Statistical Data Analysis in Research Projects

Course Leader: Rui Alberto Ferreira Jesus

Home Institution: CESPU - Cooperativa de Ensino Superior, Politécnico e Universitário, CRL, Portugal

Course pre-requisite(s): Basic computer literacy

 

Course Overview

This course presents the usual work cycle when treating the data collected during a research project. To do so, there will be presented several statistical tools in a well-known software package – SPSS from IBM – with a strong emphasis in how to interpret those statistic results and connect them to the research objectives that guided the project.

Learning Outcomes

By the end of this course, students will be able to do and interpret a statistical analysis of the data collected during a research project. From the construction of a database to hold the data, to performing a descriptive statistical analysis and then, an inferential statistical analysis, students will be able to use the statistical package SPSS, from IBM, to respond to the research questions of a scientific project.

Course Content

  1. Defining the Variables

A1. Data Types and Scales of Measurement

  1. Choosing the data analysis methods

B1. What are the dependencies of data analysis methods?

B2. Descriptive Statistics data analysis techniques

B3. Inferential Statistics data analysis techniques

  1. Data input and edition in SPSS
  2. Statistical analysis of data

D1. Descriptive Statistics vs. Inferential Statistics

D2. Univariate descriptive statistics

D3. Bivariate descriptive statistics

D4. Inferential statistics

D4a. Central Limit Theorem

D4b. How to conduct a Hypothesis Test

D4b1. Tests of normality of a variable (Shapiro-Wilk and Kolmogorov-Smirnov)

D4b2. Tests to measure the correlation between variables (of Pearson and of Spearman)

D4b3. Tests to measure differences between proportions (Binomial and Chi-square)

D4b4. Tests to measure differences between means

D4b4a. One-sample t-test and Wilcoxon signed-rank test

D4b4b. Two independent samples (independent samples t-test and Mann-Whitney test)

D4b4c. Three or more independent samples (one way ANOVA and Kruskal-Wallis test)

D4b4d. Two paired samples (paired samples t-test and Wilcoxon signed-ranks test)

D4b4e. Three or more paired samples (Friedman test)

Instructional Method

The main instructional approach that will be used during the course is Direct Instruction. This model includes "I do" (instructor), "We do" (instructor and students), "You do" (student practices on their own with instructor monitoring).

Required Course Materials

For this course I will need a computer room (ideally with one PC for each student), with the SPSS software installed (version 27 or later), and a page in your learning management system (LMS), to provide the course’s didactic materials to the students (if you don't have an LMS, I can use my own).

Assessment

The evaluation will consist of quizzes and practical assignments to be done in SPSS.