Statistical Package for the Social Sciences Online Training

SPSS (Statistical Package for the Social Sciences) has now been in development for more thanthirty years. Originally developed as a programming language for conducting statistical analysis, it has grown into a complex and powerful application with now uses both a graphical and a syntactical interface.

Statistical Package for the Social Sciences Online Training Course Content
  • Introduction and Data Access
    • Opening a data file and viewing its contents
    • Creating new variables and entering data
  • Data Manipulation
    • Creating grouped variable from a continuous Variable
    • Selecting Case
    • Weighting
  • Descriptive Statistical Analysis
    • Describing a continuous variable: measures of central tendency and dispersion; histogram
    • Describing a categorical (ordinal) variable: frequency table, bar chart
  • Bivariate (exploring relationships between pairs of variables)
    • Contingency tables: Describing the association between two categorical variables
    • Correlation coefficients: Describing the association between two continuous variables
    • Drawing a scatter plot: Visualising the association between two continuous variables
  • Inferential Statistical Analysis
  • With Quantitative Responses Variable
    • Independent samples t-test: Comparing the means of two groups
      (continuous response variable, binary explanatory variable)
    • Simple linear regression: Testing the linear
      association between two continuous variables
      (continuous response variable, continuous explanatory variable)
    • Multiple linear regression: Testing the linear association
      between a continuous response variable and more than one explanatory variable (continuous response variable,
      explanatory variables various levels of measurement)
  • With Qualitative Responses Variable
    • Two-way contingency table and chi-squared test: Testing
      the association between two categorical variables
    • Three-way contingency table and chi-squared tests: Testing the association between two
      categorical variables conditioning on levels of a third categorical variable
    • Binary logistic regression: Testing the association between a binary response variable and explanatory
      variables with various levels of measurement

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