Book Link 14 Analyzing Findings
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By the end of this section, you will be able to:
- Define correlation coefficient and its relationship between variables.
- Recognize correlation without implying cause-and-effect.
- Explain random sampling and control groups.
Coorelation & Coorelation Coefficient
A correlation coefficient is a number that tells us how two things are connected. It shows how strong and which way the connection goes between the two things. For example, the correlation is positive if one thing goes up and the other goes down and negative if one goes up and the other goes down.
Correlation doesn’t mean that one thing causes the other. It just shows that they change together. For example, just because people who eat more ice cream also buy more sunglasses doesn’t mean that eating ice cream causes people to buy sunglasses. It’s just a connection, not a cause.
A correlation coefficient helps us understand how two variables are related. It gives us a number that shows the strength and direction of the relationship between the variables.
Correlation does not show that one variable causes the other to change. It only shows that the two variables change together but does not prove that one variable directly causes the other to change.
Sometimes, we may think that two things are related when they are not. This can happen because our minds naturally look for patterns and connections, even when they don’t exist.
Random sampling, a method that ensures every member of a population has an equal chance of being chosen for a study, underscores the fairness and objectivity of our research.
By assigning participants into experimental and control groups randomly, we can be confident that any differences in the outcomes are likely due to the treatment, not the selection process.
Recognizing and mitigating experimenter or participant bias is crucial in maintaining the integrity of our experiments. If the experimenter or the participants have certain expectations or beliefs, it can significantly influence how they behave or interpret the results of the study. By being aware of this, we can ensure the validity and reliability of our research.
In an experiment, the researcher changes or manipulates the independent variable. The dependent variable is measured and expected to change as a result of the independent variable.
Example Experiment: School Lunch vs Vending Machine
Objective:
Hypothesis:
Methodology:
Survey Questions:
Data Analysis:
Conclusion:
The findings from this investigation will provide insights into students’ preferences for school-provided meals versus vending machine snacks, and whether there is a correlation between their opinions of school lunches and snack choices.