Elements of Statistical Inference

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dc.date.accessioned2024-12-31T06:22:44Z
dc.date.available2024-12-31T06:22:44Z
dc.date.issued0000
dc.descriptionThe 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.
dc.description.abstractThis 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.
dc.identifier.urihttp://192.9.200.215:4000/handle/123456789/313
dc.language.isoen
dc.subjectStatistical inference
dc.subjectInferential statistics
dc.subjectDecision making
dc.subjectData analysis
dc.subjectResearch methods
dc.subjectEvaluation reports
dc.titleElements of Statistical Inference
dc.typeOther

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