QUA 207 Statistics for Management

The aim of this course is to: Provide students with the basic concepts and terminology of statistical science (Definition of statistical science, Types of statistical data, Population, Variable, Types of variables, Population parameter, Sample, Sampling methods (Probability & Non-Probability), Random variable, Sample statistic).
• Cover different methods of arranging & tabulation and presentation of data.
• Teach the student probability theory.
• to prepare the students to perform scientific interpretation of economic and social phenomena to assist in various policy and decision-making.
• Using statistical programs (such as SPSS or Microsoft Excel)
• Using recent technology methods to teach and illustrate the subjects, which include preparation and processing of course electronically.
• Update the course as a result of new research in the field.
• Update the references regularly.
• Apply the studied methods on real life problems.
Course Description
• Basic concepts of statistics
• Tabulation and classification of data.
• Pictorial representation of data.
• Numerical descriptions of data.
• Probability theory.
• Simple linear regression and correlation.
• Time series analysis
• Index numbers.

QUA 207
Objectives
The aim of this course is to use basic concepts of probability theory which is previously studied through QUA 107, to study sampling distributions of various sample statistics. Then, point and interval estimation for different population parameters will be studied as well as performing hypotheses testing regarding these parameters. The final goal of the course is to assist in decision-making based on scientific rules.
• Using statistical programs (such as SPSS or Microsoft Excel)
• Using recent technology methods to teach and illustrate the subjects, which include preparation and processing of course electronically.
• Update the course as a result of new research in the field.
• Update the references regularly.
• Apply the studied methods on real life problems.
Topics to be covered

Review of the concepts of probability theory and probability distributions. Review of the Normal distribution and its characteristics.
Sampling distribution of important Sample statistics where the underlaying distribution is Normal (Sample mean, the difference between two sample means for independent samples, Sample Variance, Ratio between two sample variances for independent samples, Sample proportion for large sample and the difference between two sample proportions for independent large samples)
Construction of confidence interval for different population Parameters in case of Normal distribution (Population Mean, the difference between two Population Means , Population Variance, Ratio of tow Populations Variances, Population Proportion and the difference between two Population Proportions).
Hypotheses Testing about important population Parameters in case of Normal distribution
Simple Linear Regression and Correlation.
The Chi-Square distribution and the analysis of frequencies (Test of goodness of fit, Test of independence, Test of Homogeneity).

Course Materials