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Magdy Nagy Ahmed Ramadan

أستاذ مساعد

استاذ مشارك

كلية العلوم
College of Science, Building 4, Office 2B-28
مادة دراسية

Statistical packages(Stat 328)

Course outline

STAT 328 (Statistical Packages) 3 credit hours

Instructor:  Dr. Majdy Najy Ahmed

Office:  2B20 Building #4,  Phone (office): 4676270

Room:    2B 28 Building #4

 E-mail:  mnaji@ksu.edu.sa       

Text Books: 

  1. Minitab Guide, Second Edition Desmond J. Higham and Nicholas J. Higham A-Jin Publishing Company. Latest version
  2.  Excel 2010 guide to accompany understanding basic statistics

sixth edition

  1. SPSS Guide to Data Analysis by Marija Norse’s. . Latest version
  2. Hector Guerrero. Excel Data Analysis: Modeling and Simulation,  Springer. . Latest version
  3. SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM Spss. Latest version
  4. Alain F. Zuur l Elena N. Ieno Erik H.W.G. Meesters. A Beginner’s Guide to R, Springer. Latest version

Course Scope Contents: 

Using program code in a statistical software package (Excel – Minitab – SAS – SPSS - R) to write a program for data and statistical analysis.  Topics include creating and managing data files, graphical presentation - and Monte Carlo simulations.



Topics Covered

 

Week1: Introduction to statistical analysis using excel.

Week2: Some mathematical and logical functions in Excel.

Week3: Descriptive statistics using excel.

Week4: Statistical tests using excel.

Week5: Correlation and regression using excel.

Week6: Introduction to Minitab - Descriptive statistics using Minitab.

Week7: Statistical distributions in Minitab.

Week8: Statistical tests using Minitab.

Week9: Correlation and regression using Minitab.

Week10: Introduction to SPSS - Descriptive statistics using SPSS.

Week11: Statistical tests using SPSS - Correlation and regression using SPSS.

Week12: Introduction to R - Statistical and mathematical functions in R.

Week13: Descriptive statistics using R - Statistical distributions in R.

Week14: Statistical tests using R - Correlation and regression using R.

Week15: Applications, Programming and simulation in R.

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