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31 - DAB- Data Analytics & Business Intelligience


DAB 103 - Statistical Techniques using SPSS: From Beginner to Advanced (10 Days)

Code Start Date Duration Venue
DAB 103 29 April 2024 10 Days Istanbul Registration Form Link
DAB 103 03 June 2024 10 Days Istanbul Registration Form Link
DAB 103 08 July 2024 10 Days Istanbul Registration Form Link
DAB 103 12 August 2024 10 Days Istanbul Registration Form Link
DAB 103 16 September 2024 10 Days Istanbul Registration Form Link
DAB 103 21 October 2024 10 Days Istanbul Registration Form Link
DAB 103 25 November 2024 10 Days Istanbul Registration Form Link
DAB 103 30 December 2024 10 Days Istanbul Registration Form Link
Please contact us for fees

 

Course Description

This course will introduce trainees to the logic and use of statistical techniques in social sciences. The will be able to evaluate social or business research problems  themselves and to have a capability of deciding on  the true statistical alternative after handling the business problems. It presents the basics of the Statistical Package for the Social Sciences (SPSS). It introduces the SPSS Windows environment, discusses how to create a dataset, variable transformations, data manipulations, and descriptive statistics. It will assist trainees in developing the data analysis skills necessary for autonomous and efficient computer processing, manipulation, and analysis of empirical data in the study of social science data or business data.

Then the course advances to statistical techniques used for inferential approaches to the business and social problems and helps the trainee to improve new aspects for the solutions under the significancies provided by SPSS analysing features. The techniques are especially necessary for the experiments(events) that have two or more factors which impact one or more factors of the subject concerned. In real life, the problems have some factors that each has an effect on to the result, either positively or negatively concluded. However, generally their effect is considered as contributed way with all other factors. On the other hand to evalute such an impact onto the result is a complex problem for the managers or researchers. The program will give a remarkable perspective to the trainee to make confident predictions for the solutions about such multivarite problems by some compact practises focused on to the technique.

Course Objectives

  • Building on a basic understanding of statistics
  • Using an omnibus statistical package like SPSS for computation
  • Acquainting trainees to some to the mechanics of utilizing this package
  • Discussing, analyzing, and interpreting Multivariate procedures such as Multiple Regression, Discriminant Function Analysis, Logistical Regression, Cluster Analysis, Multidimensional Scaling, Loglinear Analysis, Survival Analysis, Complex Analysis of Variance Designs, Multivariate Analysis of Variance, and the Analysis of Simple Effects

Who Should Attend?

  • Statistical Managers
  • SAP project team
  • Inventory team personnel
  • anyone wants to learn about the Statistical practises and  using statistical methods

Course Details/Schedule

Day 1

  • Decision making as a business approach
  • Decision Making Procedure
  • Five basic steps

Day 2

  • Talking about Statistics, remember some basics of Statistics
  • Speaking about reseach phases, propose, analysis and reporting results
  • Learning about practises on data  using statistical methods
  • Emphasizing on the importance of data

Day 3

  • Bing familiar with the features of SPSS
  • The SPSS Windows environment
  • Handling any research problem using SPSS

Day 4

  • Determining the experiment of problem
  • Practicing with statistical analysis tool of SPSS
  • Processing data of research and extracting conclusions for the problem
  • Interpreting the conclusions in business approach and decision making 

Day 5

  • Deterministic decisions
  • Probabilistic decisions
  • Hypothesis testing in SPSS

Day 6

  • Review of descriptive statistics and exploratory data analysis
  • Introducing to inferential statistics
  • Multivariate statistics and analysing techniques in SPSS

Day 7

  • Reliability analysis
  • One-way Anova
  • Two-way Anova

Day 8

  • Multiple comparisons in ANOVA
  • MANOVA
  • ANCOVA

Day 9

  • Nonparametric statistics Mann-whitney U test Wilkcoxon signed-ranks test
  • Nonparametric statistics Chi-square tests and median test
  • Factor analysis
  • Log-linear analysis

Day 10

  • Multiple regression
  • Binomial logistic regression
  • Multinominal logistic regression