NTS NAT-IGS Statistics Syllabus

Statistics syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Statistics in NTS NAT-IGS, not a summary of it.

1. 1

   Introduction to Statistics

   3 topics

   • Nature and Scope of Statistics
   • Population and Sample
   • Types of Data and Variables
2. 2

   Presentation of Data

   3 topics

   • Frequency Distributions
   • Tabulation and Classification
   • Graphs and Diagrams
3. 3

   Measures of Central Tendency

   3 topics

   • Mean, Median and Mode
   • Geometric and Harmonic Mean
   • Quartiles, Deciles and Percentiles
4. 4

   Measures of Dispersion

   4 topics

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

   Probability

   4 topics

   • Basic Concepts of Probability
   • Addition and Multiplication Rules
   • Conditional Probability
   • Probability Distributions
6. 6

   Index Numbers and Correlation

   3 topics

   • Index Numbers
   • Correlation
   • Regression Basics

Statistics flashcards for NTS NAT-IGS

24 of 59 cards from the Statistics deck — real questions with worked answers.

1. What is Statistics as a subject of study?

   Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to aid in making effective decisions under uncertainty.

2. What is the difference between Descriptive and Inferential Statistics?

   Descriptive statistics summarizes and describes data (e.g., averages, charts), while inferential statistics uses sample data to draw conclusions or make predictions about a population.

3. In statistics, what is meant by the word 'statistics' (plural sense) versus 'statistic'?

   Statistics (plural) refers to numerical data/facts collected systematically; a 'statistic' is a numerical measure computed from sample data (e.g., sample mean).

4. Define 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).

5. What is a population in statistics?

   A population is the entire collection of all individuals, items, or measurements about which information is desired in a study.

6. What is a sample in statistics?

   A sample is a subset or representative part of a population selected for study to draw conclusions about the whole population.

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

   A census collects data from every member of the population, whereas a sample survey collects data from only a selected portion (sample) of the population.

8. What is the difference between a finite and an infinite population?

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

9. What is qualitative data?

   Qualitative (categorical) data describes attributes or qualities that cannot be measured numerically, such as gender, color, or religion.

10. What is quantitative data?

    Quantitative data is numerical data that can be measured or counted, such as height, weight, age, or income.

11. What is the difference between discrete and continuous variables?

    A discrete variable takes only distinct, countable values (e.g., number of children), while a continuous variable can take any value within a range (e.g., height, weight).

12. What are the four scales (levels) of measurement?

    Nominal, Ordinal, Interval, and Ratio scales.

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

    Primary data is original data collected first-hand by the investigator, while secondary data is already collected by someone else and reused.

14. What distinguishes a nominal scale from an ordinal scale?

    A nominal scale only classifies data into categories with no order (e.g., gender), while an ordinal scale ranks categories in a meaningful order (e.g., grades A, B, C).

15. What is the key difference between interval and ratio scales?

    Both have ordered, equal intervals, but a ratio scale has a true (absolute) zero allowing meaningful ratios (e.g., weight), while an interval scale has an arbitrary zero (e.g., temperature in °C).

16. What is a frequency distribution?

    A frequency distribution is a tabular arrangement of data showing the number of observations (frequency) falling into each class or category.

17. What is class frequency?

    Class frequency is the number of observations that fall within a particular class or interval.

18. What are class limits and class boundaries?

    Class limits are the smallest and largest values that can belong to a class; class boundaries are the precise points separating adjacent classes, found by averaging the upper limit of one class and the lower limit of the next.

19. How is the class mark (midpoint) of a class calculated?

    Class mark = (Lower class limit + Upper class limit) / 2.

20. How is the class interval (width) calculated?

    Class width = Upper class boundary − Lower class boundary (or the difference between successive lower class limits).

21. What is a relative frequency?

    Relative frequency is the ratio of a class frequency to the total number of observations, often expressed as a fraction or percentage: f / n.

22. What is a cumulative frequency distribution?

    A cumulative frequency distribution shows the running total of frequencies up to and including each class, indicating how many observations fall below a given boundary.

23. What is Sturges' rule for the number of classes?

    Sturges' rule: number of classes k = 1 + 3.322 log₁₀(n), where n is the total number of observations.

24. What is the difference between classification and tabulation?

    Classification is arranging data into groups or classes based on common characteristics; tabulation is presenting classified data in rows and columns of a table.

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