Learning Objectives

By the end of this chapter, you will be able to:

  • Define statistics and explain its dual meaning
  • Describe the nature and characteristics of statistics
  • Explain the significance of statistics in public administration
  • Identify the scope and limitations of statistics

What is Statistics?

The word statistics is derived from the Latin word “status” or the Italian word “statista”, meaning “political state” or “government.” Originally, statistics was used by rulers to collect information about their states for taxation and military purposes.

mindmap
  root((Statistics))
    Etymology
      Latin: Status
      Italian: Statista
      Meaning: Political State
    Dual Meaning
      Plural Sense
        Numerical Data
        Facts & Figures
      Singular Sense
        Science of Methods
        Collection to Analysis
    Applications
      Government
      Business
      Research
      Public Policy

Dual Meaning of Statistics

Statistics has two distinct meanings:

1. Statistics as Data (Plural Sense)

In its plural form, statistics refers to numerical facts and figures collected systematically for a specific purpose.

Example in Public Administration:

  • Number of government employees: 450,000
  • Annual budget allocation: NPR 1,800 billion
  • Literacy rate: 68%
  • Voter turnout: 74.5%

Key Point: When we say “statistics show that…”, we are using statistics in its plural sense, referring to data.

2. Statistics as a Science (Singular Sense)

In its singular form, statistics refers to the science of collecting, organizing, analyzing, and interpreting numerical data to make informed decisions.

Key Point: When we say “Statistics is a useful subject”, we are using it in its singular sense, referring to the discipline.

Nature and Characteristics of Statistics

For data to be considered “statistical data,” it must possess certain characteristics:

flowchart TD
    A[Characteristics of Statistical Data] --> B[1. Aggregate of Facts]
    A --> C[2. Numerically Expressed]
    A --> D[3. Affected by Multiple Causes]
    A --> E[4. Collected Systematically]
    A --> F[5. Reasonable Accuracy]
    A --> G[6. Predetermined Purpose]
    A --> H[7. Comparable]

    B --> B1["Cannot be single value<br/>Must be a collection"]
    C --> C1["Must be in numbers<br/>Not qualitative statements"]
    D --> D1["Multiple factors<br/>influence the data"]
    E --> E1["Planned collection<br/>Not haphazard"]

1. Statistics are Aggregates of Facts

Statistics deals with groups or collections of data, not individual or isolated figures.

✅ Statistical ❌ Not Statistical
Average income of 500 civil servants Income of one civil servant
Heights of 100 students Height of Ram (175 cm)
Population of 77 districts Population of Kathmandu only

2. Statistics Must Be Numerically Expressed

Statistical data must be expressed in numbers. Qualitative statements without numerical values are not statistics.

✅ Statistical ❌ Not Statistical
68% literacy rate “Nepal has good literacy”
25°C average temperature “Weather is pleasant”
12.5% poverty rate “Poverty is declining”

3. Statistics are Affected by Multiple Causes

Statistical data is influenced by multiple factors, not a single cause. This is called the plurality of causes.

Example: A government employee’s performance is affected by:

  • Training received
  • Work environment
  • Salary and benefits
  • Personal motivation
  • Supervision quality

4. Statistics Must Be Collected Systematically

Data collection must follow a scientific and planned method.

flowchart LR
    A[Define Purpose] --> B[Plan Collection]
    B --> C[Design Tools]
    C --> D[Collect Data]
    D --> E[Verify Data]
    E --> F[Organize Data]

5. Statistics Should Have Reasonable Accuracy

While absolute accuracy may not be possible, statistical data should have a reasonable degree of precision appropriate to the purpose.

Example:

  • For population census: Accuracy to individual level required
  • For budget estimation: Rounding to thousands acceptable

6. Statistics Must Be Collected for a Predetermined Purpose

Data collection without a clear purpose leads to wastage of resources and unusable data.

Good Practice: “We are collecting data on employee satisfaction to improve retention rates.”

Bad Practice: “Let’s collect some data and see what we find.”

7. Statistics Should Be Comparable

For statistical analysis to be meaningful, data should be comparable in terms of:

  • Units of measurement
  • Time period
  • Geographic area
  • Method of collection

Significance of Statistics in Public Administration

Statistics plays a crucial role in modern public administration. Here’s why:

flowchart TB
    subgraph "Role of Statistics in Public Administration"
        A[Policy Formulation] --> A1["Evidence-based<br/>decision making"]
        B[Planning] --> B1["Resource allocation<br/>and forecasting"]
        C[Evaluation] --> C1["Program assessment<br/>and monitoring"]
        D[Research] --> D1["Social and behavioral<br/>research"]
        E[Accountability] --> E1["Performance metrics<br/>and reporting"]
    end

1. Policy Formulation

Statistics provides the factual basis for developing public policies.

Example:

  • Child mortality statistics → Health policy decisions
  • Unemployment data → Employment generation programs
  • Crime statistics → Law enforcement strategies

2. Planning and Budgeting

Government planning relies heavily on statistical data for:

  • Population projections
  • Revenue forecasting
  • Resource allocation
  • Infrastructure development

3. Program Evaluation

Statistics helps evaluate the effectiveness of government programs:

Program Baseline Current Change
Literacy Campaign 54% 68% +14%
Vaccination Drive 67% 91% +24%
Road Connectivity 45% 73% +28%

4. Administrative Research

Public administration research uses statistics for:

  • Survey analysis
  • Hypothesis testing
  • Trend analysis
  • Comparative studies

5. Accountability and Transparency

Statistical reports enable:

  • Public disclosure of government performance
  • Comparison across departments
  • Identification of areas needing improvement

Scope of Statistics

The scope of statistics is vast and continuously expanding:

mindmap
  root((Scope of Statistics))
    Government
      Census
      Economic Planning
      Defense
      Public Health
    Business
      Market Research
      Quality Control
      Financial Analysis
    Science
      Medical Research
      Agricultural Studies
      Environmental Analysis
    Social Sciences
      Psychology
      Sociology
      Political Science
      Public Administration

In Public Administration Specifically:

  1. Human Resource Management
    • Employee performance metrics
    • Recruitment analysis
    • Training effectiveness
  2. Financial Administration
    • Budget analysis
    • Revenue collection patterns
    • Expenditure monitoring
  3. Development Administration
    • Poverty indicators
    • Development indices
    • Program impact assessment
  4. Urban and Rural Administration
    • Population distribution
    • Service delivery metrics
    • Infrastructure statistics

Limitations of Statistics

While statistics is powerful, it has certain limitations:

1. Deals Only with Quantitative Data

Statistics cannot directly handle qualitative aspects like honesty, ethics, or beauty.

2. Studies Aggregates, Not Individuals

Statistical conclusions apply to groups, not specific individuals.

3. Results are Averages

Statistical results represent average conditions, not exact values for every case.

4. Can Be Misused

“There are three kinds of lies: lies, damned lies, and statistics.” — Mark Twain

Statistics can be manipulated through:

  • Selective data presentation
  • Inappropriate methods
  • Misleading visualizations

5. Requires Expertise

Proper statistical analysis requires trained personnel to:

  • Design appropriate studies
  • Choose correct methods
  • Interpret results accurately

Key Formulas Introduction

Throughout this course, you will encounter various formulas. Here’s a preview of basic notation:

Summation Notation

The Greek letter sigma (Σ) represents summation:

\[\sum_{i=1}^{n} x_i = x_1 + x_2 + x_3 + ... + x_n\]

Example: If $x_1 = 5$, $x_2 = 8$, $x_3 = 12$, then:

\[\sum_{i=1}^{3} x_i = 5 + 8 + 12 = 25\]

Sample Size Notation

  • $n$ = sample size (number of observations)
  • $N$ = population size
  • $\bar{x}$ = sample mean (x-bar)
  • $\mu$ = population mean (mu)

Practice Questions

Conceptual Questions

  1. Define statistics in both its singular and plural meanings with examples from public administration.

  2. Explain any five characteristics of statistical data.

  3. Discuss the significance of statistics in public administration with at least three examples.

  4. What are the limitations of statistics? How can these be addressed?

  5. “Statistics is the backbone of evidence-based governance.” Discuss.

Multiple Choice Questions

Q1. Statistics in its singular sense refers to:

  • a) Numerical data
  • b) Collection of facts
  • c) Science of data analysis ✓
  • d) Government records

Q2. Which is NOT a characteristic of statistical data?

  • a) Must be numerically expressed
  • b) Must be collected systematically
  • c) Can be a single observation ✓
  • d) Should be comparable

Q3. The word ‘statistics’ is derived from:

  • a) Greek word ‘static’
  • b) Latin word ‘status’ ✓
  • c) French word ‘statistique’
  • d) German word ‘statistik’

Summary

Concept Key Points
Definition Dual meaning: Data (plural) and Science (singular)
Nature Aggregate, numerical, systematic, comparable
Significance Policy making, planning, evaluation, research
Scope Government, business, science, social research
Limitations Quantitative only, averages, can be misused

Next Chapter

In the next chapter, we will explore Descriptive and Inferential Statistics - the two main branches of statistics and their applications in public administration research.