SUBJECT (MODULE) DESCRIPTION. The name of the academic subject (module) Business Statistics

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1 SUBJECT (MODULE) DESCRIPTION The name of the academic subject (module) Business Statistics Code Staff Co-ordinator: prof.dr.g.kasnauskiene Other(s): Faculty of Economics Division first Cycle of studies compulsory Type of the subject (module): Form of implementation Period Language of instruction Lectures, seminars, work in computer 2nd, Spring English labs, examination Requirements for student Prerequisites: Micro and macro economics, Additional requirements (if any): Mathematics Volume of the subject Total student s workload Contact hours Independent work hours (module) in credits Aims of the subject (module): competences to be built by the study programme Purpose of the course to provide students with relevant knowledge and skills necessary for modern statistical analysis. Generic competences to be developed - Ability to analyse and assess. - Interpersonal skills. - Initiative and entrepreneurship. Subject-specific competences to be developed - Ability to analyse and evaluate the business and economic situations, using a variety of statistical analysis methods. - Understanding the principles of analysis and specifics of application. Ability to analyse and evaluate organizational development processes by using statistics and other areas of theories as well as national and international research and practice. Emphasis is placed on applications; all topics are illustrated by the examples from Lithuanian business and economics reality. Intended outcomes of the subject (module) Study methods Assessment methods Evaluation form: written Problem teaching, examination. On completion of the course students will be able to: research methods (search for Composition of the Know and understand the importance of modern evaluation grade: mid-term statistical analysis for organizational development information), Independently find statistical information and analyse test, the closed type group discussions. it questions that require independently conduct empirical research and Presentation of revealing the progress and summarize the results during results, team project, final make statistical conclusions and use them for business lectures by linking exam (formulaes decisions with practical allowable). The exam can carry out statistical calculations in MS Excel and IBM examples of be taken only if positive SPSS statistical analysis. evaluation of the team project is received.

2 Contact hours Independent work assignments Themes Lectures Consultations Seminars Practical classes Lab works Practice Total contact Independent work Assignments Introduction. What is Statistics? Why a Individual study of manager needs to know about statistics? Key summaries of lectures definitions. and Data collection. Types of data and their Individual study of sources. Design of survey research. summaries of lectures and. Designing the questionnaire. Presenting Data in Tables and Charts. The Ordered Array and Stem-Leaf Display. Frequency Distributions. Tabulating and Graphing Univariate and Bivariate Data , discussion of the questionaires designed and the solution of Numerical Descriptive Measures. Measures of central tendency, variation, and shape. The empirical rule. Five number summary and box-and-whisker plots , discussion of Preparation for the mid-term test 5. Mid-term test Probability. Basic Concepts of Probability. Rules of Probability Probability Distributions. Random Variables. Binomial Distribution. Poisson Distribution. The Standard Normal Distribution , discussion of Sampling Distributions Theoretical Background of Statistical Inference. Population Parameters and Sample Statistics , discussion of

3 Estimates and Sample Sizes. Estimates and Sample Sizes of Means. Estimates and Sample Sizes of Proportions , discussion of Discussion of the team project and solution of exercises Testing Hypothesis. Null and Alternative Hypotheses. Type I and Type II Errors. Testing a Claim about a Mean. Testing a Claim about a Proportion. Inferences from Two Samples. Inferences about Two Means. Inferences about Two Proportions Nonparametric statistics. Claims about a Median. Wilcoxon Tests. Analysis of Variance. F-distribution. One-Way Anova. Introduction to Linear. Regression and Correlation Analysis. Calculation and interpretation of the simple correlation between two variables. Regression analysis and its applications for purposes of prediction and description. Multiple Regression. The Multiple Regression Equation. Making Predictions Analyzing and Forecasting Time-Series Data. The components present in a time series. Smoothing-based forecasting models, presentation. including single and double exponential smoothing. Trend-based forecasting models Index Numbers. Construction and interpretation of indexes. The Consumer Price Index. Preparation for the final exam Total: Discussing progress of the project and solution of exercises Discussing solution of Project Assessment of knowledge and activeness demonstrated by students. Solution of Pre-exam test Assessment strategy Share Time of Criteria of assessment in % assessment Mid-term test 20 During the Quality of answers to the closed type questions of the course semester Team project 20 During the Project performance quality semester Final exam 60 During the Quality of answers to the open-type questions of the course and session solving

4 Author Publi Title Volume of a Place of publishing, -shed periodical or publishing house, or Internet in publication reference Compulsory literature Argyrous G Statistics for resarch with a 3rd ed. Sage guide to SPSS Groebner, D. F Business statistics: a 7th. ed. Prentice Hall Inc. decision-making approach 2011 IBM SPSS Statistics 20 Brief Guide ch?q=spss+20+brief+guide& sourceid=ie7&rls=com.micr osoft:lt:ie- SearchBox&ie=&oe= Supplementary literature McClave J.T., Benson 2008 Statistics for Business and 10th ed. Prentice-Hall, Inc. P.G., Sincich T. Economics,

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