Statistics Practical-I

Paper Code: 
24STT125
Credits: 
4
Contact Hours: 
120.00
Max. Marks: 
100.00
Objective: 

This paper is designed so that the student get familiar with statistical software for solving the problems based on various mathematical operations and also how to deal and analyse the probability of different data.

 

Course Outcomes: 

Course

Course Outcomes

Learning and teaching strategies

Assessment Strategies

Course Code

Course Title

24STT125

Statistics Practical-I

(Practical)

CO 25: Identify and collect relevant data from various sources, including databases, surveys, and web scraping techniques. 

CO 26: Apply statistical tools to analyze data and address questions. 

CO 27: Interpret the results of statistical analyses accurately and effectively and develop the ability to draw meaningful conclusions.

CO 28: Demonstrate the ability to communicate statistical concepts, methodologies, and findings clearly and concisely both orally and in writing.

CO 29: Contribute effectively in course-specific interaction.

Approach in teaching: 

Interactive Lectures, 

Group Discussion, 

Classroom Assignment,

Problem Solving Sessions.

 

Learning activities for the students:

Assignments,

Seminar,

Presentation,

Subject based  Activities.

Software based Assignments,

Class Test,

Record,

Viva-voice.

 

List of Practical Exercises:

 

  1. Data frame, data types in R.
  2. Call directories in R.
  3. Indexing and slicing of data in R.
  4. Creating matrices and their operation in R.
  5. Merging, importing and exporting of data in R.
  6. List and its operation in R.
  7. Graphical representation in R.
  8. Table manipulation in R.
  9. Descriptive statistics in R.
  10. Conditional statement in R.
  11. Construct multiple plot and sub plots in python.
  12. Data types in python.
  13. Panda and numpy library in Python.
  14. Input output function in python.
  15. String function in python.
  16. List function in python.
  17. For loop in python.
  18. Descriptive statistics in python.
  19. Array in python.
  20. Basic matrix operation in python.

 

Note: Practical exercises will be conducted on computer by using Python/R.

 

ESSENTIAL READINGS: 

  • Sudha, Sharad, Shailaja (2015): Statistics using R: Alpha Science International Ltd
  • R Programming An Approach to Data Analytics (2023): MJP Publishers    
  • R for Data Science (2023): Hadley Wickham, Mine Çetinkaya-Rundel:Shroff/O’Reilly Pvt. Ltd

 

Scheme of Evaluation for Continuous Assessment

Practical (30 %)

Time Duration: 60 minutes

Students are required to attempt 2 questions Out of 3 questions.

Experiment 1

Experiment 1

 Practical Record

Viva Voce

Attendance

Total

5

5

10

05

05

30

 

Scheme of Evaluation for Semester End Examination

Practical (70 %)

Time Duration: 3 hrs.

Students are required to attempt 3 questions Out of 5 questions.

Experiment 1

Experiment 2

Experiment 3

VIVA VOICE

TOTAL

20

20

20

10

70

 

 

Note: Scientific calculators are allowed in all papers of continuous assessment and semester end exam.

 

Academic Year: 
2024-2025
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