Course Content
Data Visualization
0/6
Histogram
Frequency Polygon
Difference Between Histogram and Frequency Polygon
Relative Frequency Distribution
Cumulative Frequency Table
Box and Whiskers : IQR
Probability Distributions
Probability Distribution – Binomial, Poisson, Normal, and Exponential
0/3
Binomial Distribution
Poisson distribution
Exponential Distribution
Operations Management Basics
0/6
Time Study
Motion Study
EOQ: Economic Order Quantity
EOQ
Process Mapping Symbols
Key Figures in Operations Management
Statistics
0/7
Method of Least Square : Regression Analysis
Assumptions Regarding the Error Term in Regression
Demand Forecasting
Types of Reliability in Research
ISO 9000 Series Standards
Lean Manufacturing
5S Lean Methodology
Transportation
0/3
Tranportation Foundations
LCM: Least Cost Method
What is ERP (Enterprise Resource Planning)?
Facility Location and Layout
Site Selection and Analysis, Layout Design and Process
0/3
Plant Layout Design
Data Collection Method
Question ID
Concept, Measures of Central Tendency and Dispersion,
Concept, Measures of Central Tendency and Dispersion,
0/7
**Contingency Table (Cross-Tabulation Table)
**Measures of Central Tendency: Mean, Median & Mode
**Standard Deviation
**Karl Pearson’s Coefficient of Variation
**Positional Averages (Positional Means)
**Mathematical Averages (Mathematical Means)
Population Variance v/s Sample variance
Probability Distribution – Binomial, Poisson, Normal, and Exponential
Probability Distribution – Binomial, Poisson, Normal, and Exponential
0/4
Normal Distribution Example
**Binomial Distribution
**Queing Theory
**Queue Discipline
Data Collection & Questionnaire Design
Data Collection & Questionnaire Design
Sampling: Concept, Process, and Techniques
Sampling: Concept, Process, and Techniques
0/2
**Sampling Methods
–research process
Hypothesis Testing: Procedure
Hypothesis Testing: Procedure
0/2
**Hypothesis Testing
–Type I & Type II Errors
T, Z, F, Chi-square tests
T, Z, F, Chi-square tests
0/2
Types of Statistical Tests
Chi-Square Goodness of Fit Test
Correlation and Regression Analysis
Correlation and Regression Analysis
0/4
Correlation Coefficient
Regression Coefficient
Relationship Between Correlation Coefficient and Regression Coefficient
Correlation and Regression Analysis
Operations Management: Role and Scope
Operations Management: Role and Scope
0/1
–Introduction
Facility Location and Layout: Site Selection and Analysis, Layout Design and Process
Facility Location and Layout: Site Selection and Analysis, Layout Design and Process
Enterprise Resource Planning: ERP Modules, ERP Implementation
Enterprise Resource Planning: ERP Modules, ERP Implementation
Scheduling: Loading, Sequencing, and Monitoring
Scheduling: Loading, Sequencing, and Monitoring
0/4
–Scheduling
**Gant Chart
**Line Balancing
**Inspection Process and Types
Quality Management and Statistical Quality Control, Quality Circles, Total Quality Management – KAIZEN, Benchmarking, Six Sigma
Quality Management and Statistical Quality Control, Quality Circles, Total Quality Management – KAIZEN, Benchmarking, Six Sigma
0/3
**Kaizen
**Six Sigma
Benchmarking Generations
ISO 9000 Series Standards
ISO 9000 Series Standards
Operation Research: Transportation, Queuing Decision Theory, PERT/CPM.
Operation Research: Transportation, Queuing Decision Theory, PERT/CPM.
0/6
**Assignment: Complete Enumeration Method
–VAM: Vogel’s Approximation Method
**North-West Corner Method
**PERT: Program Evaluation and Review Technique
**CPM: Critical Path Method
**PERT VS CPM
Unit VIII: Business Statistics and Operations Management

Frequency Polygon

A frequency polygon is a line graph that represents a frequency distribution. It connects midpoints of class intervals with straight lines.

Key Features of a Frequency Polygon:

✔ It is created by plotting points at class midpoints and connecting them.
✔ The x-axis represents class midpoints, and the y-axis represents frequency.
✔ Can be used to compare multiple distributions on the same graph.

Example: Frequency Polygon for Student Test Scores

Class Interval (Marks) Midpoint Frequency (f)
0 – 10 5 5
10 – 20 15 8
20 – 30 25 12
30 – 40 35 10
40 – 50 45 15

🔹 Graph Interpretation:

  • The highest peak represents the most frequent category.

  • A smooth curve can be drawn for better visualization.

  • It helps in comparison between datasets.

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