20354 - STATISTICS AND DATA ANALYSIS - PREPARATORY COURSE

During the course, techniques for collecting and analyzing data are described. The main concepts of statistical thinking, both descriptive and inferential, are covered. In order to better understand inferential tools, the basis of probability theory is taught. The described techniques will be applied to data during hands-on classes, using the software Excel.

The course focuses on three main parts:

• Descriptive analysis of a data set:
• Data collection, organizing data in tables, graphical presentation methods,
• Measures of central and non central tendency, measures of variation.
• Shape of a distribution. Outliers and extreme values.
• Tabulating and graphing bivariate data.
• Measures of association and of dependence (association and independence-contingency coefficient; mean dependency, linearrelationships; covariance, correlation coefficient). Simple linear regression.
• Probability theory and Random variables:
• Experiments, sample spaces and events. Definition of probability and rules of probability. Conditional probability and independent events.
• Random variables: discrete and continuous. Vectors of random variables. Transformation and sum of random variables.
• Inferential statistics:
• Sample and Sampling distribution. Descriptive versus Inferential Statistics.
• ·Point and confidence interval Estimation.
• ·Fundamentals of Hypothesis Testing, Hypothesis test for mean and for proportion.
• Simple linear regression.

• D.M. Levine, T.C. Krehbiel, M.L. Berenson, Business Statistics: A First Course, Prentice Hall, 2005.Fourth Edition.