Course Information
Statistical Tools for Data Analysis:
Special Topics
Topics:
- Computers and Computational Statistics with Applications
- Questionnaire Design and Surveys Sampling
- Time Series Analysis and Forecasting Techniques
- Topics in Statistical Data Analysis
- Companion site I: A Collection of JavaScript E-labs Learning Objects
- Companion site II: Excel For Introductory Statistical Analysis
Students may visit Professor Hossein Arsham at his office located at Business Center 479. You can contact him by phone 410-837-5268, fax 837-5722, or by Email at harsham@ubalt.edu.To find out more information about Dr. Hossein Arsham, visit his Home Page at http://home.ubalt.edu/ntsbarsh/index.html.
Students must seek tutorial help from the Academic Resource Center at 410-837-5385, E-mail, located at AC 111.
Visit also Business Statistics.
- Welcome Message
- Course Description, and Required Textbooks
- Learning Objectives
- The Main Web Sites I Recommend
Dear Student
Welcome to:
Statistical Data Analysis I am looking forward to working with you and hope that you will find the course both enjoyable and informative.
Managers need to understand variation for two key reasons. First, so that they can lead others to apply statistical thinking in day to day activities and secondly, to apply the concept for the purpose of continuous improvement. This course will provide you with hands-on experience to promote the use of statistical thinking and techniques to apply them to make educated decisions whenever there is variation in business data. Therefore, it is a course in statistical thinking via a data-oriented approach.
Know that data are only crude information and not knowledge by themselves. The sequence from data to knowledge is: from Data to Information, from Information to Facts, and finally, from Facts to Knowledge. Data becomes information when it becomes relevant to your decision problem. Information becomes fact when the data can support it. Fact becomes knowledge when it is used in the successful completion of decision process. The following figure illustrates the statistical thinking process based on data in constructing statistical models for decision making under uncertainties.
That's why we need statistical data analysis. Statistics arose from the need to place knowledge on a systematic evidence base. This required a study of the laws of probability, the development of measures of data properties and relationships, and so on.
Knowledge is more than knowing something technical. Knowledge needs wisdom, and wisdom comes with age and experience. Wisdom is about knowing how something technical can be best used to meet the needs of the decision-maker. Wisdom, for example, creates statistical software that is useful, rather than technically brilliant.
We will apply the basic concepts and methods of statistics you've already learned in the previous statistics course to the real world problems. The course is tailored to meet your needs in the statistical business-data analysis using widely available commercial statistical computer packages such as SAS and SPSS. By doing this, you will inevitably find yourself asking questions about the data and the method proposed, and you will have the means at your disposal to settle these questions to your own satisfaction. Accordingly, all the applications problems are borrowed from business and economics. By the end of this course you'll be able to think statistically while performing data analysis.
Learning Objects: Unfortunately, most classroom courses are not learning systems. The way the instructors attempt to help their students acquire skills and knowledge has absolutely nothing to do with the way students actually learn. Many instructors rely on lectures and tests, and memorization. All too often, they rely on "telling." No one remembers much that's taught by telling, and what's told doesn't translate into usable skills. Certainly, we learn by doing, failing, and practicing until we do it right. The computer assisted learning serves this purpose.
There are two general views of teaching/learning statistics: Greater and Lesser Statistics. Greater statistics is everything related to learning from data, from the first planning or collection, to the last presentation or report. Lesser statistics is the body of statistical methodology. This is a Greater Statistics course.
There are basically two kinds of "statistics" courses. The real kind shows you how to make sense out of data. These courses would include all the recent developments and all share a deep respect for data and truth. The imitation kind involves plugging numbers into statistics formulas. The emphasis is on doing the arithmetic correctly. These courses generally have no interest in data or truth, and the problems are generally arithmetic exercises. If a certain assumption is needed to justify a procedure, they will simply tell you to "assume the ... are normally distributed" -- no matter how unlikely that might be. It seems like you all are suffering from an overdose of the latter. This course will bring out the joy of statistics in you.
It is already an accepted fact that "Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write." So, let us be ahead of our time.
Feel free to contact me via phone, fax, or email. There is a lot of material to cover, so let's start now!
Course Description, and Required Textbooks
Course Description: For the course description, please read the Introductory Section of the topic that you are interested in taking:
- Computers and Computational Statistics with Applications
- Questionnaire Design and Surveys Sampling
- Topics in Statistical Data Analysis
- Time Series Analysis and Forecasting Techniques
Required Textbooks:
A Data-Based Approach to Statistics, by Iman R., Duxbury Press, 1994.
A Guide to Econometrics, by Kennedy P., MIT Press, 1998.
Statistical Data Analysis Handbook, by Wall F., McGraw-Hill, New York, 1986.
Business Forecasting, by Hanke J., and G. Reitsch, Prentice Hall, 2001.
Learning Objectives
When you completes this course they should be able to:
- Understand the role that statistical data analysis plays in managerial decision making under risk.
- Recognize the important characteristics, assumptions, terms and concepts of statistical data analysis.
- Understand the principles of inference and experimental statistical design.
- Perform various statistical data analyzes using professional computer software (e.g. SPSS, SAS), use the results to make inferences and predictions for business applications.
- Understand the important characteristics of forecasting and develop basic forecasting models. Remember "Some people can predict the future. You compute it."
- To enable students to understand the integrated processes of designing and conducting quantitative survey research projects.
- To give students experience of grappling with problems in the design of survey samples, the construction of data collection instruments and the management of survey projects.
- To make student aware of main sources of error in the survey process and ways of detecting, controlling and minimising such error.
- The quantitative survey process from project formulation, statistical design and sampling, through instrument design and question formulation, to data processing.
- Basic principles and practice of probability sample design for field surveys.
- How to operationalise concepts, word questions and design, develop and test survey instruments, taking account of intended uses of the data collected.
- Principles of manual coding and editing of survey data, computer editing and preparing data for analysis.
- Sources of error in survey data, ways of assessing them and ways of minimising error.
- Planning and management of large scale surveys, piloting and pre testing, relations with stakeholders in the sponsored survey process, issues in survey ethics.
- Create and manipulate necessary data files to perform appropriate statistical analysis.
- Prepare technical and non-technical reports for management to communicate orally and in writing an analysis of computer solutions for statistical models.
- Work as a team member to analyze, solve and prepare recommendations for moderately complex decision problems.
- Learn "how can I optimally explain or describe variation in my data set?"
The Main Web Sites I Recommend
The following main statistical web sites together with your textbook contain all the materials you need to learn statistics. Make sure to visit these sites at least once a week to learn more on the related topics covered in this course. Some other useful and specialized web sites are linked to your Weekly Topics pages.
General main statistical Web sites:
The following main statistical web sites and the lecture notes, together with your textbook contain all the materials you need to learn statistics. Make sure to visit these sites at least once a week to learn more on the related topics covered in this course. Some other useful and specialized web sites are linked to your Weekly Topics pages.
General main statistical Web sites:
- Animated Statistical Demonstrations
- Bulletin Board Libraries
- Business Problem Solving
- Epidemiology and Biostatistics
- Financial and Economic Links
- How to Study Statistics
- Intro. to Stat.
- Java Applets
- Java Applets for Visualization of Statistical Concepts
- Lecture summaries
- Merlot
- Maths & Stats Links
- Online Lecture Outlines
- Online statistical computation
- Online Statists Texts and Courses
- Probability
- Probability & Statistics
- Statistical Demos and Calculations
- Statistical Education Resource Kit
- Statistical Programs
- Statistical Training on the Web
- Statistics Education-I
- Statistics Education-II
- Statistics on the Web
- Statistics, Statistical Computing, and Mathematics
- st@tserv
- SurfStat
- Using Excel
- Virtual Library
- WebEc
- World Lecture Hall
- Yahoo:Statistics
Web sites containing statistical keywords & phrases:The following Web site collection provide a wide range of keywords & phrases. Visit these sites weekly to learn the language of statisticians.
Statistical Computation and Tables:The following Web sites provide statistical computations and tables such ad critical values useful in statistical testing and construction of confidence intervals. The results are identical to those given in your textbook. However, in most cases they are more extensive (therefore more accurate).
- Web Pages that Perform Statistical Calculations
- Normal Probability Calculation
- Calculate Mean, Standard Deviation
- Creating a Histogram
- Probability Calculator
- StatCalc
- Statstical Calculators
- SurfStat statistical tables
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