Subject Code:  PPS0016 
Objective:  This course introduces basic probability and statistics to students. In probability, students are taught the basic concepts of probability and introduced to discrete and continuous random variables, including some special probability distributions. In statistics, students will be introduced to some of the basic terms in statistics and exposed to tabular as well as pictorial presentation of data. Students will be taught sampling distribution for mean, population and variance. 
PreRequisite:  None 
Credit Hours:  3 
Student Learning Time:  120 hours 
Assessment:  Quizzes: 20% Tests: 30% Final Examination: 50% 
References: 

Descriptive Statistics
Basic terms, types of
statistics, population, sample, types of variables. Tabular
presentation – frequency, relative frequency, percentage and cumulative
frequency distributions, pictorial presentation – bar chart, pie
chart, histogram, frequency polygon and ogive. Measures of central
tendency for ungrouped and grouped data. Measures of dispersion for
ungrouped and grouped data.
Events and Probability
Experiment and sample
space, events and their occurrences, multiplication rule, combinations,
permutations, set operations, venn diagram, tree
diagram,
probability of an event, additive and multiplicative rules, conditional
probability, independent events, mutually exclusive events, complement
of an event.
Random variables
Probability distributions of
discrete random variables and continuous random variables. Cumulative
distributions of discrete random variables and
continuous random
variables. Mean, variance, and standard deviation of discrete random
variables and continuous random variables.
Special Probability
distributions
Discrete
 Binomial and Poisson Distributions. Probability formula, probability
table, mean, variance, and standard deviation of Binomial and Poisson
distributions.
Continuous  Normal Distribution, standard normal distributions.
Probability table. Applications to real problems.
Sampling Distributions
Mean, variance, and
standard deviation of the sample mean, probability of the sample mean.
Sampling error and nonsampling error. Sampling distributions of a
sample mean when the population has a normal distribution, Sampling
distributions of a sample mean when the population is not from a normal
distribution (Central Limit Theorem). Sampling distribution for sample
proportion and sample variance.
At the completion of the subject, students should be able to: