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MST-004 Statistical Inference

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MST-004 Statistical Inference

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MST-004 Statistical Inference focuses on the principles and methods of drawing conclusions about populations based on sample data, crucial for advanced statistical analysis.
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  • Comprehensive coverage of estimation techniques.
  • Detailed exploration of hypothesis testing.
  • Practical examples of confidence intervals.
  • Extensive discussion on non-parametric methods.
Category : POST GRADUATE DIPLOMA PROGRAMMES
Sub Category : Post Graduate Diploma in Applied Statistics (PGDAST)
Products Code : PGDAST-MST-6.07
HSN Code : 490110
Language : English
Author : BMAP EDUSERVICES PVT LTD
Publisher : BMAP EDUSERVICES PVT LTD
University : IGNOU (Indira Gandhi National Open University)
Pages : 50
Weight : 199 GM
Dimensions : 21.0 x 29.7 cm (A4 Size Pages)



Details

MST-004 Statistical Inference is an essential course for students pursuing a Post Graduate Diploma in Applied Statistics (PGDAST). This subject delves into the foundational concepts and methodologies required for making informed inferences from statistical data. Key topics include estimation techniques, hypothesis testing, confidence intervals, and non-parametric methods. Each chapter is designed to provide a deep understanding of these critical areas, supported by practical examples and exercises. This book is not only a vital academic resource but also a practical guide for real-world statistical applications.

Benefits:

  • Comprehensive Understanding: Gain a thorough understanding of statistical inference, which is essential for any advanced statistical analysis.
  • Exam Preparation: The book is tailored to cover important questions frequently asked in exams, making it an invaluable resource for IGNOU guess papers.
  • Practical Application: Learn through practical examples and exercises that help in applying statistical methods effectively.
  • Focused Content: With 50-60 pages of targeted content, students can efficiently grasp key concepts without being overwhelmed by excessive information.

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