BCA
BCA

BCANEPExaminationScheme 1/1

Semester1 8/8

Lecture 2.1B23CAP101 Problem Solving through CPreview

Lecture 2.2B23CAP102 Foundations of Computer SciencePreview

Lecture 2.3B23CAP103 Logical Organization of ComputerPreview

Lecture 2.4B23CAP104 Mathematical Foundations for Computer ScienceIPreview

Lecture 2.5B23BBAMDC102 Social Media MarketingPreview

Lecture 2.6B23AEC111 English Language and Communication Skills: Level 1Preview

Lecture 2.7B23SEC101 Office and spreadsheet Tools LearningPreview

Lecture 2.8B VAC 101 Human Values and EthicsPreview


Semester2 8/8

Lecture 3.1B23CAP201 Object Oriented Programming using C++Preview

Lecture 3.2B23CAP202 Introduction to Web TechnologiesPreview

Lecture 3.3B23CAP203 Concepts of Operating SystemsPreview

Lecture 3.4B23CAP204 Mathematical Foundations for Computer ScienceIIPreview

Lecture 3.5B23BBAMDC204 Entrepreneurship & StartupsPreview

Lecture 3.6B23SEC207 Soft SkillsPreview

Lecture 3.7B23VAC201 Environmental StudiesPreview

Lecture 3.8B23AEC211 English Language and Communication Skills: Level 2Preview


Semester3 6/6

Lecture 4.1B23CAP301 Java OOP FoundationsPreview

Lecture 4.2B23CAP302 Linux and Shell ProgrammingPreview

Lecture 4.3B23CAP303 Data Base TechnologiesPreview

Lecture 4.4B23SEC310 Communication in Professional LifePreview

Lecture 4.5B23AEC311 English Language and Communication Skills: Level 3Preview

Lecture 4.6B23BBAMDC302 Fundamentals of InvestingPreview


Semester4 6/6
BCANEP Semester4 syllabus uploaded soon. This is the old syllabus of BCA.

Lecture 5.1BCA – 241 ADVANCED DATA STRUCTUREPreview

Lecture 5.2BCA – 242 ADVANCED PROGRAMMING USING C++Preview

Lecture 5.3BCA243 ECOMMERCEPreview

Lecture 5.4BCA – 244 RELATIONAL DATABASE MANAGEMENT SYSTEMPreview

Lecture 5.5BCA – 245 COMPUTERORIENTED STATISTICAL METHODSPreview

Lecture 5.6BCA – 246 MANAGEMENT INFORMATION SYSTEMPreview


Semester5 6/6
BCANEP Semester5 syllabus uploaded soon. This is the old syllabus of BCA.

Lecture 6.1BCA351: Web Designing FundamentalsPreview

Lecture 6.2BCA352: Operating SystemIPreview

Lecture 6.3BCA353: Artificial IntelligencePreview

Lecture 6.4BCA354: Computer NetworksPreview

Lecture 6.5BCA355: Programming Using Visual BasicPreview

Lecture 6.6BCA356: Multimedia ToolsPreview


Semester6 6/6
BCANEP Semester6 syllabus uploaded soon. This is the old syllabus of BCA.

Lecture 7.1BCA361: Web Designing Using Advanced ToolsPreview

Lecture 7.2BCA362: Operating SystemIIPreview

Lecture 7.3BCA363: Computer GraphicsPreview

Lecture 7.4BCA364: Internet TechnologiesPreview

Lecture 7.5BCA365: Advanced Programming with Visual BasicPreview

Lecture 7.6BCA366: Programming in Core JavaPreview

BCA – 245 COMPUTERORIENTED STATISTICAL METHODS
Maximum Marks: 100  External: 80 
Internal: 20  
Minimum Pass Marks: 35  
Time: 3 hours 
Note: Examiner will be required to set Nine Questions in all. First Question will be compulsory, consisting of objective type/shortanswer type questions covering the entire syllabus. In addition to that eight more questions will be set, two questions from each Unit. A candidate will be required to answer five questions in all, selecting one question from each unit in addition to compulsory Question No. 1. All questions will carry equal marks.
UNITI
Basic Statistics: Preparing Frequency Distribution Table and Cumulative frequency, Measure of Central Tendency, Types: Arithmetic mean, Geometric Mean, Harmonic Mean, Median, Mode.
Measure of Dispersion: Range, Quartile Deviation, mean deviation, Coefficient of mean Deviation, Standard Deviation
Moments : Moments About mean, Moments about any point, Moment about origin, Moment about mean in terms of moment about any point, Moment about any point in terms of Moment about mean.
UNITII
Probability Distribution: Random Variable Discrete Random and Continuous Random variable, Probability Distribution of a Random Variable, Mathematical Expectation
Types: Binomial, Poisson, Normal Distribution, Mean and Variance of Binomial, Poisson, and Normal Distribution.
Correlation: Introduction, Types, Properties, Methods of Correlation: Karl Pearson’s Coefficient of Correlation, Rank Correlation and Concurrent Deviation method, Probable error.
UNITIII
Regression: Introduction, Aim of Regression Analysis, Types of Regression Analysis, Lines of Regression, Properties of Regression Coefficient and Regression Lines, Comparison with Correlation.
Curve Fitting: Straight Line, Parabolic curve, Geometric Curve and Exponential Curve
Baye’s Theorem in Decision Making, Forecasting Techniques
UNITIV
Sample introduction, Sampling: Meaning, methods of Sampling, Statistical Inference: Test of Hypothesis, Types of hypothesis, Procedure of hypothesis Testing, Type I and Type II error, One Tailed and two tailed Test, Types of test of Significance: Test of significance for AttributeTest of No. of success and test of proportion of success, Test of significance for large samples – Test of significance for single mean and Difference of mean, Test of significance for small samplesttest) – test the significance between the mean of a random sample, between the mean of two independent samples
Chi square Test, ANOVA: Meaning, Assumptions, One way classification, ANOVA Table for OneWay Classified Data
REFERENCE BOOKS
 Gupta S.P. and Kapoor, V.K., Fundamentals of Applied statistics, Sultan Chand & Sons, 1996.
 Gupta S.P. and Kapoor, V.K., Fundamentals of Mathematical statistics, Sultan Chand and Sons, 1995.
 Graybill, Introduction to Statistics, McGraw.
Anderson, Statistical Modelling, McGraw.