Statistics Quarter 3: Data Collection Techniques

Study Notes

This is a Quarter 3 topic.
Learning targets include investigating different data collection and sampling techniques, organizing statistical data in frequency distributions, using graphs for data representation (pie, bar, line, stem-and-leaf), and interpreting statistical graphs.

Collect data from 10 students.
Collect the following information: student name, gender, favorite food, and age.

Statistics is a branch of mathematics dealing with collecting, organizing, analyzing, and interpreting data to understand phenomena.
Includes data collection, presentation, analysis, and interpretation.

Data is information, facts, or numbers collected for analysis.
Data collection, presentation, analysis, and interpretation are key aspects of statistics.

Data is collected using various methods including surveys, experiments, and observations.
Data is recorded during and after the data gathering process.

Conclusions are drawn from the analysis to interpret findings and predict future outcomes.

Descriptive Statistics: Methods for organizing, summarizing, and presenting data to reveal meaningful information.
- Example: Most Filipinos have yet to decide who to vote for as president. About 45% of university students prefer the new policy; most of them are freshmen.
Inferential Statistics: Methods to analyze data, draw inferences, or make predictions about a larger population from a sample.
- Example: A politician wants to know their chances of winning. A dean wants to predict the passing percentage for national board exams based on past results (last 6 years).

Population: All individuals or entities of interest.
- Example: Public school teachers in Luzon.
Parameter: Numerical measurement describing the population.
- Example: Average salary of public school teachers in Luzon.
Sample: Subgroup of the population.
- Example: 100 public school teachers in Luzon.
Statistics: Numerical measurement describing the sample.
- Example: Average salary of the 100 public school teachers.

Variable: Measurable characteristic of interest, applicable to every member of the population.
- Example: Gender, age, family members, grade average, type of school.
Categorical Variable: Represents attributes or characteristics.
- Example: Student gender, student's type of school.
Numerical Variable: Represents value, count, measurement, or how many/much.
- Example: Age, number of family members.
  - Discrete: Takes on integer values.
    - Example: Number of family members, number of students engaged in dancing.
  - Continuous: Takes on any value within a range.
    - Example: Student's age, GPA.

Nominal: Categories without order.
- Example: Blood type.
Ordinal: Categories with order.
- Example: Academic rank in high school (Valedictorian, Honor Roll).
Interval: Ordered categories with equal intervals.
- Example: Intelligence Quotient (IQ).
Ratio: Ordered categories with equal intervals and a true zero point
- Example: Average daily sales of a bakery.