Population: A population is a distinct group of individuals, whether it’s a nation or a group sharing a common characteristic.The population is the entire group about which conclusions are drawn.
Sample and Sampling:
- Sample: A small part or quantity representing the whole. In research, a sample is a specific group taken from a larger population for measurement. The sample is the group from which data is collected, providing insights into the larger population.
Sampling:
Sampling is the process of selecting individual members or a subset of the population to draw statistical inferences and estimate characteristics of the entire population in a research study.
Sampling Techniques (Probability, Non-Probability):
Probability Sampling Techniques:
Simple Random Sampling:
Simple random sampling is like picking names out of a hat. Imagine you have a big jar filled with different colored marbles, and each marble represents a person in your population. You close your eyes, mix the marbles well, and randomly pick a few. Every person (marble) in the jar has an equal chance of being selected. This ensures that your sample represents the whole population without any bias.
Systematic Sampling:
Systematic sampling is a bit like organizing a line of people and then selecting every nth person. Let’s say you have a list of students in a school. Instead of randomly choosing, you decide to pick every 5th student on the list. This method is more straightforward than random sampling and still provides a representative sample.
Stratified Sampling:
Stratified sampling is like creating different groups or “strata” based on certain characteristics. If you want to study the favorite subjects of students in a school, you might divide them into groups by grade level. Each grade becomes a stratum, and then you randomly select students from each stratum. This ensures that each grade is properly represented in your study.
Proportionate Stratified Sample Example: If there are 100 students in Grade 10 and 200 in Grade 11, a proportionate stratified sample would mean that your sample size reflects these proportions – maybe 1 student from Grade 10 for every 2 from Grade 11.
Disproportionate Stratified Sampling Example: In this case, you might choose to interview more students from Grade 10 than Grade 11, even though Grade 11 has a larger population. This could be because you believe Grade 10 students might have unique perspectives relevant to your study.
Clustered Sampling:
Clustered sampling is like selecting groups or “clusters” and then randomly choosing from those groups. If you want to study different schools in a district, you might first randomly select a few schools (clusters) and then gather data from all students in those schools.
Convenience Sampling:
Convenience sampling is like picking the people who are easiest to reach. If you stand outside a grocery store and ask people about their shopping habits, your sample is based on who happens to pass by. It’s easy but might not represent the larger population well.
Quota Sampling:
Quota sampling is like setting specific targets for characteristics you want in your sample. If you’re studying smartphone usage and you know that 60% of your population is under 30, you might set a quota to ensure your sample reflects this age distribution.
Judgment (or Purposive) Sampling:
Judgment sampling is like choosing participants based on the researcher’s judgment. If you’re studying expert chefs, you might select participants based on their expertise and unique experiences rather than randomly picking from the general population.
Snowball Sampling:
Snowball sampling is like starting with one participant and then asking them to refer others. If you’re researching a small, tight-knit community, one participant might introduce you to others, creating a “snowball effect” in your sample.
Educational Research Proposal:
- Definition: A document designed to expand students’ thinking capabilities and contribute new information to the existing body of knowledge in education.
- Purpose: Contribute solutions to current educational problems.
Educational Research Report:
- Definition: A condensed paper presenting summarized research findings.
- Importance: Common task in academia and beyond for effective scholarly communication.
APA Manual:
- Definition: APA (American Psychological Association) style manual for scholarly writing.
- Importance: Used globally for concise, persuasive scholarly communication.
Bibliography/References:
- Definition: List of works on a subject or by an author, appearing at the end of a document.
- Importance: Documents sources cited in a paper for verification.
Pilot Testing:
- Definition: Rehearsal of a research study with a small group of participants before the main study.
- Purpose: Ensures the research approach runs smoothly.
Panel of Experts:
- Definition: Small group offering advice or discussing opinions, often for evaluation or decision-making.
- Example: A panel of experts judging a competition.
Statistical Testing:
- Definition: Mechanism for making quantitative decisions about processes.
- Types: Paired T-Test, Independent T-Test, Analysis of Variance (ANOVA), Correlation.
- Purpose: Provides statistical insights into data.
Correlation:
- Definition: Statistical term describing the degree of coordination between two variables.
- Types: Positive correlation, Negative correlation, Zero or no correlation.
- Purpose: Understand relationships between variables.
SPSS (IBM):
- Definition: Statistical tool for survey authoring, data mining, text analytics, and statistical analysis.
- Origin: Developed by Nie, Bent, and Hull in the 1960s.
- Advantage: Specialized for statistics compared to general-purpose tools like Microsoft Excel.