The written examination for Assistant Director in the A.P. Economics and Statistical Service, mapped one syllabus line at a time. Each line is reproduced as the notification prescribes it, pointed at the page here that teaches it, and graded for depth — and where nothing here teaches it, the line says so.
Practise on past papers. Two of the Commission’s Assistant Statistical Officer Paper-II question papers are solved here, all 150 questions of each, with the answer the Commission marked, the working, and the page that teaches it: the paper of 29 April 2025 and the paper of 4 November 2022. They were set for the Assistant Statistical Officer, but their ten subject items are the ones this notification splits across Papers 2 and 3.
| Paper | Subject | No. of questions | Duration, minutes | Maximum marks |
|---|---|---|---|---|
| PAPER-1 | General Studies and Mental Ability (Degree standard) | 150 | 150 | 150 |
| PAPER-2 | Paper-2 (P. G. Standard) | 150 | 150 | 150 |
| PAPER-3 | Paper-3 (P. G. Standard) | 150 | 150 | 150 |
| Total | 450 | |||
Scheme of examination as set out in Annexure VII of G.O. Ms. No.201 Finance (HR-I, Plg & Policy) Dept., Dt.21/12/2017.
Negative marks. “As per G.O. Ms. No.235 Finance (HR-I, Plg & Policy) Dept., Dt.06/12/2016, for each wrong answer will be penalized with 1/3rd of the marks prescribed for the question.”
Brief Notification No. 09/2026, dated 15/09/2026Educational qualification. Must possess Post Graduate Degree in one of the Subjects of Mathematics, Pure Mathematics, Statistics, Economics, Applied Economics, Applied Statistics, Applied Mathematics, Econometrics or Computer Science from a recognized University or Institution recognized by the University Grants Commission or any other recognized equivalent qualification.
Brief Notification No. 09/2026, dated 15/09/2026“P. G. Standard” does not mean postgraduate statistics here. The notification labels Papers 2 and 3 P. G. standard, but the statistics Paper-3 lists is undergraduate: collection of data, central tendency, dispersion and skewness, correlation, time series and index numbers. There is no estimation, no testing of hypotheses, no inference of any kind. Every one of its 28 lines is answered by the Foundation courses on this site, and none of the Advanced courses is needed for it. Read that as good news about where to spend the months.
Nine of the ten items in this paper are general knowledge — current events, science, history, geography, polity, the economy, environment, disaster management and reasoning. This site does not teach them and is not going to; they are named here so the map is not read as covering them:
The tenth item is statistics, and it is taught here:
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Data analysis: tabulation of data, visual representation of data, basic data analysis (summary statistics such as mean, median, mode and variance) and interpretation | Descriptive Statistics Unit 2 — Measurement Scales & Data Presentation Descriptive Statistics Unit 3 — Measures of Central Tendency Descriptive Statistics Unit 4 — Measures of Dispersion | deep |
PAPER-2 · 8 lines: 5 taught in depth, 3 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Concepts of production, consumption and demand; concept of elasticity | Applied Statistics II Unit 3 — Demand Analysis | brief |
| Market structures and equilibrium; price determination | Price Determination, Market Structures and Factor Incomes — Economics (Unit 1) | deep |
| National income: concepts and determinants — employment, consumption, savings and investment | National Income and the National Accounts — Economics (Unit 2) | deep |
| Rate of interest and profit | Price Determination, Market Structures and Factor Incomes — Economics (Unit 1) | brief |
| Concepts of money and measures of money supply, velocity | Money, Banking and Credit Creation — Economics (Unit 3) | deep |
| Banks and credit creation; banks and portfolio management; central bank and control over supply of money | Money, Banking and Credit Creation — Economics (Unit 3) | deep |
| Determination of price level; inflation — meaning, measurement and control | Applied Statistics Unit 3 — Index Numbers | brief |
| Public finance: budgets, taxes and non-tax revenues, budget deficits | Public Finance, Budgets and Deficits — Economics (Unit 4) | deep |
PAPER-2 · 4 lines: 2 taught in depth, 2 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Free trade and protection | International Economics: Trade, Balance of Payments and the Institutions — Economics (Unit 5) | deep |
| Balance of payments accounts and adjustment; exchange rate under the exchange markets | International Economics: Trade, Balance of Payments and the Institutions — Economics (Unit 5) | deep |
| International Monetary System and World Trading order — Brettonwoods system. IMF and the World Bank and their associates | International Economics: Trade, Balance of Payments and the Institutions — Economics (Unit 5) | brief |
| Sources of growth — capital, human capital, productivity, trade and aid, non-economic factors | International Economics: Trade, Balance of Payments and the Institutions — Economics (Unit 5) | brief |
PAPER-2 · 7 lines: 3 taught in depth, 4 at exam level, 0 not here yet.
PAPER-2 · 6 lines: 6 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Introduction to accounting; accounting concepts and conventions | What Accounting Is: Concepts, Conventions and the Rules of Debit and Credit — Financial Accounting (Unit 1) | deep |
| Accounting process — journalizing, posting to ledger accounts | Journal and Ledger: the Accounting Process Worked End to End — Financial Accounting (Unit 2) | deep |
| Subsidiary books including cash book | Subsidiary Books and the Cash Book — Financial Accounting (Unit 3) | deep |
| Bank reconciliation statement | Bank Reconciliation Statement — Financial Accounting (Unit 4) | deep |
| Preparation of trial balance and final accounts; errors and rectification | Trial Balance, Errors and Final Accounts — Financial Accounting (Unit 5) | deep |
| Depreciation and reserves; single entry and non-trading concerns | Depreciation, Reserves, Single Entry and Non-Trading Concerns — Financial Accounting (Unit 6) | deep |
PAPER-2 · 4 lines: 4 taught in depth, 0 at exam level, 0 not here yet.
PAPER-3 · 6 lines: 6 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Collection of data: primary and secondary data | Descriptive Statistics Unit 1 — Statistical Description of Data | deep |
| Methods of sampling (random, non-random) | Sampling Techniques Unit 1 — Sample Survey Concepts Sampling Techniques Unit 2 — Simple Random Sampling | deep |
| Definition of probability | Theory of Probability Unit 1 — Elementary Probability | deep |
| Census; schedule and questionnaire | Descriptive Statistics Unit 1 — Statistical Description of Data Sampling Techniques Unit 1 — Sample Survey Concepts | deep |
| Frequency distribution; tabulation | Descriptive Statistics Unit 1 — Statistical Description of Data Descriptive Statistics Unit 2 — Measurement Scales & Data Presentation | deep |
| Diagrammatic and graphic presentation of data | Descriptive Statistics Unit 2 — Measurement Scales & Data Presentation | deep |
PAPER-3 · 5 lines: 5 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Meaning, objectives and characteristics of measures of central tendency | Descriptive Statistics Unit 3 — Measures of Central Tendency | deep |
| Arithmetic mean, geometric mean, harmonic mean | Descriptive Statistics Unit 3 — Measures of Central Tendency | deep |
| Median and mode | Descriptive Statistics Unit 3 — Measures of Central Tendency | deep |
| Quartiles, deciles, percentiles | Descriptive Statistics Unit 3 — Measures of Central Tendency | deep |
| Properties of averages and their applications | Descriptive Statistics Unit 3 — Measures of Central Tendency | deep |
PAPER-3 · 5 lines: 5 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Dispersion: meaning and properties | Descriptive Statistics Unit 4 — Measures of Dispersion | deep |
| Range, quartile deviation, mean deviation, standard deviation, coefficient of variation | Descriptive Statistics Unit 4 — Measures of Dispersion | deep |
| Skewness: Meaning — Karl Pearson and Bowley's measures of skewness | Descriptive Statistics Unit 5 — Moments, Skewness & Kurtosis | deep |
| Concept of kurtosis | Descriptive Statistics Unit 5 — Moments, Skewness & Kurtosis | deep |
| Normal distribution | Continuous Distributions Unit 4 — Normal Distribution | deep |
Two spellings corrected. Both notifications print “Coefficient of Veriation” and “Karl Pearson and Bowl’s measures of skewness”. The lines above print variation and Bowley’s, because reproducing the first would read as this site’s own typo and the second would send you looking up the wrong statistician. Every other line on this page is the notification’s own wording, with … marking where a long line has been shortened.
PAPER-3 · 4 lines: 4 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Correlation: meaning, uses and types of correlation | Statistical Methods Unit 2 — Correlation | deep |
| Karl Pearson's correlation coefficient | Statistical Methods Unit 2 — Correlation | deep |
| Spearman's rank correlation | Statistical Methods Unit 2 — Correlation | deep |
| Probable error | Statistical Methods Unit 3 — Concurrent Deviation, Multiple & Partial Correlation | deep |
PAPER-3 · 8 lines: 8 taught in depth, 0 at exam level, 0 not here yet.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Time series analysis: meaning and uses; components of time series | Applied Statistics Unit 1 — Time Series | deep |
| Measurement of trend and seasonal variations | Applied Statistics Unit 1 — Time Series Applied Statistics Unit 2 — Seasonal Component | deep |
| Utility of decomposition of time series; decentralization of data | Applied Statistics Unit 2 — Seasonal Component | deep |
| Index numbers: meaning and importance | Applied Statistics Unit 3 — Index Numbers | deep |
| Methods of construction of index numbers: price index numbers, quantity index numbers | Applied Statistics Unit 3 — Index Numbers | deep |
| Tests of adequacy of index numbers | Applied Statistics Unit 3 — Index Numbers | deep |
| Base shifting and deflation of index numbers | Applied Statistics II Unit 2 — Index Numbers (Advanced) | deep |
| Cost of living index numbers; limitations of index numbers | Applied Statistics Unit 3 — Index Numbers Applied Statistics II Unit 2 — Index Numbers (Advanced) | deep |
Proficiency in Office Automation with usage of Computers and Associated Software — practical, 60 minutes, 100 marks, with minimum qualifying marks of 30 (SC/ST/PBD), 35 (B.C.’s) and 40 (O.C.’s).
Scheme prescribed by G.O.Ms.No.26, G.A. (Ser.B) Dept., dt: 24.02.2023, reproduced in Brief Notification No. 09/2026, dated 15/09/2026A qualifying practical test, and the best-covered paper of the three: the data-science section of this site teaches almost all of it.
8 lines: 1 deep, 7 brief, 0 not here.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| Introduction to Computers — Components and their classification — Peripheral devices and their purpose. Input Devices — Keyboard, Mouse, Scanner … Output Devices: Display devices, Printers, Monitor, Speaker, Plotter, Secondary Storage Devices … Random-Access Memory (RAM) — Read-Only Memory (ROM) — Control Unit — Memory Unit — Arithmetic Logic Unit (ALU) | Data Science Computer Fundamentals and Office Automation Unit 1 — Number Systems, Evolution, Block Diagram and Generations | deep |
| System Software, Application Software, Embedded software, Proprietary Software, Open source software (their purpose and characteristics only) | Data Science Problem Solving Using C Unit 1 — Introduction to Computer Programming | brief |
| Purpose of operating system, Single User and Multi User Operating Systems with Examples | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
| Interfacing Graphical User Interface (GUI), Differences between Character User Interface (CUI) and Graphical User Interface (GUI) — working With Files and Folders … Running An Application Through the File Manager … Setting up of Printer, Webcam, Scanner and other peripheral devices | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
| Introduction to Linux — Features and advantages of Linux, File handling commands, directory handling commands — User Management — File permissions … Macintosh Apple Computer (MAC) OS … Basics commands | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
| Minimum Hardware and Software Requirements for a system to use internet, Communication Protocols and Facilities — Various browsers — What is Internet Protocol (IP) Address — Steps required in connecting system to network — Uploading and Downloading Files from Internet | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
| Sending and receiving mails, Basic E-Mail Functions, Using your word processor for E-mail, Finding E-Mail Address, Mailing Lists and lists Servers | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
| WWW advantages of the Web — how to navigate with the Web — Web Searching | Data Science Computer Fundamentals and Office Automation Unit 2 — Basic Organization and Networking Fundamentals | brief |
7 lines: 3 deep, 4 brief, 0 not here.
| Syllabus line, as prescribed | Where it is taught here | Depth |
|---|---|---|
| MSOFFICE or any open source office like Libre Office / Apache Open Office / Neo office for Windows/Linux/Macintosh Apple Computer (MAC) OS | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | brief |
| Introduction to Office Software — Starting and Exiting the Office Applications — Introducing the Office Shortcut Bar — Customizing Office Shortcut Bar | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | brief |
| Common Office Tools and Techniques — Opening An Application — Creating Files — Entering And Editing Text — Saving Files … Managing Your files With the Office Applications | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | brief |
| Key Combinations — Cut, Copy and Paste — Drag And Drop Editing — Menu Bars And Toolbars — Undo and Redo — Spell Checking — Auto Correct — Find and Replace — Help And The Office Assistants — Templates and Wizards | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | brief |
| Starting Word … Designing Your Document — Typing Text … Formatting text and document … Saving Document — Page Setup … Printing … Page Break — Header and Footer … Table and Sorting — Working With Graphics … Word Art … Mail Merge | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | deep |
| Features Of Excel — Excel worksheet — Selecting Cell … Entering And Editing Formulas — Referencing Cells … Excel Functions … Saving A Worksheet — Printing A Worksheet … Function Wizard … Organizing Your Data — Excel's Chart Features … Creating Trend Lines … Sorting Excel Data — Adding Subtotals To Databases … Comma Separated Value (CSV) File format — Using Worksheet As Databases | Data Science Computer Fundamentals and Office Automation Unit 4 — Spreadsheet Basics MS-Excel Unit 1 — Excel Basics for Data Analysis MS-Excel Unit 2 — Data Visualization & Frequency Analysis Data Science Computer Fundamentals and Office Automation Unit 5 — Data Analysis and Visualization | deep |
| Introduction — Starting Presentation Software — Views in Presentation Software — Slides … Color Schemes — Formatting Slides — Creating a Presentation … Using a Template … Working with Text in Power Point … Inserting A Picture — Working With Graphics … Assigning Transitions And Timings — Setting The Master Slide — Setting Up The Slide Show — Running The Slide Show | Data Science Computer Fundamentals and Office Automation Unit 3 — Word Processing and Presentations | deep |
No gaps in Assistant Director. Every line above points at a page on this site.