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Using Microsoft Excel for Social Research

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Overview

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This course teaches social research methods using Microsoft Excel, from data cleaning to advanced statistical tests and effective presentation of research results through charts and reports. This resource provides a practical, hands-on approach to using Microsoft Excel for social research. It covers essential data preparation, analysis, and presentation techniques, helping learners build confidence in handling real-world data. The content is designed to support both academic and professional development in quantitative research methods. This resource is ideal for social science students, researchers, and professionals seeking to enhance their data analysis and presentation skills. A basic understanding of Excel and research methods is recommended to get the most out of the content. This course provides a comprehensive guide to using Microsoft Excel for social research. It starts with planning and undertaking research projects and progresses through essential Excel functions for data cleaning, statistical analysis, and visualization. It equips readers with practical skills to analyze data, interpret results, and present research effectively. This course is based on Using Microsoft Excel for Social Research, by Charlotte Brookfield. Copyright ©2021 by Sage Publications Limited. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies. Published by Sage Publications Limited, London. Used by arrangement with Sage Publications Limited.

Syllabus

  • Introduction
    • This module introduces learners to the use of Excel for social science research, covering statistical analysis, dataset reproducibility, and time-saving shortcuts. It also addresses the importance of statistics in social science education and how to approach quantitative methods effectively.
  • Planning and Undertaking a Research Project in the Social Sciences
    • 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.
  • Selecting, Evaluating and Cleaning Data Using Microsoft Excel
    • 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.
  • Getting Familiar with Your Data
    • 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.
  • Exploring Bivariate Relationships: Crosstabulations and Chi-Square Statistic
    • 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.
  • T-tests, ANOVA Test and Non-parametric Equivalents
    • 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.
  • Exploring Bivariate Relationships: Correlation
    • 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.
  • Exploring Multivariate Relationships: Linear Regression
    • 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.
  • Bringing It All Together: Writing and Presenting Research for Different Audiences
    • 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.

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