Lesson 5: Sampling Method

Sampling Method

Population vs Sample

  • Population: The entire group that you want to draw conclusions about.

  • Sample: The specific group of individuals from whom you will collect data.

Primary Types of Sampling Method

  • Probability Sampling: Involves random selection, enabling strong statistical inferences about the whole group.

  • Non-probability Sampling: Involves non-random selection based on convenience or other criteria for easier data collection.

Probability Sampling

  • Every member of the population has a known and equal chance of being selected.

  • Commonly used in quantitative research for objectivity and accuracy.

Types of Probability Sampling

  1. Simple Random Sampling:

    • Each individual has an equal chance of selection.

  2. Systematic Sampling:

    • Similar to simple random sampling, but selection occurs at regular intervals.

    • Individuals are chosen from a numbered list at regular intervals.

  3. Stratified Sampling:

    • Population is divided into subgroups (strata) based on specific characteristics.

    • Samples are randomly selected from each stratum.

  4. Cluster Sampling:

    • Population is divided into subgroups with similar characteristics to the whole sample.

    • Entire subgroups are randomly selected instead of individuals.

Examples of Probability Sampling Methods

  1. Simple Random Sampling:

    • Grade 11 students assign numbers to all students and use a random number generator to select 50 participants for research on study habits.

  2. Systematic Sampling:

    • A research group lists all students and selects every 5th name, starting from a randomly chosen student to study food preferences.

  3. Stratified Sampling:

    • Students divide the population into male and female groups and randomly select an equal number of participants from each group for a study on extracurricular activities.

  4. Cluster Sampling:

    • Researchers randomly select one section from each school strand (e.g., STEM, HUMSS) and survey all students in those sections to study classroom participation.

Non-Probability Sampling Methods

  • Individuals are selected based on non-random criteria, meaning not everyone has a chance of being included.

Types of Non-Probability Sampling

  1. Convenience Sampling:

    • Sample is chosen for accessibility (e.g., surveying people at a mall).

  2. Quota Sampling:

    • Similar to stratified sampling but non-random; researchers ensure the sample reflects specific characteristics.

  3. Purposive Sampling:

    • Researcher selects individuals based on their expertise or relevance to the study.

  4. Snowball Sampling:

    • Existing participants recruit additional participants, useful for hard-to-reach populations.

Examples of Non-Probability Sampling Methods

  1. Convenience Sampling:

    • For a study on social media usage, students survey classmates who are readily available during lunch.

  2. Quota Sampling:

    • A research team studying exercise habits surveys 15 males and 15 females and stops collecting responses once the quota is met.

  3. Purposive Sampling:

    • Students interview honor students for a study on academic excellence.

  4. Snowball Sampling:

    • Students start with eco-club members and ask for recommendations of other students interested in environmental initiatives.