ICS (Intermediate in Computer Science) Statistics (Part I) - Elective Syllabus

Statistics (Part I) - Elective syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Statistics (Part I) - Elective in ICS (Intermediate in Computer Science), not a summary of it.

1. 1

   Introduction to Statistics

   4 topics

   • Meaning and Scope of Statistics
   • Population and Sample
   • Variables and Data Types
   • Sources and Collection of Data
2. 2

   Presentation of Data

   3 topics

   • Classification and Tabulation
   • Frequency Distribution
   • Graphs and Charts
3. 3

   Measures of Central Tendency

   4 topics

   • Arithmetic Mean
   • Median and Mode
   • Geometric and Harmonic Mean
   • Quantiles
4. 4

   Measures of Dispersion

   4 topics

   • Range and Quartile Deviation
   • Mean Deviation
   • Variance and Standard Deviation
   • Coefficient of Variation
5. 5

   Index Numbers

   4 topics

   • Simple and Composite Index Numbers
   • Price and Quantity Index
   • Laspeyres and Paasche Indices
   • Consumer Price Index
6. 6

   Probability

   4 topics

   • Basic Concepts and Sample Space
   • Laws of Probability
   • Conditional Probability
   • Bayes' Theorem
7. 7

   Random Variables and Probability Distributions

   3 topics

   • Discrete and Continuous Random Variables
   • Expectation and Variance
   • Mathematical Expectation

Statistics (Part I) - Elective flashcards for ICS (Intermediate in Computer Science)

24 of 60 cards from the Statistics (Part I) - Elective deck — real questions with worked answers.

1. Define Statistics in the plural sense.

   In the plural sense, statistics means numerical facts or data collected systematically for a definite purpose, e.g., data on population, prices, or production.

2. Define Statistics in the singular sense.

   In the singular sense, statistics is the science (and methods) of collecting, organizing, presenting, analyzing, and interpreting numerical data to aid decision-making.

3. What are the two main branches of Statistics?

   Descriptive Statistics (collecting, organizing, summarizing and presenting data) and Inferential Statistics (drawing conclusions about a population from a sample).

4. What is descriptive statistics?

   The branch concerned with methods of collecting, organizing, summarizing, and presenting data (e.g., tables, graphs, averages) without drawing conclusions beyond the data.

5. What is inferential statistics?

   The branch concerned with making generalizations, estimates, predictions, or decisions about a population based on data obtained from a sample.

6. State two important limitations of Statistics.

   It studies only aggregates/groups (not individuals), and it deals only with quantitative (or quantifiable) data; results are true on average and can be misused.

7. Define a population (in statistics).

   A population is the complete set of all individuals, objects, or measurements of interest in a particular study.

8. Define a sample.

   A sample is a part or subset of the population, selected to represent it for study.

9. Differentiate between a parameter and a statistic.

   A parameter is a numerical measure describing a population (e.g., population mean μ); a statistic is a numerical measure describing a sample (e.g., sample mean x̄).

10. Distinguish between a finite and an infinite population.

    A finite population has a countable, fixed number of units (e.g., students in a college); an infinite population has unlimited or uncountable units (e.g., stars in the sky).

11. What is the difference between a census and a sample survey?

    A census collects data from every unit of the population; a sample survey collects data from only a representative part (sample) of the population.

12. Give two advantages of sampling over a complete census.

    Sampling saves time and money, and it allows quicker results; it is also feasible when the population is infinite or testing is destructive.

13. Define a variable.

    A variable is a characteristic or quantity that can take different values from one unit to another (e.g., height, weight, marks).

14. Define a constant.

    A constant is a quantity that keeps a fixed value throughout an investigation (e.g., π = 3.1416).

15. Distinguish between qualitative and quantitative variables.

    A qualitative variable describes a quality or attribute that cannot be measured numerically (e.g., gender, color); a quantitative variable can be measured and expressed numerically (e.g., age, income).

16. Distinguish between discrete and continuous variables.

    A discrete variable takes only whole/distinct values obtained by counting (e.g., number of children); a continuous variable can take any value within a range obtained by measuring (e.g., height, weight).

17. What is the difference between primary and secondary data?

    Primary data are collected first-hand by the investigator for a specific purpose; secondary data are already collected by someone else and used by another for a different purpose.

18. Name the main methods of collecting primary data.

    Direct personal interview, indirect interview, questionnaires sent by mail, enumerators (schedules), through local correspondents, and direct observation.

19. Name two important sources of secondary data.

    Published sources such as government reports, official publications (e.g., Statistical Year Book), newspapers, journals; and unpublished records of organizations.

20. What is the difference between a questionnaire and a schedule?

    A questionnaire is filled in by the respondents themselves; a schedule is filled in by trained enumerators who put the questions to respondents.

21. Define classification of data.

    Classification is the process of arranging data into groups or classes according to their common characteristics or resemblances.

22. Name the four bases (types) of classification of data.

    Qualitative, quantitative, geographical (spatial), and chronological (temporal) classification.

23. What is chronological classification?

    Classification of data according to time (e.g., production figures arranged year by year).

24. Define tabulation of data.

    Tabulation is the systematic arrangement of classified data into rows and columns of a table for clear presentation and comparison.

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