2.1 Why Is Research Important?

The Process of Scientific Research

• Deductive reasoning: ideas are tested against the empirical world

  • Scientists use deductive reasoning to empirically test their hypotheses.

  • Deductive reasoning begins with a generalization (hypothesis) that is used to reach logical conclusions about the real world.

    • If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct.

• Inductive reasoning: empirical observations lead to new ideas

  • Inductive reasoning uses empirical observations to form broad generalizations.

  • Scientists use inductive reasoning to form theories, which in turn form hypotheses that are tested with deductive reasoning.

• Theory: a well-developed set of ideas that propose an explanation for observed phenomena.

• Hypothesis: a testable prediction about how the world will behave and it’s often worded as an if-then statement

  • A scientific hypothesis is falsifiable, or capable of being shown to be incorrect.

  • As hypotheses are tested, theories are modified to incorporate the result of these tests.

2.2 Approaches to Research

Clinical or Case Studies

• Clinical/case study: when an experiment/research involves focusing on one person or a few people.

• By doing a clinical study, scientists focus their attention on a very small number of people, and can gather a lot more information in comparison to other research methods.

  • However, since the cases are so specific, what they’ve learned will mainly apply to their test subjects and can’t be universally applied.

• Generalizing: the ability to apply the findings of a particular research project to larger segments of society

Naturalistic Observation

• Naturalistic observation: observing behavior in its natural setting

• It’s critical that the observer be as discrete as possible because when people are aware they’re being observed, they are less likely to behave naturally.

• Naturalistic observation is not limited to research involving humans.

• A benefit to naturalistic observation is it’s accuracy and ability to be universally applied. A downside is that it’s hard to to set up and control, and observer bias may occur.

• Observer bias: when the observer unconsciously skews their observations to fit their hypothesis/expectations.

• Inter-rater reliability: a measure of reliability that assesses the consistency of observations by different observers.

Surveys

• Surveys: a series of questions to be answered by research participants, and can be administered as paper-and-pencil questionnaires, electronically, or verbally.

• A benefit to surveys is that they allow researchers to gather data from larger samples in comparison to other research methods.

• A downside is that the information won’t be as great or detailed as that of a case study. and the participants may also give inaccurate answers, making the data unreliable.

• Sample: a subset of individuals selected from a population

• Population: the overall group of individuals that the researchers are interested in. Researchers study the sample and generalize their findings to the population.

Archival Research

• Archival research: looking at past records or data sets to find patterns or relationships.

• The researcher never interacts with participants and they have no control over the original information collected, so the hypothesis must be adjusted to fit the original data/experiment.

Longitudinal and Cross-Sectional Research

• Longitudinal research: a research design in which data is gathered over an extended period of time.

  • A downside to this research is that the results won’t be known for years or even decades.

  • The long period of time also caused a high attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies

• Cross-sectional research: a researcher compares multiple segments of the population at the same time.

  • Cross-sectional research is shorter than longitudinal research, but it’s limited by differences that exist between the different groups being compared that aren’t being tested/observed.

2.3 Analyzing Findings

Correlational Research

• Correlation: a relationship between two or more variables, but this relationship does not necessarily imply cause and effect; as one variable changes, so does the other.

  • Correlation can be calculated with a correlation coefficient.

• Correlation coefficient: a number from -1 to +1 that indicates the strength and direction of the relationship between variables; usually represented by the letter r.

  • The closer the correlation coefficient is to 1, whether it’s negative or positive, the more strongly related the variables are, and the more predictable the changes in one variable will be as the other variable changes. However, the closer the number is to zero, the weaker the relationship, and the less predictable the relationships between the variables becomes.

  • The sign of the correlation coefficient indicates the direction of the relationship.

    • Positive correlation: the variables move in the same direction; as one variable increases so does the other and when one variable decreases so does the other.

    • Negative correlation: the variables move in opposite directions. as one variable decreases, the other one increases and vice versa

• Correlation is limited because it tells us little about cause and effect.

  • There are cases where variables are correlated because one causes the other, but another there could be a confounding variable causing it.

• Illusory correlations: false correlations that occur when people believe that relationships exist between two things when no such relationship exists.

Causality: Conducting Experiments and Using the Data

• In order to conduct an experiment, a researcher must have a specific hypothesis to be tested.

  • Hypotheses can be formulated either through direct observation of the real world or after.

• The most basic experimental design involves two groups: the experimental group and the control group.

  • The two groups must be the same except one undergoes experimental manipulation.

  • Experimental group:  the group that receives the experimental manipulation (the treatment or variable being tested)

  • Control group: the group that doesn’t receive the experimental manipulation.

  • Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation.

• Operational definition: a description of how the researcher will measure their variables; helps other researchers interpret the data and repeat the experiment.

• Single-blind study: one of the groups of participants are unaware which group they’re in (experiment or control) but the researcher knows which participants are in each group.

• Double-blind study: both the researchers and the participants are unaware of which participants are in which group; helps to avid the placebo effect

• Placebo effect: when people's expectations or beliefs influence or determine their experience in a given situation; expecting something to happen can actually make it happen.

• Independent variable: the variable being manipulated or controlled by the experimenter

• Dependent variable: the variable the researcher measures to see how much effect the independent variable had.

• Participants: the subjects of psychological research and actively participate in the process.

• Random sample: a subset of a larger population in which every member of the population has an equal chance of being selected; preferred because if the sample is large enough there’s a good chance that the participants are representative of the larger population.

• Random assignment: participants are randomly assigned to either the experimental or control group; participants have an equal chance of being assigned to either group.

• Statistical analysis: determines how likely any difference found between the two variables is due to chance (how meaningful are the differences between the two groups?).

• Reliability: the ability to consistently produce a given result.

  • Having consistent measurements doesn’t mean that you’ve measured something correctly.

• Validity: the extent to which a given instrument or tool accurately measures what it’s supposed to measure.

  • All valid measurements are reliable.

2.4 Ethics

Research Involving Human Participants

• Experiments involving the participation of human subjects undergoes strict guidelines to ensure that the experiment doesn’t harm the subjects.

  • Institutional review board (IRB): a committee of individuals that review proposals for research that involves human participants; their approval is required in order for the experiment to proceed.

  • Each participant must sign an informed consent form before they can participate in the experiment.

• Deception: purposely misleading experiment participants to maintain the integrity of the experiment

  • The deception in these cases can’t be harmful and the participants must be fully briefed at the conclusion of the experiment.

Research Involving Animal Subjects

• Since animals and humans undergo many similar basic processes, animals are acceptable substitutes for research that would be considered unethical in human participants.

• Researchers must design their experiments to minimize any pain or distress experienced by animals serving as research subjects.

• Institutional Animal Care and Use Committee (IACUC): a committee of individuals that review experimental proposals proposals involving animals and require the humane treatment of animal research subjects

  • No animal research project can proceed without the committee’s approval.