- Degree Master
- Code: BIS959
- Credit hrs: 3
- Prequisites: -
This course contains many topics and its applications in Business studies. In each topic we consider firstly the theoretical part then we consider its applications with real examples. Also, students can suggest a real problem according to their specialization and one of the case studies is to formulate the suggesting problems in statistical Model, then solving it. This course will introduce students to different types of statistics and statistical methods. Students will then be able to determine which statistic and /or method is appropriate for a given situation. Emphasis will not be placed on memorizing formulas, but instead will be placed on applying statistics to real world business problems.
MBA
- David R. Anderson, Thomas A. Williams, Dennis J. Sweeney, and Jeffrey D. Camn, (2020), “Statisicts for business and economics”, 14th edition, cengage learning incorporation. - Darren George and Paul Mallery, (2020) “IBM SPSS statistics step by step: A simple guide and reference”, 16th edition, Routledge, New York.
content serial | Description |
---|---|
1 | Introduction to statistics & Describing data using tables (frequency table, cross tabulation and custom table) &Describing data using graphs (bar chart, pie chart, pareto diagram, dot plot, stem and leaf, and histogram) |
2 | Describing data using numerical measures (measures of central tendency, measures of dispersion, and measures of distribution) &Empirical rule and chebychev rules for describing data&Determing extreme and outlies (Z- Score and Box plot) |
3 | Introduction to probability &Probability distributions: (Binomial, Poisson and normal)&Estimation and confidence intervals |
4 | Test of hyptheres and test selection&One sample test of hypotheses (parametric and nonparametric tests)&Two samples test of hypotheses (parametric and nonparametric tests) |
5 | Three or more samples test of hypotheses (parametric and nonparametric tests)&Correlation analysis (Pearson and Spearman correlation coeffients)&Simple and multiple regression analysis |
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