# sap course 1497254627

## Course Code & Number:

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## Pre-requisites & Co-requisites:

Basic concepts of probability (sample spaces and events, permutations, combinations, conditional probability and independence). Discrete and continuous random variables, their probability distributions, expected value, variance. Discrete probability distributions: Binomial, Poisson distributions. Continuous probability distributions: normal, exponential, applications of exponential distribuiton in component and system reliability. Jointly distributed and independent Random Variables. Covariance and correlation. The sampling distribution of sample mean. Central Limit Theorem and its applications. Estimation. Confidence Intervals, Hypothesis Testing, Simple Regression, ANOVA

1) Compute probabilities by modeling sample spaces and applying rules of permutations and combinations, independency and conditional probability

2) Construct the probability distribution of a discrete random variable, based on a real-world situation

3) Identify the random variable(s) of interest in a given scenario

4) Find expected values and variances of both discrete and continuous random variables

5) Demonstrate knowledge of joint probability distributions

6) Find estimators for unknown parameters of distribution using mathematical methods; such as the Method of Moments and the Method of Maximum Likelihood

7) Demonstrate ability to do interval estimation for parameters of distribution/population

8) Demonstrate ability to interpret regression and ANOVA results