APPLIED STATISTICS (THEORY)

Paper Code: 
HFN 222
Credits: 
03
Contact Hours: 
45.00
Max. Marks: 
100.00
Objective: 
This course will enable the students to:
To understand the role of statistics and computer applications in research.
To apply statistical techniques to research data for analyzing and interpreting data carefully. 
 
 
9.00
Unit I: 
Introduction of Statistics.
Classifications and Tabulation of data. Frequency Distribution. Diagrammatic(one- dimensional and two- dimensional) and Graphical presentation of data( Histogram, Frequency Polygon, Frequency curve and ogives)
Measure of Central Tendency- Mean, Median and Mode, their properties, merits and demerits.
Measure of Dispersion- Range, Quartile Deviation, Mean Deviation and standard deviation.
                     
9.00
Unit II: 
Concept of Probability.
Properties of Normal Probability Curve and its applications.
Correlation Analysis- Definition and concept, types and measures of studying correlation (Karl Pearson’s coefficient of correlation, its assumptions, properties, merits and demerits, Spearman’s Rank correlation coefficient)
Regression Analysis- Definition, concept, uses and properties. Least Square Methods, Regression Coefficients, Fitting of Regression lines.
 
9.00
Unit III: 
Sampling Distribution and Standard Error
Elements of Testing a Statistical Hypothesis- Formulation of the problem, Types of errors . Level of significance, Large sample tests for proportions, Single mean and difference in two means. 
 
9.00
Unit IV: 
Small sample tests-
Application of  t- test for testing the significance of single mean & difference in two means ( independent and paired-t). Chi-square test for  testing normal population variance. Test for goodness of fit, independence of attributes using 2x2 and rxc contingency tables).
 
9.00
Unit V: 
Definations of F test, application of F test for testing of equality of two variances.
Definations of F test, application of F test for testing of equality of two variances.                                                                                   
Analysis of Variance- Concept , assumptions, basic idea of one way and way classification with simple questions. 
 
Academic Year: