A short list of item for comparison is:1) Ease of learning,
2) Amount of help incorporated for the user,
3) Level of the user,
4) Number of tests and routines involved,
5) Ease of data entry,
6) Data validation (and if necessary, data locking and security),
7) Accuracy of the tests and routines,
8) Integrated data analysis (graphs and progressive reporting on analysis in one screen),
9) CostNo one software meets everyone's needs.
In the last few years the survival analysis software available in several of the standard statisticalpackages has experienced a major increment in functionality, and is no longer limited to the triad ofKaplan-Meier curves, logrank tests, and simple Cox models.
Multivariate analysis is a branch of statistics involving the consideration of objects on each of which are observed the values of a number of variables.
The concept of influence is the study of the impact on the conclusions and inferences on various fields of studies including statistical data analysis.
Analyzing the DataStatistical data analysis divides the methods for analyzing data into two categories: exploratory methods and confirmatory methods.
The statistical software package, SPSS, which is used in this course, offers extensive data-handling capabilities and numerous statistical analysis routines that can analyze small to very large data statistics.
Statistical data analysis provides hands on experience to promote the use of statistical thinking and techniques to apply in order to make educated decisions in the business world.
The computer will assist in the summarization of data, but statistical data analysis focuses on the interpretation of the output to make inferences and predictions.
Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis.
Weatherson B., Begging the question and Bayesians, , 30(4), 687-697, 1999.
The problem with the Classical Approach is that what constitutes an outcome is not objectively determined.
1. Defining the problem
2. Collecting the data
3. Analyzing the data
4. Reporting the resultsDefining the Problem An exact definition of the problem is imperative in order to obtain accurate data about it.
The author states that statistics has become known in the twentieth century as the mathematical tool for analyzing experimental and observational data.
Paradoxically, the design of data collection, never sufficiently emphasized in the statistical data analysis textbook, have been weakened by an apparent belief that extensive computation can make upfor any deficiencies in the design of data collection.
Featured topics include public opinion polls, industrial quality control, factor analysis, Bayesian methods, program evaluation, non-parametric and robust methods, and exploratory data analysis.
Porter T., , 1820-1900, Princeton University Press, 1986.
Other modeling approaches include structural and classical modeling such as Harvey, and Box-Jenkins approaches, co-integration analysis and general micro econometrics in probabilistic models, e.g., Logit, Probit and Tobit, panel data and cross sections.
The course is tailored to meet your needs in the statistical business-data analysis using widely available statistical computer packages such as SAS and SPSS.