Unit 1 of 4 · BBA Sem 2

Unit 1: Introduction to statistics & sampling

Business Statistics notes · PTU syllabus (BBA 201-18)

3 min read5 topics8 exam questions
On this page
  1. Unit summary
  2. Meaning, features, importance and scope
  3. Sources of data
  4. Frequency distribution
  5. Population, sample, descriptive and inferential statistics
  6. Sampling methods
  7. Key terms
  8. Quick revision
  9. Important questions

Unit summary

Business decisions rely on numbers — sales trends, customer surveys, quality checks. Statistics provides the tools to collect, organise and interpret such data. This unit covers the meaning, features, importance and scope of statistics, sources of data, frequency distributions, populations and samples, descriptive and inferential statistics, and sampling methods.

After this unit you can

  • Define statistics and explain its features, importance and scope in business
  • Distinguish primary and secondary data and build frequency distributions
  • Distinguish population and sample and descriptive and inferential statistics
  • Explain probability and non-probability sampling methods

PTU syllabus topics

  • Meaning
  • features
  • importance and scope of statistics
  • sources of primary and secondary data
  • frequency distribution
  • population and sample
  • descriptive and inferential statistics
  • probability and non-probability sampling methods
ClassificationSampling methods
Sampling
  • Simple random

    Every member has an equal chance

  • Stratified

    Random samples from each subgroup

  • Systematic

    Every kth item from a list

  • Cluster

    Randomly chosen whole groups

  • Non-probability

    Convenience, judgement, quota, snowball

1

Topic 1

Meaning, features, importance and scope

Statistics (singular) is the science of collecting, classifying, presenting, analysing and interpreting numerical data. Statistics (plural) are numerical facts collected for a purpose. Features (Secrist): aggregates of facts, numerically expressed, affected by multiple causes, collected systematically for a purpose, reasonably accurate and comparable. Importance in business: market research, demand forecasting, quality control, financial analysis, HR analytics (attrition, performance) and decision-making under uncertainty. Limitations: studies only quantitative data and groups (not individuals), results are true on average, and data can be misused.

2

Topic 2

Sources of data

ComparisonPrimary vs secondary data
Primary data
Secondary data

Meaning

Collected first-hand for the purpose

Already collected by others

Methods/sources

Surveys, interviews, observation, experiments

Government reports, RBI bulletins, company reports, websites

Cost and time

High

Low

Reliability for the purpose

High

Must be checked

3

Topic 3

Frequency distribution

A frequency distribution groups data into classes and shows how many observations fall into each.

MarksNumber of students
0–204
20–4010
40–6018
60–8012
80–1006

Key terms: class limits, class interval (width), mid-value, frequency and cumulative frequency. A good distribution has 5–15 classes of equal width.

4

Topic 4

Population, sample, descriptive and inferential statistics

  • Population (universe): the whole group under study (all customers of a bank).
  • Sample: a part of the population selected for study. A parameter describes a population; a statistic describes a sample.
  • Descriptive statistics summarise data (averages, charts). Inferential statistics draw conclusions about a population from a sample (estimation, hypothesis testing).
5

Topic 5

Sampling methods

ClassificationSampling methods
Sampling
  • Probability: simple random

    Every unit has an equal chance (lottery, random numbers)

  • Probability: stratified

    Divide into strata, sample each

  • Probability: systematic

    Every kth unit

  • Probability: cluster

    Randomly choose whole groups

  • Non-probability: convenience, judgement, quota, snowball

    Chosen by ease or judgement

Exam tip

Probability sampling allows results to be generalised to the population; non-probability sampling is quicker and cheaper but may be biased.

Key terms

Statistics
The science of collecting and analysing numerical data
Population
The entire group under study
Sample
A subset of the population
Parameter
A measure describing a population
Stratified sampling
Sampling separately from each subgroup

Quick revision

  • Primary = first-hand; secondary = already published.
  • Parameter (population) vs statistic (sample).
  • Descriptive summarises; inferential generalises.
  • Probability: random, stratified, systematic, cluster.

Important exam questions

Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).

Short-answer questions

  1. Q1.Define statistics and list two limitations.
  2. Q2.Differentiate between primary and secondary data.
  3. Q3.Differentiate between population and sample.
  4. Q4.What is inferential statistics?
  5. Q5.What is systematic sampling?

Long-answer questions

  1. Q1.Explain the importance and scope of statistics in business.
  2. Q2.Explain the construction of a frequency distribution with an example.
  3. Q3.Explain probability and non-probability sampling methods.

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