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Research Training


RESEARCH METHODOLOGY

Course Description

This course is designed to equip students with the essential skills and knowledge required to conduct rigorous and ethical research across diverse academic disciplines. Through a combination of theoretical lectures, hands-on exercises, and real-world applications, students will gain a comprehensive understanding of research process including research designs,sample size determination, sampling procedures, data collection methods, statistical analysis, and ethical considerations. By the end of the training, students will be well-prepared to undertake independent research projects and contribute meaningfully to the scholarly community.

Course Objectives

Understanding Research Foundations

Define the concept of research and its significance across disciplines.
Differentiate between basic and applied research.
Identify key characteristics of high-quality research.

Research Designs

Explore various research designs, both experimental and non-experimental.

Sample size and Sampling Procedure
Understand the principles of sampling and determine appropriate sample sizes.

Data Collection Instruments
Evaluate strengths and limitations of different data collection methods, such as surveys, interviews, and observations.

Data Analysis Techniques

Introduce basic statistical concepts for quantitative research.
Develop skills in using statistical software for data analysis.
Explore qualitative data analysis techniques for in-depth understanding.

Ethical Considerations

Examine the ethical principles guiding research conduct.
Understand the importance of obtaining informed consent and protecting participants’ rights.
Navigate the Institutional Review Board (IRB) process.

Assessment
Assessment in this course will be based on a combination of individual and group assignments, quizzes, and a final project. The final project will require participants to apply the knowledge gained throughout the course


DATA ANALYSIS

Course Description

This course provides a comprehensive introduction to the fundamental principles and techniques of data analysis. As businesses and industries increasingly rely on data-driven decision-making, the ability to analyze and interpret data has become a crucial skill. Whether you are a novice or have some background in data analysis, this course is designed to equip you with the essential tools and concepts to make sense of data and derive meaningful insights.

Course Outline

  1. Introduction to Data Analysis
    • Understanding the importance of data analysis in various domains.
    • Overview of the data analysis process.
    • Types of data and their characteristics.
  2. Data Exploration and Preparation
    • Exploratory Data Analysis (EDA) techniques.
    • Handling missing data and outliers.
    • Data cleaning and preprocessing.
  3. Data coding and Entry
    • Data coding using SPSS.
    • Entering Data .
    • Running output.
  4. Descriptive Analysis
    • Descriptive statistics: Frequencies, mean, standard deviation.
    • Hypothesis testing and confidence intervals.
  5. Regression Analysis
    • Simple and multiple linear regression.
    • Assessing the goodness of fit and making predictions.
    • Introduction to logistic regression.
  6. Ethical Considerations in Data Analysis
    • Privacy and security concerns.
    • Responsible use of data and avoiding biases.
  7. Final Project
      • Applying the knowledge and skills gained throughout the course to a comprehensive data analysis project.
      • Presenting findings and insights.

By the end of this course, students will have a solid foundation in data analysis, enabling them to extract valuable information from data sets and contribute meaningfully to decision-making processes in various professional contexts.

Recommended Textbook

Wanjohi, A.M. (2014). Social Research Methods Series: Proposal Writing Guide. Nairobi: KENPRO Publications.

Application

  • To apply for the training, kindly CLICK HERE and fill the form

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  • Academic Papers (53)
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  • Announcements (7)
  • ARJESS Publications (1)
  • Business Articles (15)
  • Education Articles (6)
  • El-Paradiso Demo Farm (2)
  • Environment Articles (12)
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