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This sequence is ideal for students or early data science professionals who want to strengthen their knowledge of fundamental probability and statistics concepts. Mastery of Mathematical Fundamentals is a prerequisite.
 Course related:
 AMA1110 Basic Mathematics I – Calculus and Probability & Statistics
 Subjects:
 Finance and Mathematics and Statistics
 Keywords:
 Probabilities Mathematical statistics Business mathematics
 Resource Type:
 Others

Courseware
Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you the tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.With examples ranging from medical testing to sports prediction, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.
 Course related:
 AMA1501 Introduction to Statistics in Business
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities
 Resource Type:
 Courseware

ebook
This is a "first course" in the sense that it presumes no previous course in probability. The mathematical prerequisites are ordinary calculus and the elements of matrix algebra. A few standard series and integrals are used, and double integrals are evaluated as iterated integrals. The reader who can evaluate simple integrals can learn quickly from the examples how to deal with the iterated integrals used in the theory of expectation and conditional expectation. Appendix B provides a convenient compendium of mathematical facts used frequently in this work. And the symbolic toolbox, implementing MAPLE, may be used to evaluate integrals, if desired. In addition to an introduction to the essential features of basic probability in terms of a precise mathematical model, the work describes and employs user defined MATLAB procedures and functions (which we refer to as mprograms, or simply programs) to solve many important problems in basic probability. This should make the work useful as a standalone exposition as well as a supplement to any of several current textbooks. Most of the programs developed here were written in earlier versions of MATLAB, but have been revised slightly to make them quite compatible with MATLAB 7. In a few cases, alternate implementations are available in the Statistics Toolbox, but are implemented here directly from the basic MATLAB program, so that students need only that program (and the symbolic mathematics toolbox, if they desire its aid in evaluating integrals). Since machine methods require precise formulation of problems in appropriate mathematical form, it is necessary to provide some supplementary analytical material, principally the socalled minterm analysis. This material is not only important for computational purposes, but is also useful in displaying some of the structure of the relationships among events.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities MATLAB Textbooks
 Resource Type:
 ebook

Video
In this video we look at how to decide for a given scenario (worded problem) if the distribution described is a Binomial distribution or Poisson distribution and whether its probability distribution function or its cumulative distribution function is required to calculate a specified probability.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Binomial distribution Probabilities Poisson distribution Distribution (Probability theory)
 Resource Type:
 Video

Video
In this video we look at how to use statistical tables to calculate probabilities in a Binomial distribution. This includes an example of using the table for the probability density function to determine the probability the random variable takes a particular value and an example of using the table for the cumulative distribution function to determine the probability the random variable is less than or equal to a certain value and an example determining the probability it is greater than or equal to a certain value.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities Poisson distribution Distribution (Probability theory)
 Resource Type:
 Video

Video
In this video we look at how to use statistical tables to calculate probabilities in a Poisson distribution. This includes an example of using the table for the probability density function to determine the probability the random variable is equal to particular value in a case where the average number of events per interval needs to be adjusted to match the units specified in the question and an example of using the table for the cumulative distribution function to determine the probability the random variable takes a value between two specified numbers.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Binomial distribution Probabilities Distribution (Probability theory)
 Resource Type:
 Video

Video
In this video we look at how to use statistical tables to calculate probabilities in a Poisson distribution. This includes an example of using the table for the probability density function to determine the probability the random variable is equal to a particular value and an example of using the table for the cumulative distribution function to determine the probability the random variable is less than a certain value and an example determining the probability it is greater than or equal to a certain value.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities Poisson distribution Distribution (Probability theory)
 Resource Type:
 Video

Courseware
Second introductory course covering basic principles of probability and statistical inference. Topics: Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities Mathematical statistics
 Resource Type:
 Courseware

Courseware
Introductory course covering basic principles of probability and statistical inference. Topics covered in this course: Axiomatic definition of probability, random variables, probability distributions, expectation.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Probabilities Mathematical statistics
 Resource Type:
 Courseware