RESEARCH Q3

1. Data Collection Methods

Interviews (Face-to-Face, Telephone, CAPI): Provide detailed insights but can be time-consuming and expensive.
Questionnaires (Paper-Pencil, Web-Based): Cost-effective and anonymous, but may suffer from low response rates.
Experimental Method: A controlled study to establish cause-and-effect relationships; highly reliable but time-intensive.
Observational Study: Records real-time events, reducing bias but potentially difficult to interpret.

2. Data Organization

Definition: The process of classifying and structuring data for better usability.

Ways to Organize Data:

Graphs
Charts
Tables
Pictures
Graph: A visual representation of data relationships.
Chart: A structured display of data in tables, graphs, or diagrams.

3. Types of Graphs

Bar Graph: Represents independent values.
Line Graph: Displays trends and changes over time.
Cartesian Graph: Uses numerical axes to illustrate relationships, commonly used in algebra.

4. Definition of Statistics

Statistics involves the design of experiments, data collection, classification, organization, interpretation, and decision-making. It is divided into:

Descriptive Statistics: Summarizes and presents data using graphs, tables, measures of central tendency, and variability.
Inferential Statistics: Makes predictions about a population based on a sample.

5. Measures of Central Tendency

A single value representing a dataset:

Mean: The average of all values.
Median: The middle value when data is arranged in order.
Mode: The most frequently occurring value.

6. Measures of Variability

Indicates how spread out the data is:

Range: The difference between the highest and lowest value.
Mean Deviation: The average of absolute differences from the mean.
Variance: The mean of squared deviations from the mean, useful for statistical comparisons.
Standard Deviation: Measures the average distance of data points from the mean.