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SPSS Training, Kabul

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Data Management and SPSS training is going to take place by May 16,2015 in Kabul:

Duration: 5 Days 

Trainer: International

Course outline

Day 1

Basics of SPSS. Descriptive statistics, charts and graphs, hypothesis analysis, testing dependence/independence.

  • Different levels of measure: scale, ordinal, nominal.
  • Basic descriptive statistics. Measures of central tendency: mean, median, mode. Measures of dispersion: range, standard deviation, variance.
  • Graphs and charts: bar chart, pie chart, histogram, scatter plot. Which of them should be used in different situations?
  • Hypothesis analysis with SPSS. Testing dependence/independence, Pearson’s chi-square. Levels of significance.
  • SPSS in practice, some useful tips. The "tricks" of dependence/independence testing
  • Converting different types of files into ".sav" files. How can one enter raw data into SPSS efficiently, how to label the data.
  • Transforming the data.
  • Multiple independence analysis - a useful way to circumvent "significance level problems".
  • Elementary principal component analysis.

Day 02

Principal Component Analysis with SPSS.

  • Definition and meaning of the principal component.
  • Communalities, extraction, variance.
  • Usability of the method (the cases of scale and ordinal measures).
  • Information content and the distribution of the principal component.
  • Omission of variables with insufficient communalities.
  • Factor Analysis with SPSS using a "real example".
  • The factor matrix and its interpretation.
  • The Maximum Likelihood method. Repairing the model.
  • Factor rotation and the varimax method.
  • Omission of variables belonging to more than one factor, the appearance of latent variables.
  • Establishing factor scores. Statistics of factor scores.
  • When the factors explain more than 100%. A common pitfall.

Day 03

  • Explanatory models. Analysis of Variance, Regression Analysis.
  • Using SPSS for Analysis of Variance (ANOVA)
  • Twofold ANOVA, interaction.
  • Linear regression analysis. When should we accept a regression line?
  • Two variable regressions.

Day 04

  • Charts and tables
  • Simple charts: bar, pie, histogram
  • Compound charts, chart builder
  • Chart editing, 3D effects, color and fill
  • Adding special effect to charts, jittering, plethora of graphs
  • Saving and manipulating tables

 

Day 05 

  • SPSS Syntax         
  • Syntax files
  • The syntax editor
  • Writing syntax using the Log
  • Open up SPSS files using syntax
  • Define variables using syntax
  • Create compute and auto-record procedures
  • Create simple and multiple IF and DO-IF statements