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UGC NET Statistics (107)

Prepare for UGC NET Statistics with the common Paper I foundation and 24 subject lessons: a study roadmap, 20 unit lessons and three practice lessons.

₹9,999 · full-course fee · 9 months access

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10-second subject-group introduction

UGC NET Statistics: Science, Computing and Environment introduction

Watch the Science, Computing and Environment section relevant to UGC NET Statistics. This short introduction is shared by the subjects in this group. Explore this programme’s own learning material below.

UGC NET Statistics (107)

One-time full-course fee for this subject programme

₹9,999

9 months course access

Review this course's own syllabus, fee and access period before enrolling. One purchase covers your selected subject programme with its included common Paper I foundation, not all subjects.

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Explore the learning material in UGC NET Statistics

Examples from this programme’s published subject lessons:

  • Probability, Conditional Probability, Bayes Theorem, Random Variables and Generating Functions
  • Real Analysis: Countability, Sequences and Series, Mean Value Theorems, and Maxima and Minima in Two Variables
  • Sampling Methods: Simple Random, Stratified and Systematic Sampling, Ratio and Regression Estimation, Cluster and Double Sampling
Read the video transcript

Explore computing, electronics, statistics and environmental subjects alongside forensic science, forestry and disaster management. Choose your field and review the program.

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Suggested study duration

10-14 weeks

LMS access

9 months course access

Delivery

Online LMS learning support

Payment availability

Check current checkout options

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Review the published learning format and access period before enrolling. Checkout shows current payment availability; a pending attempt is not confirmation of payment or course access.

Reading material available in the LMS

Check the published readings before you enrol. Full lesson text is available in the protected LMS through your eligible trial or course access.

View published modules and readings

34 published readings across 4 modules.

1. Start Here — Exam Pattern & Study Plan (1 readings)
  1. How this course works: exam pattern, syllabus map and study plan
2. Paper I — Teaching & Research Aptitude (10 readings)
  1. Paper I Unit 1 — Teaching Aptitude: Levels of Teaching, Learners, Methods and Evaluation Systems
  2. Paper I Unit 2 — Research Aptitude: Types, Approaches, Steps, Writing and Research Ethics
  3. Paper I Unit 3 — Comprehension: Reading a Passage for Main Idea, Inference, Tone and Vocabulary
  4. Paper I Unit 4 — Communication: Process, Types, Classroom Communication, Barriers and Mass Media
  5. Paper I Unit 5 — Mathematical Reasoning and Aptitude: Series, Codes, Relationships and Arithmetic
  6. Paper I Unit 6 — Logical Reasoning: Propositions, Syllogism, Fallacies and Indian Logic
  7. Paper I Unit 7 — Data Interpretation: Sources, Classification, Graphs and Data in Governance
  8. Paper I Unit 8 — Information and Communication Technology: Terminology, Internet, Digital Initiatives and E-Governance
  9. Paper I Unit 9 — People, Development and Environment: Sustainable Development, Pollution, Resources, Disasters and Environmental Agreements
  10. Paper I Unit 10 — Higher Education System: Ancient Institutions, Post-Independence Evolution, Programmes, Policies and Governance
3. Paper II — Unit-wise Notes (20 readings)
  1. Unit 1 — Probability, Conditional Probability, Bayes Theorem, Random Variables and Generating Functions
  2. Unit 1 — Standard Distributions, Joint and Sampling Distributions, Convergence, Laws of Large Numbers and the Central Limit Theorem
  3. Unit 2 — Real Analysis: Countability, Sequences and Series, Mean Value Theorems, and Maxima and Minima in Two Variables
  4. Unit 2 — Matrix Algebra: Vector Spaces, Rank, Characteristic Roots, the Cayley-Hamilton Theorem and Quadratic Forms
  5. Unit 3 — Sampling Methods: Simple Random, Stratified and Systematic Sampling, Ratio and Regression Estimation, Cluster and Double Sampling
  6. Unit 3 — Design of Experiments: Analysis of Variance, CRD, RBD, Latin Squares, Factorial Experiments, Confounding and BIBD
  7. Unit 4 — Point Estimation: Unbiasedness, Consistency, Sufficiency, Completeness, Rao-Blackwell, Lehmann-Scheffe and Maximum Likelihood
  8. Unit 4 — Confidence Intervals, Order Statistics and Rank Correlation: Pivots, Distribution-Free Intervals, Spearman and Kendall
  9. Unit 5 — Neyman-Pearson Lemma, Monotone Likelihood Ratio, UMP Tests, Likelihood Ratio Tests and Wald's SPRT
  10. Unit 5 — Chi-Square Tests and Nonparametric Tests: Sign, Wilcoxon Signed Rank, Mann-Whitney U and Kruskal-Wallis
  11. Unit 6 — Linear Estimation and Regression: Least Squares, the Gauss-Markov Theorem, R-squared and Tests on Regression Coefficients
  12. Unit 6 — Econometrics: Multicollinearity, Heteroscedasticity, Autocorrelation, Logistic Regression, Instrumental Variables and Two-Stage Least Squares
  13. Unit 7 — Stationary Time Series: Autocovariance and Autocorrelation, AR, MA and ARMA Processes, Invertibility and the Yule-Walker Equations
  14. Unit 7 — ARIMA Models, the Box-Jenkins Method, Forecasting, Spectral Density and Periodogram Analysis
  15. Unit 8 — The Multivariate Normal Distribution, the Wishart Distribution and Hotelling's T-squared for Mean Vectors
  16. Unit 8 — Discriminant Analysis, Principal Component Analysis and Canonical Correlation Analysis
  17. Unit 9 — Markov Chains: Transition Matrices, Chapman-Kolmogorov Equations, Classification of States and Stationary Distributions
  18. Unit 9 — Poisson Process, Birth and Death Processes, the M/M/1 Queue and the Simple Random Walk
  19. Unit 10 — The Indian Statistical System: MoSPI, the National Statistical Commission, NSO, Census and Surveys, and the Contributions of Mahalanobis, Sukhatme, Bose, Roy and Rao
  20. Unit 10 — R Software for Research: Vectors, Missing Data, Matrix Operations, Loops, Data Frames, Graphics and Writing Functions
4. Applied practice, case studies and revision (3 readings)
  1. Statistics: worked case studies and applied scenarios
  2. Statistics: common mistakes, misconceptions and self-check Q&A
  3. Statistics: revision sheet and timed mock with answer key

This index shows available reading material. It does not certify complete coverage of every university, board or examination syllabus.

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What you will study

Prepare for UGC NET Statistics with the common Paper I foundation and 24 subject lessons: a study roadmap, 20 unit lessons and three practice lessons.

  • Published LMS lessons
  • Course Tutor support
  • Guided practice and revision

Is this programme for you?

  • Check the programme's academic or examination eligibility with Admissions

Review eligibility, learning scope and the current examination requirements before committing. Academic and professional-examination support does not itself award the underlying degree or professional registration.

Admission and finance assistance

Inside this programme

How learning works in UGC NET Statistics (107)

Online LMS learning support. Study the material available for this programme in the student LMS. Features and assessments vary by course; check what is included before enrolling.

  1. 01

    Follow the course outline

    Start with the published modules for UGC NET Statistics (107). Read the lesson explanations and worked examples in sequence.

  2. 02

    Ask the Course Tutor

    Where available, ask for an explanation, comparison or revision of the lesson you are reading. The AI Course Tutor is an automated service, not a live faculty member, and can make mistakes.

  3. 03

    Use available learning tools

    Use the narration, visuals or videos provided in the course player. A programme introduction is not a promise of a video lecture for every lesson.

  4. 04

    Practise and revise

    Complete the published exercises and knowledge checks, review mistakes and revisit the relevant lessons. Confirm any live sessions, mocks or evaluated assignments on this programme’s own details.

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Admissions for this programme

Before you enrol in UGC NET Statistics (107)

Review the curriculum and eligibility above, explore the available learning experience, then confirm this programme’s fee and access period.

9 months course access

The one-time full-course fee is shown once, at the top of this page.

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Use this programme’s trial link below. Eligible access lasts 24 hours for one selected programme, with one trial per account. A parent or guardian should manage a school learner’s account.

What does the fee cover?

New Education admissions use a one-time full-course fee for the stated access period, not a monthly course subscription. Historical purchases retain their original terms. Finance or EMI assistance is separate and subject to lender approval; it is not guaranteed.

When is admission confirmed?

Resolve programme questions with Admissions, review the current checkout options and read the terms and refund policy. A payment attempt or pending payment does not confirm admission. Paid access requires verified payment and the applicable programme checks.

Does this award a degree or guarantee selection?

This is learning or examination-preparation support. The underlying degree, professional registration, eligibility and examination rules are governed by the relevant institution or examining authority. Selection, rank and passing are not guaranteed.

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Complete UGC NET course catalogue

All 87 subject programmes — courses & fees

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Course questions answered

What will I study in UGC NET Statistics (107)?

Prepare for UGC NET Statistics with the common Paper I foundation and 24 subject lessons: a study roadmap, 20 unit lessons and three practice lessons.

What is the full-course fee and how long does access last?

The one-time full-course fee is shown at the top of this page, with 9 months of course access. Review the current checkout and refund terms before paying. Access time is separate from any degree duration or examination schedule.

How is the course delivered, and can I try it first?

Online LMS learning support. An eligible 1-Day Free Trial provides 24-hour protected access to explore the available material. The Course Tutor is automated. Review the published reading index and course scope before enrolling.

Who should consider this programme?

Check the programme's academic or examination eligibility with Admissions Confirm current prerequisites with the relevant institution or examining authority. Learning support does not itself award a degree, professional registration, admission, employment or an examination result.

Check the terms and refund policy, or ask admissions about course fit.

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