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محمد عبد الله عبد القادر

Assistant Professor

عضو هيئة تدريس

كلية العلوم
2B27
مادة دراسية

Stat 332

Outline Stat 332
Regression Analys
Instructor:  Dr. Mohamed Abdelkader
Office: 2B27 Building #4,  Phone (office): 76269
 E-mail:  aabdelkader1.c@ksu.edu.sa       
Textbook: 
Applied Linear Regression Models, Fifth Edition by Kutner, Nachtsheim and Neter
Data:
http://users.stat.ufl.edu/~rrandles/sta4210/Rclassnotes/data/textdatasets/Chapter%20%201%20Data%20Sets.html
 
  كتاب مترجم للطبعة الرابعة
نماذج إحصائية خطية تطبيقية ( الجزء الأول)  
المؤلف:  نيتر واخرون .ترجمة: د. انيس كنجو – د. عبد الحميد الزيد – د. الحسيني عبد البر
 
Course Scope and Contents
This course is an introduction to applied data analysis. We will explore data sets, examine various models for the data, assess the validity of their assumptions, and determine which conclusions we can make (if any). Data analysis is a bit of an art; there may be several valid approaches. We will strongly emphasize the importance of critical thinking about the data and the question of interest. Our overall goal is to use a basic set of modeling tools to explore and analyze data and to present the results in a scientific report. We then consider simple linear regression, a model that uses only one predictor. After briefly reviewing some linear algebra, we turn to multiple linear regression, a model that uses multiple variables to predict the response of interest. For all models, we will examine the underlying assumptions. More specifically, do the data support the assumptions? Do they contradict them? What are the consequences for inference? Also, we will explore some nonlinear models and data transformations. Finally, we discuss Linear regression based on the categorical with some applications
 

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