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University Syllabus Course For BCA Computer Oriented Statistical Methods

Atlanta Computer Institute Nagpur conducts Tuition Classes for BCA First Year (  Part 1 ) , BCA  Second Year (   Part 2  ) and BCA Final Year ( Part 3 ) for all universities in India . The Following syllabus is of Nagpur University.  Final Year Projects Training is also given to  BCA  Students.
 
 
BCA Bachelor of Computer Applications   Part 1

 BCA Part 1 ( First Year ) 

SUBJECT-III     ANALYTIC COMPUTATION


Paper-2:Computer oriented statistical methods

Unit-1:   Introduction

Definition  of statistics, importance    and  scope  of  statistics,limitation of  Statistic,  distrust  of  statistics.  Statistical   data  collection-  primary  and  secondary   data, methods  of  collecting  primary   data  Sources  and secondary  data, Census  and  sample  investigation.  Presentation   of  statistical  data-  classification   , Tabulation, frequency  distribution, graphic  representation   of  a  frequency  distribution,average  or measure  s of  central   tendency or  measures  of  locations, requisites  for  an  ideal  measure of  central  tendency-Arithmetic :   Mean, median,mode,eometric mean  and Harmonic  Mean, weighted   Average, Relatrionship amongst   different  averages.

 Unit-2:    Measures   of  Dispersion, Skeewness  and  kurtosis

Meaning      and   significance  of  dispersion, methods  , of  measuring  dispersion- range,quartile, mean  deviation,    standard  deviation, coefficient  of  skweness, kurtosis, coefficient  of  dispersion, coefficient  of  variation. Co relation   and  regression-definition   of  correlation, scatter diagram, karl pearson  coefficient  o  correlation, limits for  correlation  coefficient, definition  of  regression, lines  of  regression, regression  curves, regression  coefficients,properties  of regression coefficients, correlation   analysis vs.  regression  analysis.

Unit-3:   probability

Introduction , definitions  of  various    terms, mathematical   or  classical   probability, statistical   or  empirical    probability,  mathematical  tools, sets    and  elements of  sets, operation s   on sets,axomatic approach  to probability, probability  function ,  mathematical    law  of  addition  of probability and  conditional  probabilities, independent  events, bayes   theorem, geometric    probability.

Unit-4  Random  variables    and    distribution   functions

Definition  of   random  variable  , distribution  function, properties   of  distribution  function,disctrete   random   variable,probability   mass    function,discrete    distribution function , continuos   random  variable,  continuous   density  function, continuous  distribution   function.Mathematical   expectation  and  Generation   function  -  definition    of   mathematical    expectation  , addition  &  multiplication   theorem   of   expectation , co-variance  , expectation &  variance   of  a linear   combination  of  random  variables, moment  generating   function,   cumulants.

Unit-5:    Theoreitical   discrete   distributions

Introduction  , bernouli  distribution ,  binomial  distribution,poisson  distribution, geometric  distribution  . theoretical   continuous  distributions- introductuion, normal  distribution, gama distribution, cauchy’s  distribution  and   central  limit  theore

 


 

 

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