Discovering Statistics Using SPSS

REG517 Discovering Statistics Using SPSS

  • Topics

    Topics

  • Learning outcome

    Learning outcome

    At the completion of the course, students will be able to:

    • Understand how statistics can be used to analyze experimental data
    • Use analytical skills to correctly describe the results from various statistical analyses
    • Explain the role of assumptions regarding data in analyzing experimental data
    • Understand the use of correlation, regression, logistic regression, ANOVA, ANCOVA, MANOVA, and factor analysis to describe the results from experiments

  • Teaching

    Teaching

    Self - study

  • Required prerequisites

    Required prerequisites

    PhD Status

  • Requirements for course approval

    Requirements for course approval

  • Assessment

    Assessment

    All assignments should be completed to receive a pass grade.

     

    Assignments

     

    No.

    Chapter

    Problem/Task

    1.

    2: Everything you ever wanted to know about statistics (well, sort of)

    Problems: 2, 4, 5, 6, 7, 8, 9

    2.

    5: Exploring assumptions

    Tasks: 1, 2

    3.

    6: Correlation

    Tasks: 1, 2, 3

    4.

    7: Regression

    Tasks: 1, 2, 3

    5.

    8: Logistic regression

    Tasks: 1, 2, 3

    6.

    10: Comparing several means: ANOVA (GLM 1)

    Tasks: 1, 2, 5

    7.

    11: Analysis of covariance, ANCOVA (GLM 2)

    Tasks: 1, 2

    8.

    12: Factorial ANOVA (GLM 3)

    Tasks: 1, 2, 3

    9.

    16: Multivariate analysis of variance (MANOVA)

    Tasks: 1, 2

    10.

    17: Exploratory factor analysis

    Tasks: 1, 2

     

     

    Total: 7 problems, 23 tasks

  • Grading Scale

    Grading Scale

    Grading: Pass / fail.

  • Semester

    Semester

    Currently not offered 

     

  • Literature

    Literature

    Field, Andy, Discovering Statistics Using SPSS, 3rd edition, London: Sage Publications.

Overview

ECTS Credits
5
Teaching language
English.
Semester
Spring, Autumn

Course responsible

Professor Iris Stuart, Department of Accounting, Auditing and Law