Sampling: This is all about who's in your study! It's like inviting guests to a party - you pick and choose who comes. The people (or sometimes animals or things) you choose to study are your sample.
Real-world example: Let's say you want to study if teenagers who watch superhero movies are more likely to help others. If you only ask the kids in your school who are part of the comic book club, your results might not truly represent all teenagers. This shows how your sampling technique can shape your conclusions.
Credibility: Can we trust the study's results? It's a bit like Detective Work! If the study is full of bias, like only noticing clues that fit the theory, it's not very credible.
Real-world example: Let's imagine you're researching whether dogs or cats are smarter. But, you are a die-hard dog lover and dismiss evidence that cats can perform complex tasks. In this case, your bias might affect the credibility of your study.
Generalizability: Can the study's findings be applied to a wider group or different settings? If you discover that all students in your class prefer vanilla ice cream over chocolate, can you say that ALL teenagers prefer vanilla? That's what generalizability is all about.
Real-world example: A study finds that wearing glasses correlates with higher grades in a single school. Can we say that this applies to all schools worldwide? That's a question of generalizability.
Bias: Like the villain in our research story, bias is anything that skews your results. It could come from researchers (like only seeing what you want to see) or from participants (like trying to guess what the researcher wants).
Real-world example: You conduct a survey asking people if they think exercise is important while wearing a gym uniform. Participants may answer "yes" more often because they guess you're promoting fitness, creating bias in your results.
💡 Remember, these terms are used in all social science research, but the way they're handled can vary between quantitative (more about numbers and statistics) and qualitative (more about words and meanings) research.
Sampling Techniques: There are many ways to select your sample. Depending on your technique, the strengths and limitations of your study might change.
Credibility and Bias: These two often go hand in hand. If your study is biased, its credibility decreases. A credible study has controlled or eliminated bias as much as possible.
Quantitative and Qualitative Differences: The way these key concepts are approached can be different in quantitative and qualitative research. Quantitative research might focus more on how generalizable the results are, while qualitative research might give more weight to the credibility of the findings.
As you progress through your psychology studies, remember to revisit these terms and deepen your understanding of them. They're like the Avengers of research - each plays a different role, but together, they ensure that your research study is powerful and trustworthy! 🦸♀️🦸♂️
Sampling: This is all about who's in your study! It's like inviting guests to a party - you pick and choose who comes. The people (or sometimes animals or things) you choose to study are your sample.
Real-world example: Let's say you want to study if teenagers who watch superhero movies are more likely to help others. If you only ask the kids in your school who are part of the comic book club, your results might not truly represent all teenagers. This shows how your sampling technique can shape your conclusions.
Credibility: Can we trust the study's results? It's a bit like Detective Work! If the study is full of bias, like only noticing clues that fit the theory, it's not very credible.
Real-world example: Let's imagine you're researching whether dogs or cats are smarter. But, you are a die-hard dog lover and dismiss evidence that cats can perform complex tasks. In this case, your bias might affect the credibility of your study.
Generalizability: Can the study's findings be applied to a wider group or different settings? If you discover that all students in your class prefer vanilla ice cream over chocolate, can you say that ALL teenagers prefer vanilla? That's what generalizability is all about.
Real-world example: A study finds that wearing glasses correlates with higher grades in a single school. Can we say that this applies to all schools worldwide? That's a question of generalizability.
Bias: Like the villain in our research story, bias is anything that skews your results. It could come from researchers (like only seeing what you want to see) or from participants (like trying to guess what the researcher wants).
Real-world example: You conduct a survey asking people if they think exercise is important while wearing a gym uniform. Participants may answer "yes" more often because they guess you're promoting fitness, creating bias in your results.
💡 Remember, these terms are used in all social science research, but the way they're handled can vary between quantitative (more about numbers and statistics) and qualitative (more about words and meanings) research.
Sampling Techniques: There are many ways to select your sample. Depending on your technique, the strengths and limitations of your study might change.
Credibility and Bias: These two often go hand in hand. If your study is biased, its credibility decreases. A credible study has controlled or eliminated bias as much as possible.
Quantitative and Qualitative Differences: The way these key concepts are approached can be different in quantitative and qualitative research. Quantitative research might focus more on how generalizable the results are, while qualitative research might give more weight to the credibility of the findings.
As you progress through your psychology studies, remember to revisit these terms and deepen your understanding of them. They're like the Avengers of research - each plays a different role, but together, they ensure that your research study is powerful and trustworthy! 🦸♀️🦸♂️