics
Lecture 17 - Notes Of Engineering Statistics
Lecture 17
Lecture 17
Lecture 17
Lecture 17
Lecture 16: Recall defns of ergodicity and mixing for Z and Z actions.
Lecture 16: Recall defns of ergodicity and mixing for Z and Z actions.
Lecture 16: Expected value, variance, independence and
Lecture 16: Expected value, variance, independence and
Lecture 16 1. Some examples
Lecture 16 1. Some examples
Lecture 16 1. Some examples
Lecture 16 1. Some examples
Lecture 15-16
Lecture 15-16
LECTURE 15 Lecture outline • Readings: Sections 7.1-7.3 • Limit theorems:
LECTURE 15 Lecture outline • Readings: Sections 7.1-7.3 • Limit theorems:
Lecture 15
Lecture 15
Lecture 14w Frequency Analysis
Lecture 14w Frequency Analysis
Lecture 14 Stochastic Processes.pptx
Lecture 14 Stochastic Processes.pptx
Lecture 14 chi-square test, P-value
Lecture 14 chi-square test, P-value