This comprehensive course provides an in-depth exploration of quantitative research methods, equipping students with the knowledge and skills necessary to conduct rigorous quantitative studies. The course covers essential topics, including sampling techniques, one-sample t-test, paired sample t-test, independent sampling t-test, ANOVA (Analysis of Variance), and Chi-square analysis.
Sampling Techniques: Students will delve into various sampling techniques employed in quantitative research, such as random sampling, stratified sampling, and cluster sampling. They will learn how to select appropriate sampling methods based on research objectives and effectively handle issues of bias and generalizability.
One-Sample t-test: The course will focus on one-sample t-test, which enables researchers to assess whether a sample mean significantly differs from a hypothesized population mean. Students will learn how to conduct one-sample t-tests, interpret the results, and make informed conclusions based on statistical significance.
Paired Sample t-test: Students will gain an understanding of paired sample t-tests, which compare means between two related groups or conditions. They will learn how to design studies using a pre-test/post-test design and analyze paired data to determine if there is a significant difference in means.
Independent Sampling t-test: The course will cover independent sampling t-tests, which examine differences in means between two independent groups. Students will explore the steps involved in conducting independent t-tests, interpret the results, and evaluate the significance of observed differences.
ANOVA (Analysis of Variance): Students will be introduced to ANOVA, a statistical technique used to analyze differences among three or more groups. They will learn the principles and assumptions underlying ANOVA, conduct ANOVA tests, and perform post-hoc analyses to identify specific group differences.
Chi-square Analysis: The course will delve into chi-square analysis, a non-parametric statistical method used to determine the association between categorical variables. Students will learn how to perform chi-square tests, interpret the results, and understand the practical implications of significant associations.
Throughout the course, students will engage in hands-on activities, exercises, and real-world examples to reinforce their understanding of these quantitative research methods. They will also learn to use statistical software for data analysis and interpretation.
By the end of the course, students will possess the skills to design sound quantitative research studies, collect and analyze data using appropriate techniques, and draw valid conclusions. They will be equipped to apply these methods in various domains, contributing to evidence-based decision-making and advancing knowledge in their respective fields
