Chapter 2: The Research Enterprise in Psychology

Empiricism: How to Know Stuff

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Empiricism is the belief that the best way to understand the world is to observe it firsthand. It is only in the past few centuries that people have begun to systematically collect and evaluate evidence to test the accuracy of their beliefs about the world.

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• Observation requires a method

THE SCIENTIFIC PROCESS

1. Identify a question (what do we want to learn about?)

2. Form a hypothesis (what is our specific prediction?)

3. Gather information

4. Analyze the data (what can we conclude?)

THE SCIENTIFIC METHOD

1. Make observations → collecting qualitative and quantitative data

2. Use inductive reasoning (making generalizations from repeated observations)

3. Forming hypotheses

4. Testing hypotheses

• Making observations includes collecting qualitative and quantitative data, qualitative data is descriptions and quantitative data is recorded measurements

• Data that has been confirmed through repeated observation or experimentations are facts

• A hypothesis is a proposed explanation for a set of observations based on the available data and guided by inductive reasoning. A theory is a principle formed to explaining things already shown in data and is supported by evidence

• Use deductive reasoning to make predictions from hypotheses that are testable and falsifiable through observation and experimentation

• Controlled experiments compare an experimental and control group to differentiate between correlation and causation

• A good theory organizes information in a meaningful way, is testable, is supported by research and conforms to the Law of parsimony

LAW OF PARSIMONY

• The scientific principle that things are usually connected or behave in the simplest or most economical way, especially with reference to alternative evolutionary pathways.

• The parsimony principle, also known as Occam's razor, states that when there are multiple explanations for observed data, the simplest one is preferred. It is a universal feature in science that guides decision-making processes by favoring simplicity in explanations.

HUMANS ARE COMPLEX, VARIABLE, AND REACTIVE

• The methods of psychology are special because human beings are more complex, variable, and reactive than almost anything else that scientists study

• It can be difficult to study unobservable mental processes

• Humans are complex, like for example we have 500 million neurons in the brain

• There’s variability because every person is different

• Reactivity → reactions differ based on or the lack of observation

Methods of Observation: Discovering What People Do

MEASUREMENT

Define the Property → Detect the Property

• Measurement involves: Defining a property in measurable terms and then using a device that can detect that property

• Operational definition is a description of a property in measurable terms eg. defining happiness as the amount of dopamine in the brain or smiles per hour

• There needs to be a detector— an instrument or device— that can detect the property just defined (eg. carbon electrode to detect dopamine)

• Construct validity is a feature of operational definitions whose specified operations are generally considered good indicators of the specified properties

• A good detector has power (the ability to detect the presence of differences or changes in the magnitude of a property), and reliability (the ability to detect the absence of differences or changes in the magnitude of a property)

• Observer bias is the tendency of observers’ expectations to influence both what they believe they observed and what they actually observed → essentially seeing what you expect, seeing what you want to see, because expectations can influence observations and lead you to be blind to that which contradicts your expectations (we all want to be right)

DEMAND CHARACTERISTICS

• Demand characteristics are the aspects of an observational setting that cause people to behave as they think someone else wants or expects _→ Societal Pressure (expectations, fear of offending someone, reputation)

Avoiding demand characteristics:

• Naturalistic Observation is a technique for gathering information by unobtrusively observing people in their natural environments.
  Limits include: experimenter cannot give informed consent of observation, makes it difficult to study many things eg. things that people do rarely, and it requires long periods of observations to get a single measure of a desired behaviour

• Privacy and Control → people are less likely to be influenced by demand characteristics when they can’t be identified as the authors of their actions and psychologists often take advantage of this fact by allowing participants in their studies to respond privately

• Unawareness is one of the best ways to avoid demand characteristics is to make sure that the people who are being observed are unaware of the true purpose of the observation (people can’t try to behave how they think they should when they don’t know how they should behave)

• Double-blind Study is a study in which neither the researcher nor the participant knows how the participants are expected to behave

• Random Assignment → Using a random event to assign people to the experimental or control group

POPULATION AND SAMPLE

• Population is a complete collection of people

• Sample is a partial collection of people drawn from a population

• A Representative Sample possesses the important characteristics of the population in the same proportions. Data from a representative sample are more likely to generalize to the larger population than data from an unrepresentative sample

• Random Sampling is a technique for choosing participants that ensures that every member of a population has an equal chance of being included in the sample

Methods of Observation: Discovering Why People Do What They Do

TYPES OF STUDIES

• Descriptive Research → Describe behaviour in nature (case studies, surveys, naturalistic observations)

• Case Studies are a method of gathering scientific knowledge by studying a single individual, it is not generalizable but important for testing particular theories and/or exceptional cases

• Correlational Research → Looks for relationships between variables (cannot tell if variables have a causal relationship)

• Experimental Research → The only wat to truly infer causality is to develop an experiment, an experiment is a technique for establishing the causal relationship between variables. Experiments allow researchers to determine the causal relationship between two variables, can tell if variable of A causes variable B — BUT it requires strict control of conditions to determine causation.

CORRELATION IS NOT CAUSATION

• Correlation compares the pattern of variation in a series of measurements between variables

• The strength of Correlations is denoted by the letter ‘r’. it indicates how related two variables are

• Perfect Correlations → The change in one variable is exactly proportional to the change in the other variable (r = +1 or -1)

• Positive Correlations → An increase in one variable relates to an increase in the other, or a decrease in one variable relates to a decrease in the other (r is greater than 0 and less or equivalent to +1)

• Negative Correlations → An increase in one variable relates to a decrease in the other (r is greater or equivalent to -1 and less than 0)

• With correlations you can make knowledgeable predictions about the future/past. it can also give you an idea on which variables to use in an experiment to determine causality, and it can also be use to study things where the manipulation of variables is impossible

• The Third Variable Problem → Two variables may be correlated to one another but only because both are causally related to a third variable

VARIABLES

• Variable → a property whose value can change across individuals and over time

• Independent Variable → manipulated in an experiment

• Dependent Variable → measured in an experiment

TYPE I AND TYPE II ERRORS

• Type I Error → When researchers conclude that there is a casual relationship between two variables when in fact there is not (false positive/flukes)

• Type II Errors → When researchers conclude that there is not a causal relationship between two variables when in fact there is (false negative/flunk)

Examining Data (Statistics):

DESCRIPTIVE STATISTICS

• Central Tendency → The value of measurements near the center/midpoint of a distribution

• Variability → How much measurements differ from one another

DESCRIPTIONS OF CENTRAL TENDENCY

• Mean → Value of the most frequently observed measurement

• Median → Average value of all measurements

• Mode → Value in the middle of the distribution

VARIABILITY

• Range → largest measurement - smallest

• Standard deviation → average difference between the measurements in a frequency distribution and the mean of that distribution

DESCRIBING DATA

• Graphical representation of data is quick and efficient

Frequency distributions

• Histograms

• Box Plots

NORMAL DISTRIBUTION

• Bell Curve

• Symmetrical

• Central Peak

• Tails off to both ends

Skewed Distributions

• Positive → right

• Negative → left

Thinking Critically about Evidence

SIGNIFICANT RESULTS

• Inferential statistics → Tests the significance of differences between groups to see if the effect we are observing is meaningful

• Results are meaningless unless you can report that you are 95% sure that random assignment has not failed

• p < 0.05 → probability that random assignment failed and that the results can be attributed to some other variable (chance) is less than 5%

• Null Hypothesis → Any observed differences between the samples are due to chance (assume this is true until rejected by statistically significant results)

• Internal Validity → results worked out, p < 0.05 → characteristics of an experiment that establish the casual relationship between variables

• External Validity → Experimental property where variables have been operationally defined in a normal, typical, or realistic way → used to draw broader conclusions

• Always think critically about claims. Always.

SCIENCE

• What makes science different from most other human enterprises is that scientists actively seek to discover and remedy their mistakes.

• Scientists are constantly striving to make their observations more accurate and their reasoning more rigorous, and they invite anyone and everyone to examine their evidence and challenge their conclusions.

• Science is the ultimate democracy in which the lowliest nobody can triumph over the most celebrated somebody.

The Ethics of Science: Doing What is Right

• There are strict ethical laws for performing experiments on both people and animals

• Scientists must show respect for people, animals, and the truth

ETHICAL CONSIDERATIONS OF THE AMERICAN PSYCHOLOGICAL ASSOCIATION (APA)

• Informed consent → Agree to risks and benefits

• Freedom from coercion → Cannot be forced to participate

• Protection from harm → Protect their participants from physical or psychological harm

• With humans

  • Debriefing → if there is deception during or before an experiment, at the end they must be told the purpose of the study and be informed of the deception

  • Confidentiality → Private/personal info kept confidential

• With Animals

  • must be trained in research methods and experienced in the care of laboratory animals

  • must minimize discomfort, infection, illness, and pain of animals (animals can only be subjected to pain if no alternative procedures are available)

  • The study MUST show significant benefit to society for these works to be approved

  • Must perform all surgical procedures under proper anesthesia and must minimize animal’s pain during and after surgery