This module equips learners with essential skills for planning and executing a research project in the social sciences. It covers time management, ethical considerations, and practical tools like Gantt charts in Excel. Learners will gain a structured approach to research design and project organization.

This module provides learners with essential skills in data preparation, including referencing datasets, identifying and handling non-numerical values, and using Excel functions like VLOOKUP, HLOOKUP, and CONCATENATE. It also covers techniques for filtering data, assessing data quality, and evaluating reliability and validity in research.

This module covers essential data analysis techniques using Excel, focusing on measures of central tendency, spread, and normality checks. Learners will gain hands-on skills in interpreting and visualizing data through practical exercises with real datasets.

This module teaches learners how to analyze bivariate relationships using crosstabulations and the chi-square statistic. It covers the creation of pivot tables in Excel and the interpretation of statistical results for survey data. Learners will develop skills in data analysis and evidence-based decision-making.

This module covers statistical analysis techniques such as F-tests, T-tests, and ANOVA, as well as their non-parametric alternatives like the Mann-Whitney U and Kruskal-Wallis tests. Learners will gain hands-on experience using Excel to compare group variances, analyze data distributions, and interpret real-world survey datasets.

This module covers the fundamentals of bivariate analysis, focusing on Pearson's r and Spearman's rho correlation coefficients, scatterplots, and Excel techniques for data visualization and interpretation. Learners will develop skills to analyze relationships between two variables using real-world datasets.

This module focuses on understanding and applying multiple linear regression techniques using Excel. It covers the analysis of categorical variables and their integration into regression models, along with hands-on practice using real-world datasets.

This module focuses on effective research communication by teaching learners how to analyze data, create clear visual representations, and present findings to diverse audiences using tools like Excel. It covers techniques for formatting tables, designing interactive charts, and using maps to enhance data understanding.