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Course Content
Lecture 1
0/2
Introduction, counting techniques
01:20:17
P2
29:15
Lecture 2
0/1
Probability ,Addition rule, complement.
01:59:01
Lecture 3
0/1
Conditional probability &Independence.(multiplication rule)
01:28:01
Lecture 4
0/1
Bayes’ Theorem
02:00:02
Lecture 5
0/1
Discrete and continuous Random variables.
01:51:15
Lecture 6
0/2
P1
02:01:38
Joint , marginal
01:44:15
Lecture 7
0/1
marginal, joint , expected value Discrete
01:07:39
Lecture 8
0/1
mean, variance and covariance continuous
02:00:00
Lecture 9
0/1
Linear combinations
01:40:00
Lecture 10
0/1
chebychev’s Theorem
01:00:00
Lecture 11
0/1
Special discrete distributions
01:37:00
Lecture 12
0/1
Special Continuous Probability Distributions
01:50:00
Final Revision
0/1
revision
02:00:00
Math240-spring 24/25-Bilgi
Exercise Files
L1.pdf
Size: 4.19 MB
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