Statistical Packages (STAT-301)

Introduction:

This course is an introduction to four statistical software packages, Minitab, EViews, SPSS and R, which are often used in professional practice. After studying this course, students will be able to understand about inserting, coding, sorting, filtering and grouping variables on above-mentioned statistical software packages. It deals with Implementing statistical tools like all measures of central tendency, dispersions, graphical procedures, measures of correlational structures, simple and multiple regression, time series analysis and various estimation and testing procedures. Computation of probability of different events and dealing with probability distributions are also of major concerns. It provides an understanding to tackles real-life variables as well as the artificial environment of random variables by simulation. Also, it signifies how to perform complex statistical analysis like principal component analysis, factor analysis, culture analysis and discernment analysis on above-mentioned statistical software packages.

Pre-requisite: STAT-5103

Learning outcomes:

  • Students will learn the basics of the statistical software packages (Minitab, EViews, SPSS and R) for reading, processing, transforming, visualizing and analyzing data.
  • Students will able to analyze data for their thesis or dissertation and other purposes.
  • This course will not teach Statistics but will enable students to become familiar with powerful and widely-used programs for data management and analysis.

Textbooks:

  1. Ryan, B. F., Joiner, B. L., & Cryer, J. D. (2012). MINITAB Handbook: Update for Release. Cengage Learning.
  2. Lesik, S.A. (2009). Applied Statistical Inference with Minitab. CRC Press, New York.
  3. Bassi, I. (2007). Six Sigma Statistics with Excel and Minitab. McGraw Hill, New York.
  4. Agung, I. G. N. (2011). Time series data analysis using EViews. John Wiley & Sons.
  5. Agung, I. G. N. (2011). Cross section and experimental data analysis using EViews. John Wiley & Sons.
  6. Landau, S. (2019). A handbook of statistical analyses using SPSS. Chapman & Hall.
  7. Rajathi, A., & Chandran, P. (2015). SPSS for You. MJP Publisher, India.
  8. Leech, N. L., Barrett, K. C., & Morgan, G. A. (2014). IBM SPSS for intermediate statistics: Use and interpretation. Routledge.
  9. Hothorn, T., & Everitt, B. S. (2014). A handbook of statistical analyses using R. CRC press.
  10. Dalgaard, P. (2008). Introductory statistics with R. Springer.

Course Plan:

 

Week

Topics and Readings

Books

1

Introduction to Minitab 19

Getting started with Minitab 19 for windows (4-7)

2

Importing and preparing data, Repeat an analysis with Minitab

Getting started with Minitab 19 for windows (50-59)

3

Descriptive Statistics and Graphical representation of data with Minitab

Applied Statistical Inference with Minitab (15-74)

4

Estimation and Testing of the hypothesis of univariate and bivariate data sets with Minitab

Applied Statistical Inference with Minitab (83-153)

5

Regression analysis and Analysis of variance with Minitab

Applied Statistical Inference with Minitab (155-348)

6

Time series analysis and forecasting with Minitab

MINITAB Handbook

7

Introduction to EViews 10

EViews 10 getting started

8

Regression analysis with EViews

Cross section and experimental data analysis using EViews

9

Time series analysis and forecasting with EViews

Time series data analysis using EViews

10

Introduction to SPSS 26.

IBM SPSS Statistics 26 Brief Guide

11

Variable naming and Data entry in SPSS.

SPSS for You (23-38)

12

Descriptive analysis and Graphical representation of qualitative and quantitative univariate, bivariate and multivariate data sets

SPSS for You (39-74)

13

Estimation and Testing of the hypothesis of univariate and bivariate data sets with Minitab

SPSS for You (75-91)

14

Regression analysis with SPSS

SPSS for You (142-155)

15

Introduction to R, Variable naming and Data entry in R.

A handbook of statistical analyses using R (1-14)

16

Descriptive Statistics and Graphical representation of a data with R

Introductory statistics with R (67-93)
 

Assessment criteria:

Mid Exam:          30

Final exam:         50

Sessional (Assignment, Presentation, Participation, Attendance, Quizzes):             20
 

Time Table:      

BS 5th Reg:        Tuesday (08:00-09:00)      Thursday(10:00-11:00)     Friday(10:00-11:00)

 

Course Material

Other Courses by Summera Kinat