Elements of Statistical Inference
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Abstract
This text explores the principles and applications of inferential statistics, emphasizing its role in decision-making. It guides readers on using statistical methods to interpret data and make informed inferences about populations based on samples. Topics include estimation, hypothesis testing, and understanding evaluation and research reports. Practical examples illustrate the application of these concepts in real-world scenarios, such as education, workplace productivity, and program evaluation. The material is aimed at professionals who need to interpret statistical data without engaging in complex computations.
Description
The document introduces key concepts of inferential statistics, focusing on estimation and hypothesis testing. It provides a foundation for decision-makers to read and understand research and evaluation reports. Examples cover educational programs, workplace productivity, and career development initiatives, highlighting the importance of making data-driven inferences. Emphasis is placed on practical applications over computational details, making it accessible for non-specialists.
Keywords
Statistical inference, Inferential statistics, Decision making, Data analysis, Research methods, Evaluation reports