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Tribhuvan university CSIT 2065 Syllabus Probability and Statistics

Probability and Statistics - Syllabus

Course Overview and Structure
Syllabus Notes Old Questions Unit Wise Questions Question Bank

Embark on a profound academic exploration as you delve into the Probability and Statistics course () within the distinguished Tribhuvan university's CSIT department. Aligned with the 2065 Syllabus, this course (STA-103) seamlessly merges theoretical frameworks with practical sessions, ensuring a comprehensive understanding of the subject. Rigorous assessment based on a 60+20+20 marks system, coupled with a challenging passing threshold of , propels students to strive for excellence, fostering a deeper grasp of the course content.

This 3 credit-hour journey unfolds as a holistic learning experience, bridging theory and application. Beyond theoretical comprehension, students actively engage in practical sessions, acquiring valuable skills for real-world scenarios. Immerse yourself in this well-structured course, where each element, from the course description to interactive sessions, is meticulously crafted to shape a well-rounded and insightful academic experience.


Course Synopsis:    Concept of descriptive statistics, probability, probability distributions, inferential statistics and their applications.
Goal:  This course enhances the ability of students in computing and understanding summary statistics; understanding the concept of probability and probability distributions with their applications in statistics. Finally, students will develop their ability of using inferential statistics in decision-making processes.

Units

Key Topics

  • Introduction to E-commerce
    IN-1

    Overview of E-commerce and its significance in the digital age.

  • E-business vs E-commerce
    IN-2

    Understanding the differences between E-business and E-commerce.

  • Features of E-commerce
    IN-3

    Key characteristics and benefits of E-commerce.

Key Topics

  • Designing Databases
    DE-1

    This topic covers the fundamentals of designing databases, including the relational database model, normalization, and transforming E-R diagrams into relations.

  • Designing Forms and Reports
    DE-2

    This topic focuses on designing forms and reports, including formatting and assessing usability to create effective user interfaces.

  • Designing Interfaces and Dialogues
    DE-3

    This topic explores the design of interfaces and dialogues, including interaction methods and devices, and designing interfaces and dialogues in graphical environments.

  • Implementation Issues
    DE-4

    Addressing common challenges and considerations that arise during the implementation phase of software development.

  • Open-Source Development
    DE-5

    Exploring the principles, benefits, and best practices of open-source software development.

Key Topics

  • Project Management Techniques
    PR-1

    This topic covers various project management techniques used to plan, organize, and control projects. It includes developing project management plans and implementing, monitoring, and controlling projects.

  • Collaborative Development Environment
    PR-2

    This topic focuses on creating an environment that fosters collaboration and teamwork. It includes communications planning, organizing and conducting effective meetings, and other collaborative development strategies.

  • Inter Process Communication
    PR-3

    Methods of communication between processes, including race conditions and critical sections.

  • Implementing Mutual Exclusion
    PR-4

    Techniques for achieving mutual exclusion, including busy waiting, sleep and wakeup, semaphores, monitors, and message passing.

  • Classical IPC Problems
    PR-5

    Solutions to classic inter-process communication problems, including producer-consumer, sleeping barber, and dining philosopher problems.

  • Process Scheduling
    PR-6

    Goals and techniques for scheduling processes, including batch, interactive, and real-time systems.

Random Variables: Discrete and continuous random Variables; Probability distribution of random variables; Expected value of discrete & continuous random Variable.


Joint Probability Distribution of two random variables: Joint probability mass functions and density functions; Marginal probability mass and density functions; Mean, variance, covariance and correlation of random variables; Independent random variables; Illustrative numerical problems.

Bernoulli and binomial random variable and their distributions and moments; Computing binomial probabilities; Fitting of binomial distribution; Poisson random variable and its distribution and moments; Computing Poisson probabilities; Fitting of Poisson distribution.

Normal distribution and its moments; Standardization of normally distributed random variable; Measurement of areas under the normal curve; Negative exponential distribution and its moments; Concept of hazard rate function.

Characteristics function of normal random variable; Distribution of sum and mean of n independent normal random variables; Canonical definitions of chi-square, t and F random variables and their distributions; Joint distribution of and S2 in case of normal distribution.

Simple random sampling method and random sample; Sampling distribution and standard error; Distinction between descriptive and inferential statistics; General concept of point and interval estimation; Criteria for good estimator; Maximum likelihood method of estimation; Estimation of mean and variance in normal distribution; Estimation of proportion in binomial distribution; Confidential interval of mean in normal distribution; Concept of hypothesis testing; Level of significance and power of a test; Tests concerning the mean of a normal distribution case – when variance is known (Z-test) and unknown (t-test)

Simple Correlation: Scatter diagram; Karl Pearson's correlation coefficient and its properties, Simple Linear Regression: Model and assumptions of simple linear regression; Least square estimators of regression coefficients;Tests of significance of regression coefficients; Coefficient of determination.