Certificate in Program Evaluation: Data Analysis and Interpretation
-- ViewingNowThe Certificate in Program Evaluation: Data Analysis and Interpretation is a comprehensive course that equips learners with essential skills in data analysis and interpretation for program evaluation. This course is crucial in today's data-driven world, where organizations require professionals who can analyze data, interpret results, and use findings to improve programs and decision-making processes.
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⢠Descriptive Statistics & Data Analysis: Understanding the basics of data analysis, including measures of central tendency, dispersion, and correlation, to effectively interpret and present program evaluation data.
⢠Inferential Statistics & Hypothesis Testing: Learning the principles of inferential statistics and hypothesis testing to make data-driven decisions and evaluate program effectiveness.
⢠Data Visualization & Presentation: Mastering effective data presentation techniques and tools to communicate evaluation findings to stakeholders.
⢠Quantitative Research Methods: Gaining in-depth knowledge of quantitative research methods and their application in program evaluation.
⢠Qualitative Research Methods: Understanding the principles and best practices of qualitative research methods and their use in program evaluation.
⢠Mixed Methods in Program Evaluation: Exploring the integration of qualitative and quantitative methods in program evaluation to gain a more comprehensive understanding of program effectiveness.
⢠Sampling Techniques: Learning about different sampling techniques and their implications for program evaluation, including probability and non-probability sampling.
⢠Data Collection & Management: Acquiring the skills necessary to design and implement effective data collection strategies and manage large datasets.
⢠Evaluation Design & Theory: Understanding the principles of evaluation design and theory, including formative, summative, and process evaluation.
⢠Ethics in Program Evaluation: Examining ethical considerations and best practices in program evaluation, including informed consent, confidentiality, and data security.
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