Collection

Courses Taught 

QUA 609 Applied Multivariate Analysis: This course is designed to provide students with knowledge of the concepts underlying multivariate techniques with an overview of actual applications in business. Topics covered include: review of matrix theory, univariate normal,  t distribution, chi-squared distribution, F distributions, and multivariate normal distributions. Inference about multivariate means, Hotellings T2, multivariate analysis of variance, multivariate regression, and multivariate repeated measures. Inference about covariance structure, principal components, factor analysis, and canonical correlation. Multivariate classification techniques, discriminant and cluster analysis, measures of validity and reliability.
QUA102 Mathematic for Business: Brief review of matrices and their operations, Vector Space: definition of vector space - linear independence and dependence – basis – dimension – orthogonality - dot and vector product - Matrices: rank - elementary row and column operations and their use in finding rank,
QUA121 Business statistics: Brief review of probability and distributions with emphasis on the normal distribution - sampling distributions for the mean - proportion - variance - difference between two means - and difference between two proportions - Estimation of population parameters - Point estimation and interval estimation for the mean - proportion - variance - difference between two means difference between two proportions - and the ratio of two variances - Tests of statistical hypotheses - basic definitions – testing hypothesis about the mean - proportion - difference between two means - difference between two proportions - variance - the ratio of two variances. (Suitable software packages are used),
QUA511 Statistical Analysis: MBA course,
QUA512 Statistical Analysis: MBA course,
QUA512 Statistical Analysis: Master of management course,
QUA608 Advanced Business Statistics: This course covers parametric and nonparametric statistics - intermediate and advanced statistics - and the review of descriptive statistics with applications using the statistical package PASW (SPSS). The contents will be more oriented toward practical applications - its use and interpretation - rather than mathematical derivation. Course topics include - role and purpose of statistics - descriptive statistics,

QUA101 Introduction to Business Statistic: Basic concepts – statistical data – population and random sample - sampling methods – collecting data methods - the questionnaire – tabular and graphical presentation of data – measures of central tendency – measures of dispersion – definition of probability - probability axioms - probability space - conditional probability – independent events - addition and multiplication rules - Bayes theorem – random variables and probability distributions –simple regression and coloration - time series(general trend equation) – index numbers. (Suitable software packages are used)

 

inverse and solving linear equations systems - Matrix Partitions - Eigenvalues and Eigenvectors. Quadratic forms - Differentiation of the matrices, summary measures for quantitative and qualitative data - data displays - modeling random behavior - elementary probability and some probability distribution models - normal distribution - statistical inference - confidence intervals and tests for means - variances - and proportions - linear regression analysis and inference - control charts for statistical quality control - introduction to experimental designs and ANOVA - simple factorial design and its analysis