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Tribhuvan university CSIT 2065 Syllabus Statistics I

Statistics I - 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 Statistics I course () within the distinguished Tribhuvan university's CSIT department. Aligned with the 2065 Syllabus, this course (STA-108) 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 Applied Statistical Techniques and its Applications
Goal:This course makes students able to understand Applied Statistical Techniques and their applications in the allied areas.

Units

Key Topics

  • Sampling Distribution
    SA-1

    The distribution of a statistic obtained from multiple samples of a population. It is a fundamental concept in inferential statistics.

  • Sampling Distribution of Mean and Proportion
    SA-2

    The distribution of the sample mean and proportion, which are used to make inferences about the population mean and proportion.

  • Central Limit Theorem
    SA-3

    A fundamental theorem in statistics that states that the sampling distribution of the mean will be approximately normal, even if the population distribution is not normal.

  • Concept of Inferential Statistics
    SA-4

    The branch of statistics that deals with making inferences about a population based on a sample of data.

  • Estimation
    SA-5

    The process of making an educated guess about a population parameter based on a sample of data.

  • Methods of Estimation
    SA-6

    Different techniques used to estimate population parameters, such as maximum likelihood estimation and method of moments.

  • Properties of Good Estimator
    SA-7

    The characteristics of a good estimator, including unbiasedness, consistency, and efficiency.

Key Topics

  • Chi-Square Test
    NO-1

    The Chi-Square test is a statistical test used to determine whether there is a significant association between two categorical variables. It is used to test the independence of two variables or to test whether the observed frequencies of a categorical variable match the expected frequencies.

  • Order Statistics
    NO-2

    Order statistics is a branch of statistics that deals with the arrangement of data in order of magnitude. It is used to describe the distribution of data and to make inferences about the population.

  • Run Test
    NO-3

    The Run test is a non-parametric test used to determine whether a sequence of data is random or not. It is used to test for randomness in a sequence of binary data.

  • Sign Test
    NO-4

    The Sign test is a non-parametric test used to compare the median of two related samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

  • Wilcoxon Matched Pairs Signed Ranks Test
    NO-5

    The Wilcoxon Matched Pairs Signed Ranks test is a non-parametric test used to compare the median of two related samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

  • Mann-Whitney U Test
    NO-6

    The Mann-Whitney U test is a non-parametric test used to compare the median of two independent samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

  • Median Test
    NO-7

    The Median test is a non-parametric test used to compare the median of two or more samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

  • Kolmogorov Smirnov Test (One Sample Case)
    NO-8

    The Kolmogorov Smirnov test is a non-parametric test used to compare the distribution of a sample to a known distribution. It is used to test whether the distribution of a sample is significantly different from a known distribution.

  • Cochran Q Test
    NO-9

    The Cochran Q test is a non-parametric test used to compare the proportion of successes in multiple related samples. It is used to test whether the proportion of successes in one sample is significantly different from the proportion of successes in another sample.

  • Kruskal Wallis One way ANOVA Test
    NO-10

    The Kruskal Wallis one-way ANOVA test is a non-parametric test used to compare the median of three or more independent samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

  • Friedman Two way ANOVA Test
    NO-11

    The Friedman two-way ANOVA test is a non-parametric test used to compare the median of three or more related samples. It is used to test whether the median of one sample is significantly different from the median of another sample.

Key Topics

  • Nature of Internship
    CO-1

    The internship work should be relevant to the field of computer science and information technology, with a minimum duration of 180 hours or ten weeks.

  • Phases of Internship
    CO-2

    The internship evaluation consists of three phases: Proposal Submission, Mid-Term Submission, and Final Submission.

  • Provision of Supervision
    CO-3

    A regular faculty member of the college is assigned as a supervisor to supervise the students throughout the internship period.

  • Provision of Mentorship
    CO-4

    A regular employee of the intern providing organization is assigned as a mentor to guide the students throughout the internship period.

  • Evaluation Scheme
    CO-5

    The evaluation scheme consists of Proposal Defense, Midterm, and Final Defense, with a total of 200 marks.

  • Report Contents
    CO-6

    The internship report should contain prescribed content flow, including introduction, problem statement, objectives, and references.

  • Citation and Referencing
    CO-7

    The citation and referencing standard should be APA referencing standard, with proper citation and referencing in the document.

  • Report Format Standards
    CO-8

    The report format standards include page number, page size and margin, paragraph style, text font, section headings, figures and tables.

  • Final Report Binding and Submission
    CO-9

    The final report should be submitted in three copies, with a golden embracing and black binding, to the Dean Office, Exam Section, Institute of Science and Technology, Tribhuvan University.