Statistical Methods and Data Analysis (MDC-03)

Basic concepts of statistic

3 topics

• Population vs. sample, variables (categorical vs. numerical), datatypes
• Descriptive statistics: measures of central tendency (mean, median, mode)
• Measures of dispersion (range, variance, standard deviation)

Data Representation and Sampling technique

6 topics

• Graphical representation of data (histograms, box plots, scatter plots)
• Probability theory: basic probability concepts
• Probability distributions (binomial, normal distributions)
• Sampling techniques: random sampling, stratified sampling
• Sampling distributions
• Understanding the Bell curve

Introduction to R and working with Data

5 topics

• Overview of R and its applications in data analysis and statistics
• Installing R and RStudio
• Basic R syntax, variables, and data types
• Importing data into R from different file formats (CSV, Excel, etc.)
• Read, write and view data using data frames

Data Filtering and cleaning

5 topics

• Subsetting and filtering data
• Adding, removing, and renaming variables/attributes
• Data cleaning and transformation
• Identifying and handling missing values
• Data type conversion and recoding variables

Working with Data in R

7 topics

• Reordering and reshaping data frames
• Merging and joining data frames
• Calculating summary statistics (mean, median, mode, standard deviation)
• Generating frequency tables and cross-tabulations
• Commands for measures of central tendency and dispersion
• Concepts of normal distribution
• Commands to explore and view data distributions graphically (Bell curve)

Previous-year question papers

Published by VNSGU. These open on the university’s own site.

• November 2025MDC-302-Statistical Methods and Data Analysis
• March 2025MDC-STATISTICAL METHODS AND DATA ANALYSIS

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