SPSS Course

Statistics is a software package used for statistical analysis.

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

What you will learn

The developers of the Statistical Package for the Social Sciences (SPSS) made every effort to make the software easy to use. This prevents you from making mistakes or even forgetting something. That's not to say it's impossible to do something wrong, but the SPSS software works hard to keep you from running into the ditch.

  • Introduction and Data Access
  • Data Manipulation
  • Descriptive Statistical Analysis

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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