UKPSC ASO Syllabus 2025 PDF Download & Exam Pattern

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UKPSC ASO Syllabus 2025 PDF Download & Exam Pattern: The Uttarakhand Public Service Commission (UKPSC) has released the UKPSC ASO Exam Syllabus 2025 for preparation of the exam. This syllabus is very important for the candidates who are applying for the Investigator cum Computer and Assistant Statistical Officer position. The Job Location is said to be Uttarakhand.

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UKPSC ASO Syllabus 2025

So, with no late download, the Syllabus is given on this page. Not only, the UKPSC ASO Syllabus 2025, but the syllabus topics are also given for all the  Assistant Statistical Officer. Therefore practice well for the Examination using the UKPSC ASO Exam Pattern 2025. Find out complete details from this page Moreover, prepare a schedule using the data provided on this page.

UKPSC ASO Syllabus 2025 – Overview

UKPSC ASO Exam Pattern 2025

It is strongly recommended that all candidates obtain precise and pertinent details concerning the UKPSC ASO Syllabus 2025 Download Link, as this pattern holds significant importance for applicants in preparing for the upcoming examination.

Written Exam

• The question paper will have 2 sections of 200 and 300 marks each respectively.
• The questions asked will be objective type.
• For each wrong answer, 0.25 marks of the marks assigned to that question will be deducted.

Computer Based test

This is the second hiring phase in UKPSC Investigator/Computer vacancy. Those who had cleared the written examination will be allowed to appear in this round. It will be an exam of 100 marks qualifying in nature. A candidate has to secure a minimum of 40 marks to qualify this exam. Each applicant taking this exam in the form of multiple-choice questions has to choose the right answer from the given list of options. Each question will carry a score of 20 marks.

UKPSC ASO Exam Syllabus 2025

Hindi

• Grammar
• Vocabulary
• Comprehension
• Fill in the blanks
• Error Detection
• Antonyms
• Synonyms
• Phrases/Muhavre

Techniques of statistical analysis

• Overview: Statistics Definition, Scope, Functions, Limitations, Distrust & Misuse.
• Collection of Data: Primary Data, Secondary Data, Elementary Idea of Sampling Techniques, Classification. Tabulation & Frequency Distribution; Presentation of Data: Graphical and Diagrammatic.
• Measures of Central tendency: Arithmetic Mean, Geometric Mean, Harmonic Mean, Median & Mode. Quartiles, Deciles and Percentiles.
• Measures of Dispersions: Range, Quartile Deviation, Mean Deviation, Standard Deviation, Coefficient of Variation, Moments, Skewness, Kurtosis and their measures.
• Index Number: Meaning, Importance, Laspeyre, Paasche’s, Marshall and Fisher Ideal Index numbers. Construction of Index Numbers and their Calculation, Cost of living Index number. Change of Base, Splicing, Deflating.

Simple Correlation: Linear & Rank, Simple Regression Analysis.

• Fundamentals of Mathematics: Elementary Set Theory; Number System, Elementary, Algebra, Coordinate Geometry; Straight Lines; Rates Ratios, Percentage &

Logarithms, Permutations and Combinations, Elementary Probability Theory, Additive and Multiplicative Theorems, of Probability Conditional Probability.

Mathematics/Industrial

Mathematics/Applied Mathematics

• ABSTRACT ALGEBRA:
  • Theory of Equations:
  • Groups and Rings
• LINEAR ALGEBRA
  • Vector Spaces
  • Linear transformations
  • Inner Product Spaces

• NUMERICAL ANALYSIS
  • Errors
  • Solution of equations
  • Interpolation
  • Numerical differentiation and Integration
  • Solution of ODE

• CALCULUS

• ANALYTICAL GEOMETRY
• DIFFERENTIAL EQUATIONS
• COMPLEX ANALYSIS
  • MECHANICS
  • Statics
  • Dynamics
• MATHEMATICAL ANALYSIS
  • Structure of point Sets
  • Convergence of real sequences
  • Infinite Series
  • Riemann Integral

Statistics/Mathematical Statistics/ Applied

• Descriptive Statistics: Primary and secondary data, classification and presentation of data, diagrammatic and graphical representation of data; Frequency distribution, Measures of location and dispersion, skewness and kurtosis. Bivariate data
• Probability and Distribution Theory: Classical, statistical and axiomatic definitions of probability. Additive and Multiplicative laws of probability, Conditional probability, Bayes’ theorem and its applications

• Inference Estimation:Concept of estimation, Properties of good estimator; Estimation by methods of maximum likelihood and moments, Optimal properties of maximum likelihood estimators; Minimum variance unbiased estimators. Minimum variance bound; Cramer-Rao inequality. Errors
• Analysis of Variance and Design of Experiments: Analysis of variance for one way and two way classifications; Fixed, mixed and random effect models; Basic principles of experimental design-randomization, replication and local control
• Sampling Theory and Official Statistics: Concept of population and sample, Complete enumeration versus sampling; sampling and non-sampling errors, Types of sampling: Purposive and random sampling, simple random sampling with and without replacement
• Applied statistics Quality Control:Process control and product control: control limits, charts for attributes p chart, np chart, c-chart, charts for variables: (𝑋ത,R), (𝑋ത,σ) charts
• Demography and Vital Statistics: Complete life table and its main features, Uses of life table. Abridged life tables. Stable and stationary populations. Measurement of Fertility

Economics/ Applied Economics/ Business

Economics/ Econometrics

• Micro Economics: Concept of Micro and Macro economics; Economic Static and Economic Dynamics; Nature of Economics: Normative and Positive; Consumer’s Behaviour and Equilibrium, Meaning of Demand, Law of Demand and Utility Analysis
• Macro Economics: National Income: Meaning, Concepts, Measurement and Limitations; Circular Flow of National Income; Methods of National Income Accounting; National Income and Employment: Classical, Keynesian and NeoClassical theories
• Economic Growth and Development: Meaning; Difference between Growth and Development; Measurement of Development: Human Development Index (HDI), Gender Development Index (GDI), Gender Inequality Index (GII), MultiDimensional Poverty Index (MPI)
• Money, Banking and Public Finance: Meaning, Concepts and Functions of Money; Measures of Money Supply; Theories of Money: Fisher, Cambridge, Keynesian, Milton Friedman; Functions of Central Bank; Credit Control
• Public Finance: Public Expenditure: Theories, Classification and Effects; Taxation: Principles of Taxation, Classification of Taxes, Incidence, Impact and Shifting of Taxes, Theories of Tax Shifting, Taxable Capacity;
• Demography: Theory of Demographic Transition; Malthusian Theory; Fertility: Concepts, Measurement and Factors; Mortality; Population Pyramid; Demographic Dividend; Population Growth rate
• Indian Economy: Sectoral Distribution of National Income; Trends in Population Growth and Demographic Changes; Poverty in India:- Measurement, Nature and Poverty Alleviation Programmes; Unemployment : Nature, Problems and Remedies; Page 45 of 72 Inequality in India; Recent Social Security measures; Economic Planning in India

Commerce

• Financial and Management Accounting: Accounting Concepts and Conventions, Accounting Standards, Capital & Revenue, Methods of Charging Depreciation, Financial Statements-Trading Account, Manufacturing Account, Profit and Loss Account, Balance Sheet
• Banking and Financial Institutions: Central banking in India, Methods of Credit Control by RBI, Commercial Banks, Banking Sector Reforms in India, NPA, Capital Adequacy Norms, Latest trends in E-Banking, Digital Currency, Payment Banks and UPI Payments.
• Business Management and Communication: Functions of Management- Planning, Organising, Staffing, Directing and Controlling, Decision Making Process, Theories of Motivation, Leadership Styles, Theories of Leadership, Management by Objectives, Management by Exception.
• Marketing Management: Marketing- Concept, Direct Marketing, Ps of Marketing, Market Segmentation,

Product Life Cycle, Branding and Advertisement, SWOT Analysis

• Auditing Standards of Auditing, Internal Control, Audit Sampling and Test Checking, Routine Checking, Vouchers and Vouching, Internal Check and Internal Audit, Verification and Valuation of Assets & Liabilities

Data Science

• Introduction to Data Science: Data Science, types of data, skill required for data science, personnel involved with data science, Data Science Process (DSP), Big data vs. Data Science, Big Data Analytics in Vertical Industry,
• Exploratory Data Analysis: Primary and secondary data, classification and presentation of data, diagrammatic and graphical representation of data
• Data Mining Data preprocessing: Introduction to data pre-processing, data cleaning, data integration, data reduction, data transformation and data discretionary. Data warehouse: Basic concepts, data warehouse modelling: data cube and OLAP
• Data Visualization: Purpose, scope, communication style, quantitative relationships, differing roles of tables and graphs. Exploring the visual data spectrum: charting primitives (data points, line charts, bar charts, pie charts, area charts), exploring advanced visualizations (candlestick charts, bubble charts, surface charts, map charts, infographics).
• Clustering: Introduction to clustering, mixture densities, k-means clustering, supervised learning after clustering, hierarchical clustering, choosing the number of clusters.
• Machine Learning: Introduction to machine learning, types of machine learning, Nearest neighbour methods, Validation: Nearest neighbour prediction, k-nearest neighbour methods, weighted neighbour methods, Curse of dimensionality.

Basic Knowledge of Computer

• Fundamentals of Computer
  • CPU
  • Memory
  • Hard Disk
  • Input/output Devices
  • Knowledge of Number System
• Basic Concept of Computer (Hardware & Software)
  • Computer Software
  • Operating System
  • Computer language
• Basic knowledge of MS Office
  • MS Word
  • MS Excel
  • MS PowerPoint
• Basic knowledge of Internet
  • Web browser
  • Email
  • Search Engines
  • Web Servers
• Basic Knowledge of Computer network
  • LAN
  • WAN
  • MODEM
• Basic Knowledge of cyber security
  • Virus, Malware, etc.
  • Warm
  • Internet Security
  • Network security
  • Firewall

UKPSC ASO Syllabus 2025 Download Link

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