APPLIED STATISTICS -PRACTICAL

Paper Code: 
24HFN226
Credits: 
04
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

This course will enable the students to –

  1. Understand the role of statistics and computer applications in research.
  2. Apply statistical techniques to research data for analyzing and interpreting data carefully.

 

 

Course Outcomes: 

Course

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

Course Code

Course

title

24HFN226

Applied Statistics-Practical

(Practical)

 

 

COFN 69: To apply SPSS skills to manage data, including entering, organizing, saving, creating variables, and entering data for analysis.

 

COFN70: To describe data using Descriptive Statistics & Graphs in SPSS. 

 

COFN71: To Examine Relationships between variables by using Correlation & Regression technique.

 

COFN72: To Analyze and evaluate statistical hypotheses by comparing groups to determine significance

COFN73: To compile comprehensive practical records for numerical problems related to describing data, examine relationship and for comparing groups using SPSS.

COFN 74: Contribute effectively in course-specific interaction

 

Approach in teaching:

Interactive Lectures, Discussion, Power Point Presentations, Informative videos, group discussion

 

Learning activities for the students:

Self learning assignments, Effective questions, presentations, Field trips

Open Book Test,  Class test, Semester End Examination, discussion

 

CONTENTS

The following test should be performed on computer

·         Formation of frequency distribution table (inclusive and exclusive)

·         Graphical representation- histogram, frequency polygon, ogives

·         Measures of Central Tendency- Mean, Median and Mode

·         absolute and relative Measures of Dispersion- range, Quartile Deviation, Mean Deviation, Standard Deviation

·         Coefficient of correlation- karl pearson and spearmens rank

·         Fitting of Regression lines and prediction.

·         normal Distribution-area under the curve

·         Chi-square tests- Goodness of fit, Independence of Attributes 2x2 and rxc contingency tables, testing of single variance

·         Application of Student’s t-test for small samples- test of significance of single mean, difference in means, independent and paired T test.

·         F-test for two sample variances.

·         Analysis of Variance- one-way classification, two-way classification 

Essential Readings: 
  1. Gupta, S.P.: Statistical Methods, Sultan Chand and Company, New Delhi.
  2. Elhane,D.N.: Fundamentals of Statistics, Kitab Mahal, Allahbad.

 

Academic Year: 
2024-2025
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