Statistics I Chapters

Basic concepts of statistics; Applications in computer science and information technology; Scales of measurement; Variables; Types of data; Notions of a statistical population and sample.

Measures of central tendency; Measures of dispersion; Measures of skewness and kurtosis; Moments; Stem-and-leaf display; Five number summary; Box plot; Problems and illustrative examples.

Concepts of probability; Definitions of probability; Laws of probability; Bayes theorem; Prior and posterior probabilities; Examples related to computing and randomness.

Definition of population; Sample survey vs census survey; Sampling error and non-sampling error; Types of sampling and their applications.

Concepts of random variables; Types of random variables; Probability distribution of a random variable; Mathematical expectation; Properties; Addition and multiplication rules.

Probability distribution functions; Joint probability distributions; Discrete distributions: Bernoulli, Binomial, Poisson; Continuous distributions: Uniform, Normal and others.

Bivariate data; Bivariate frequency distribution; Correlation between two variables; Karl Pearson’s correlation coefficient (r); Spearman’s rank correlation; Linear regression analysis and equations.