https://cis.temple.edu/~latecki/Courses/CIS2033-Spring13/Modern_intro_probability_statistics_Dekking05.pdf
Basic to statistics is that one usually does not consider one experiment, that the same experiment is performed several times. For example, we throw a coin two times.
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch2.pdf
One of the reasons Selix won so many times in 2006 is that he spent about $200 a week or more than $10,000 a year on scratch-off games. If the games cost $1 then this would be 10,000 plays with an approximate 1/100,000 chance of winning.
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch3.pdf
When we picked one of the three doors initially we had probability 1/3 of picking the car, and since the host can always open a door with a donkey the new information does not change our chance of winning.
https://cis-linux1.temple.edu/~tug29203/25fall-2033/lectures/ch1-1.pdf
Suppose you’re on a game show, and you’re given the choice of three doors; behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat.
https://bulletin.temple.edu/courses/as/
This course covers one of the foundational concepts of actuarial science: the time value of money. Students learn about simple, compound, and effective interest rates, and use them to calculate present values and future values of all forms of deterministic cash flows, both discrete and continuous.
https://cis-linux1.temple.edu/~tug29203/25fall-2033/lectures/ch1-3.pdf
Calculation of Conditional Probability In observing the outcomes of a random experiment, one is often interested in how the outcome of one event A is influenced by that of another event B. If A and B are events in the sample space S, the conditional probability of A given B, when P(B) > 0 is: P(A∩B) P(A|B) = P(B)
https://www.fox.temple.edu/directory/zhigen-zhao-zhaozhg
Sarkar, S.K. & Zhao, Z. (2022). Local false discovery rate based methods for multiple testing of one-way classified hypotheses. Electronic Journal of Statistics, 16 (2). Institute of Mathematical Statistics. doi: 10.1214/22-ejs2080. Xing, X., Zhao, Z., & Liu, J.S. (2021). Controlling False Discovery Rate Using Gaussian Mirrors.
https://sites.temple.edu/gametheory/2024/04/22/understanding-the-game-theory-in-poker/
One of the foundational concepts in game theory applied to poker is the Nash Equilibrium, named after mathematician John Nash. In poker terms, Nash Equilibrium occurs when a player’s strategy is optimal, considering the strategies of their opponents.
https://cst.temple.edu/sites/cst/files/IPLecture1.pdf
What is integrable probability? Imagine you are building a tower out of standard square blocks that fall down at random time moments. How tall will it be after a large time T? It is natural to expect that Height = const T + random fluctuations What can one say about the fluctuations?
https://cis.temple.edu/~giorgio/cis587/readings/constraints.html
We generate one by one all possible complete variable assignments and for each we test if it satisfies all constraints. The corresponding program structure is very simple, just nested loops, one per variable.