Introduction to Statistics

Introduction to Statistics

• Statistics is the field of mathematics focused on collecting, tabulating, and interpreting numerical data.
• It involves using mathematical models to analyze data from real-world studies and experiments.

Outline

• Definitions of Terms: This section will cover key terms used in statistics.
• Statistical Methods: This segment defines the various approaches for collecting data.
• Types of Statistics: Describes the difference between descriptive and inferential statistics.
• Difference between Descriptive and Inferential Studies: This explains the distinct approaches to analyzing data.

Definitions of Terms

• Statistics: A tool for organizing, summarizing, and communicating findings (data) clearly and meaningfully.
• Medical Statistics/Biostatistics: A science applying statistical principles to health-related issues.
• Data: The basic elements or building blocks of statistical analysis.

Importance of Statistics

• Statistics provides a clear and transparent picture of work processes.
• Statistical methods help analyze various fields like medicine, economics, business, and social sciences.
• Organized data presentation is achieved with graphs, tables, diagrams, and charts.
• Statistics enables an understanding of data patterns and variations.
• Statistics is a method and tool for accurate quantitative data acquisition.

Population and Parameter

• Population (N): All elements (people or things) whose characteristics are being studied.
• Parameter: A value about a population (e.g., mean, total, average), calculated from the entire population.

Sample and Statistic

• Sample (n): A subset of the target population selected for study, used to make inferences about the population.
• Statistic: A value representing a characteristic of a sample (e.g., sample mean), that can be calculated directly from the collected data.

Sample

• A sample comprises one or more observations from a population.
• Subjects are the units on which characteristics are measured, often humans, also cells in culture or animals for research.

Census vs Sample

• A census collects data from the entire population.
• A sample collects data from a representative subset of the population.

Statistical Methods

• A) Methods of Data Collection.
• B) Analytic Statistics.
• C) Methods of Data Presentation.

What is Data?

• Data are observations or evidence concerning the social world.
• Data can be quantitative or qualitative.
• Data is produced, not given; researchers select what to record.

Data and Information

• Information is processed data that is meaningful and useful.
• Data + Meaning = Information. (Example: Individual exam scores are data, but processing them to show boys scored higher than girls is information.)

Sources of Data

• Census
• Vital registration
• Official records
• Simple survey
• Individuals studied

Nature of Data

• Data can be classified into:
  • Qualitative Data (or Attributes)
  • Quantitative Data (or Variables)

Types of Statistics

• Descriptive/Deductive
• Inferential/Inductive

Descriptive Statistics

• Techniques to organize, display, and describe using tables, graphs, and summary measures.

Inferential Statistics

• Techniques using sample data to make predictions or inferences about a population.

Statistics and Research

• Applied in research studies for analyzing collected data.
• Examples of using statistics in research include determining preference differences and meaningful statistical differences in research participation.

Descriptive and Inferential Statistics

• Descriptive: Organizes, summarizes, and presents data.
• Inferential: Generalizes from samples to populations; tests hypotheses and assesses relationships among variables.

Types of Statistics (Another Classification)

• Descriptive Statistics:
  • Measures of Central Tendency (mean, median, mode)
  • Measures of Dispersion (range, variance, standard deviation)
• Inferential Statistics:
  • Hypothesis Testing (z-test, t-test, ANOVA)
  • Regression Analysis