Lecture Notes: Research Methods and Critical Thinking in Psychology
Foundations: Psychology as a science
Psychology is a science, like biology or chemistry, but it studies people's minds and behaviors. This section helps you understand how we do scientific research in psychology.
Some topics might be more interesting than others, but it's all important to learn how research works.
Class rules:
You need to take part in research or experiments to get 10 credits by the end of the semester.
We track attendance, usually with Poll Everywhere, to help you come to class regularly.
The teacher needs department approval to set up some things, so it might take a little longer.
Core themes: thinking like scientists in psychology
To think like a scientist in psychology, you need to avoid being too confident or just relying on common sense, as these can trick you (Dunning–Kruger effect).
Dunning–Kruger effect: People who know less about something often think they know a lot, and those who know a lot might underestimate themselves. It's important to be careful when judging your own knowledge or data.
People often see patterns in random things (like athletes having a certain routine) even when there are no real patterns.
Hindsight bias: After something happens, people often say they "knew it all along," making them feel smarter than they actually were. For example, after a game, commentators might claim they predicted the outcome.
Social media can spread wrong information and create "echo chambers" where you only see opinions that match yours, making things more divided. We need to be careful and check our sources.
It's important to look at how many people were studied and if they represent the bigger group (e.g., if a TikTok video about a disorder is actually reliable).
Just because many people are talking about something on social media doesn't mean it's true or important (often, the studies are small).
You need to be good at understanding what you see in the media and know that computer programs (algorithms) can influence what you see, creating echo chambers.
Key concepts in research methods (overview)
How scientists do research:
They start with a theory (an idea) and create a hypothesis (a testable prediction).
They test the hypothesis using empirical studies, which are carefully designed experiments to look at specific factors.
If different studies show the same results (replication), the evidence gets stronger. If results are different, it makes scientists question their methods.
Defining and measuring things can be hard:
Operational definitions: These are exact, measurable ways to describe something abstract, like "happiness." For example, happiness could be measured by a self-report scale or by looking at brain activity.
Confounding variables: These are other factors that could secretly affect the outcome of a study, making it hard to tell what's really causing what. Researchers try to control these, but many things can affect results (e.g., sleep studies and memory are affected by stress, caffeine, etc.).
External validity and generalizability: Case studies (studying one person deeply) and naturalistic observations (watching people in their natural environment) give lots of details but might not apply to everyone else.
Theoretical foundations and core terms
Theory: An overall idea or set of rules that explains why things happen; it leads to predictions that can be tested.
Hypothesis: A specific, testable prediction that comes from a theory.
Operational definition: A clear, measurable way to define something (e.g., happiness might be measured by scores on a survey, specific brain signals like dopamine levels, or observed behaviors).
Variables: Anything that can change or vary. In studies, variables are things that can be changed or measured.
Independent vs. dependent variables: The independent variable is what the researcher changes or manipulates (e.g., giving different doses of a drug). The dependent variable is what the researcher measures to see if the change had an effect (e.g., measuring mood after taking the drug).
Research designs: from case studies to experiments
Case study
Studying one person or a small group in great detail (like Freud's theories, which often came from studying individual patients).
Good things: Lots of detailed information; helps understand rare situations.
Bad things: Hard to apply to many people; the information might be biased if the person tells only what they want.
Naturalistic observation
Watching behavior in its regular environment (like Jane Goodall watching monkeys; or watching a child with ADHD in school).
Good things: Shows real behavior; happens in a real-world setting.
Bad things: The observer can accidentally influence what they see; people might act differently if they know they're being watched; hard to control what happens.
Surveys
Very common; easy to gather information from many people.
Problems: How questions are worded can change answers; some people might be left out (sampling bias). Need random sampling where everyone has an equal chance to participate, to get a group that truly represents the broader population.
Correlational studies
Look at how two things are related without changing anything.
Important point: Just because two things are related doesn't mean one causes the other. For example, social media use and mental health problems in teens might be related, but we can't say social media causes mental health issues from this type of study alone.
Correlation coefficient: A number () between and .
The sign (plus or minus) tells you the direction: positive means both go up or down together; negative means one goes up when the other goes down.
The strength is how close the number is to (ignoring the sign). In psychology, a strong correlation might be around , not necessarily .
Directionality problem: We can't tell if A causes B, or B causes A, or if something else causes both.
Illusory correlations: Seeing relationships that aren't really there (e.g., ice cream sales and crime go up in summer, but ice cream doesn't cause crime; hot weather causes both).
Experimental designs (to find causes)
This is the only method that can show if one thing causes another, by changing one factor (independent variable) and randomly putting people into different groups.
Limits: Some things are impossible or wrong to manipulate (e.g., how breastfeeding affects IQ). In these cases, researchers use other methods like quasi-experiments (comparing existing groups) or longitudinal studies (following people over time).
Ethics: Past unethical experiments (like Nazi experiments) show why strict rules are needed to protect people. Even studies with ethical problems can give information, but we must be careful with it.
Replication
Doing a study again to see if the results are the same. If they are, it makes the findings more reliable. If they're different, it makes scientists look closer at the methods or situations.
Measurement and data visualization
Graphs help us see relationships that are hard to spot in tables of numbers.
For example, a scatter plot shows how two variables relate. If points form a line, there's a strong relationship; if they're scattered like a cloud, there's no clear relationship.
How to understand data:
A positive correlation means as one thing increases, the other generally increases too. A negative correlation means as one thing increases, the other generally decreases.
The correlation number doesn't tell you about cause and effect.
Regression toward the mean: If someone performs extremely well or poorly, their next performance will likely be closer to their average. This can make it seem like there's a pattern or a "jinx" when it's just natural variation.
Sleep, memory, and confounding variables (example discussion)
Using sleep and memory as an example to explain predictions and other influential factors:
Idea (Theory): Memories get stronger during sleep; not enough sleep harms memory.
Prediction (Hypothesis): People will remember less when they haven't slept enough compared to after eight hours of sleep. We can write this as: \text{Memory score (deprived)} < \text{Memory score (8 hours)} or look at the difference: \text{Difference} = \text{Memory score (8 hours)} - \text{Memory score (deprived)} > 0.
Other factors (confounds): Stress, drug use, mood, environment, what kind of task it is, and even where the study happens can all affect memory. Researchers try to control or account for these "confounding variables."
Having clear operational definitions for memory (e.g., test scores) and sleep (e.g., hours slept) is crucial to measure them properly.
Ethical considerations in research (summary)
When studying people, ethical rules are very important. Researchers must cause the least harm, get informed consent (people agree to participate after knowing what's involved), and make sure the experiment is fair.
Some studies (quasi-experiments) can't randomly assign people, so they use existing groups or observe over time, which is ethical.
Bad experiments from the past (e.g., Nazi experiments) remind us to always put participants' rights and well-being first, even if a study could give valuable information.
Real-world links and practical implications
How wrong information spreads and social media's role in shaping what we believe:
You need to check the number of people studied, who is giving the information, and how the study was done before you believe its findings.
Be aware of echo chambers and how computer programs can make you see more of what you already believe.
Polarization and information bubbles:
Only seeing content that matches your views can make your opinions more extreme.
Critical thinking and scientific understanding:
Students should ask about how people were chosen for a study, how things were measured, what other factors might have influenced results, and whether a study can truly show cause and effect.
Applying this to daily life:
Our natural biases (like Dunning–Kruger and hindsight bias) influence how we understand information and study results.
Knowing the difference between correlation and causation helps us avoid jumping to conclusions, like thinking social media causes mental health issues, or sugar causes ADHD, without considering other reasons or two-way effects.
Quick recap: takeaways for studying and evaluating research
Always separate an idea (theory) from a prediction (hypothesis) and specific measurements (operational definitions); make sure measurements are clear and can be repeated.
Be careful of biases and wrong information; check the group size, if it represents the population, and other possible influencing factors (confounds).
Correlation doesn't mean causation; look for experiments or long-term studies to prove cause and effect.
If a study is replicated with the same results, the claims are stronger; if results differ, carefully examine the methods.
Ethics are fundamental in human research; always think about risks, consent, and peoples' welfare.
Notes on course logistics and next steps (recap)
You'll need to do some research participation and sign up through the university system. The teacher will give more details on setting this up (around mid-semester).
Attendance will likely use Poll Everywhere to encourage you to come to class regularly.
Future classes will go deeper into the scientific method, experiments, replication, and specific studies about sleep, memory, and feelings.