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MST 017 Applied Regression Analysis | Guess Papers of IGNOU

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MST 017 Applied Regression Analysis | Guess Papers of IGNOU

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MST 017 Applied Regression Analysis focuses on understanding regression models and their applications in statistical data analysis. This course is essential for mastering predictive modeling and data interpretation techniques.
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  • In-depth coverage of simple and multiple regression models.
  • Comprehensive analysis of model diagnostics and validation techniques.
  • Practical applications using statistical software.
  • Emphasis on real-world data and case studies.
Category : MASTER‘S DEGREE PROGRAMMES
Sub Category : Master of Science (Applied Statistics) (MSCAST)
Products Code : MSCAST-MST-S2-5.51
HSN Code : 490110
Language : English, English
Author : BMAP EDUSERVICES PVT LTD
Publisher : BMAP EDUSERVICES PVT LTD
University : IGNOU (Indira Gandhi National Open University)
Pages : 50
Weight : 157gms
Dimensions : 21.0 x 29.7 cm (A4 Size Pages)



Details

MST 017 Applied Regression Analysis is a crucial course for students pursuing a Master of Science in Applied Statistics. This subject provides a thorough understanding of regression models, which are fundamental tools for statistical data analysis. Students will learn about simple and multiple regression models, model diagnostics, and validation techniques. The course also includes practical sessions using statistical software, allowing students to apply their knowledge to real-world data and case studies. By mastering these skills, students will be well-prepared for careers in data analysis, research, and various fields requiring predictive modeling.

Benefits:

  • Master Predictive Modeling: Gain expertise in creating and interpreting regression models.
  • Practical Skills: Learn to use statistical software for real-world data analysis.
  • Exam Preparation: The book covers important questions and topics likely to appear in exams, helping students score better.
  • Career Advancement: Enhance your data analysis skills, making you more competitive in the job market.

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