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SKILL ENHANCEMENT COURSES

SEMESTER IV

SEC1 – SKILL ENHANCEMENT COURSE
KU4SECSTA251: STATISTICAL COMPUTING AND DATA VISUALIZATION BY MS EXCEL
SemesterCourse TypeCourse LevelCourse CodeCreditsTotal Hours
IVSKILL ENHANCEMENT200 – 299KU4SECSTA251360

Learning Approach (Hours/Week) / Marks Distribution
LecturePractical/InternshipTutorialCEESETotalDuration of ESE (Hours)
22-2550751½
Course Description

The course provides an introduction to statistics, covering definitions, data types, collection, presentation methods, Excel operations, data representation through various charts and graphs, and summary statistics including measures of central tendency, dispersion, correlation, and regression analysis.

Course Prerequisite

Foundation Courses (Level 100 – 199)

Course Outcomes
CO No.Expected OutcomeLearning Domains
1Understand the fundamental definition and significance of statistics in various fields.U
2Demonstrate proficiency in differentiating and categorizing various types of data.R
3Acquire skills in employing data collection techniques and presenting data effectively using Excel.U
4Apply different methods for summarizing data, including measures of central tendency and dispersion.A
5Analyse and interpret data representations such as histograms, scatter plots, and pie charts, and perform basic statistical analyses like correlation and regression.An
COURSE CONTENTS
Contents for Classroom Transaction
ModuleDescriptionHoursContents
1Introduction to Statistics7
  1. Definition of Statistics and its importance
  2. Types of data
  3. Data collection and presentation methods
  4. Data summarization methods
2Introduction to Excel7 Data operations, creating forms to enter data – concatenation of text, numbers
Splitting of data into columns, sort and reverse sort
Grouping and ungrouping of data
3Data Representation8
  1. Histogram, line diagram
  2. Box plots, scatter plots
  3. Bar charts – stack, subdivided
  4. Pie charts, radar graphs
4Summary Statistics8
  1. Arithmetic Mean, Median, Mode
  2. Range, Standard Deviation, Coefficient of Variation
  3. Simple Correlation, correlation graph, rank correlation
  4. Simple Regression
5Open End30 Practical using MS Excel
History of Statistics, Data entry using MS Excel, Understanding the usage of various statistical and mathematical functions in Excel, Preparation of diagrams explained in Module 4 by Excel, Preparation and submission of a report.
Essential Readings
  1. Sarma, K. V. S. (2010). Statistics Made Simple: Do it Yourself on PC, Prentice Hall India Learning Pvt. Ltd.
  2. Wayne, W. L. (2019). Microsoft Excel: Data Analysis & Business Model, Microsoft Press.
Suggested Readings
  1. Nelson, S. L. and Nelson, E. C. (2018). Microsoft data analysis for dummies, Wiley.
  2. Berk, K. N. and Carey, P. (2000), Data Analysis with Microsoft Excel, S. Chand (G/L) & Company Ltd, 3/e.
Assessment Rubrics
Evaluation TypeMarksEvaluation TypeMarksTotal
Lecture50Practical2575
End Semester Evaluation35End Semester Evaluation15
Continuous Evaluation15Continuous Evaluation10
a) Test Paper- 15a) Punctuality2
b) Test Paper-25b) Skill3
c) Assignment/ Viva-Voce5c) Assignment/ Field Report5
Total50Total2575

SEMESTER IV

SEC2 – SKILL ENHANCEMENT COURSE
KU4SECSTA252: BASICS OF STATISTICAL INFERENCE
SemesterCourse TypeCourse LevelCourse CodeCreditsTotal Hours
IVSKILL ENHANCEMENT200 – 299KU4SECSTA252360

Learning Approach (Hours/Week) / Marks Distribution
LecturePractical/InternshipTutorialCEESETotalDuration of ESE (Hours)
22-2550751½
Course Description

This course introduces the fundamental principles and methods of statistical inference, covering sampling distributions, estimation theory, hypothesis testing, and the application of large and small sample tests for drawing valid conclusions from data.

Course Prerequisite

Foundation Courses (Level 100 – 199)