Psychology: Approaches, Research Methods, and Statistics Notes

Empiricism and Approaches

  • empiricism: the idea that knowledge comes from experience, and that observation and experimentation enable scientific knowledge.

Major Psychological Perspectives and Subfields

  • behaviorism: the view that psychology (1) should be an objective science that (2) studies behavior without reference to mental processes. Most psychologists today agree with (1) but not with (2).
  • humanistic psychology: a historically significant perspective that emphasized human growth potential.
  • cognitive psychology: the study of mental processes, such as occur when we perceive, learn, remember, think, communicate, and solve problems.
  • psychodynamic psychology: a branch of psychology that studies how unconscious drives and conflicts influence behavior and uses that information to treat people with psychological disorders.
  • social-cultural psychology: the study of how situations and cultures affect our behavior and thinking.
  • social psychology: the scientific study of how we think about, influence, and relate to one another.
  • industrial-organizational (I/O) psychology: the application of psychological concepts and methods to optimizing human behavior in workplaces.
  • human factors psychology: a field allied with I/O psychology that explores how people and machines interact and how machines and physical environments can be made safe and easy to use.
  • biological psychology: the scientific study of the links between biological (genetic, neural, hormonal) and psychological processes.
    • note: Some biological psychologists call themselves behavioral neuroscientists, neuropsychologists, behavioral geneticists, physiological psychologists, or biopsychologists.
  • evolutionary psychology: the study of the evolution of behavior and the mind, using principles of natural selection.
  • positive psychology: the scientific study of human flourishing, with the goals of discovering and promoting strengths and virtues that help individuals and communities to thrive.
  • (general psychology): psychology as the science of behavior and mental processes.

Additional Organizing Concepts in Psychology

  • psychodynamic vs. other approaches: emphasizes unconscious drives and conflicts as influencers of behavior and as a basis for treatment.
  • overarching aim across perspectives: to explain, predict, and improve human behavior and mental processes.

Key Theoretical Terms

  • theory: an explanation using an integrated set of principles that organizes observations and predicts behaviors or events.
  • hypothesis: a testable prediction, often implied by a theory.
  • operational definition: a carefully worded statement of the exact procedures (operations) used in a research study. Example: human intelligence may be operationally defined as what an intelligence test measures.

Research Methods and Foundational Concepts

  • replication: repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding can be reproduced.
  • case study: a descriptive technique in which one individual or group is studied in depth in the hope of revealing universal principles.
  • naturalistic observation: a descriptive technique of observing and recording behavior in naturally occurring situations without trying to manipulate or control the situation.
  • survey: a descriptive technique for obtaining the self-reported attitudes or behaviors of a particular group, usually by questioning a representative, random sample of the group.
  • sampling bias: a flawed sampling process that produces an unrepresentative sample.
  • population: all those in a group being studied, from which samples may be drawn. Note: Except for some national studies, this does not refer to a country’s whole population.
  • random sample: a sample that fairly represents a population because each member has an equal chance of inclusion.

Correlation and Causation Basics

  • correlation: a measure of the extent to which two factors vary together, and thus of how well either factor predicts the other.
  • correlation coefficient: a statistical index of the relationship between two things (from $-1.00$ to $+1.00$).
  • variable: anything that can vary and is feasible and ethical to measure.
  • scatterplot: a graphed cluster of dots, each of which represents the values of two variables. The slope of the points suggests the direction of the relationship between the two variables. The amount of scatter suggests the strength of the correlation (little scatter indicates high correlation).
  • illusory correlation: perceiving a relationship where none exists, or perceiving a stronger-than-actual relationship.
  • regression toward the mean: the tendency for extreme or unusual scores or events to fall back (regress) toward the average.

Experimental Design and Key Concepts

  • experiment: a research method in which an investigator manipulates one or more factors (independent variables) to observe the effect on some behavior or mental process (the dependent variable). By random assignment of participants, the experimenter aims to control for other relevant factors.
  • experimental group: in an experiment, the group exposed to the treatment, that is, to one version of the independent variable.
  • control group: in an experiment, the group not exposed to the treatment; contrasts with the experimental group and serves as a comparison for evaluating the effect of the treatment.
  • random assignment: assigning participants to experimental and control groups by chance, thus minimizing preexisting differences between the different groups.
  • double-blind procedure: an experimental procedure in which both the research participants and the research staff are ignorant (blind) about whether the research participants have received the treatment or a placebo.
  • placebo effect: experimental results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition, which the recipient assumes is an active agent.
  • confounding variable: a factor other than the factor being studied that might influence a study's results.
  • dependent variable: in an experiment, the outcome that is measured; the variable that may change when the independent variable is manipulated.
  • independent variable: in an experiment, the factor that is manipulated; the variable whose effect is being studied.
  • validity: the extent to which a test or experiment measures or predicts what it is supposed to.

Ethics and Participant Rights

  • informed consent: giving potential participants enough information about a study to enable them to choose whether they wish to participate.
  • debriefing: the postexperimental explanation of a study, including its purpose and any deceptions, to its participants.

Descriptive and Inferential Statistics

  • descriptive statistics: numerical data used to measure and describe characteristics of groups. Includes measures of central tendency and measures of variation.
  • histogram: a bar graph depicting a frequency distribution.
  • mode: the most frequently occurring score(s) in a distribution.
  • mean: the arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores.
  • median: the middle score in a distribution; half the scores are above it and half are below it.
  • skewed distribution: a representation of scores that lack symmetry around their average value.
  • range: the difference between the highest and lowest scores in a distribution.
  • standard deviation: a computed measure of how much scores vary around the mean score, often denoted as $s$ or $SD$.
  • normal curve (normal distribution): a symmetrical, bell-shaped curve that describes the distribution of many types of data; most scores fall near the mean (about $68\%$ fall within one standard deviation of it) and fewer near the extremes.

Inferential Statistics and Significance

  • inferential statistics: numerical data that allow one to generalize to infer from sample data the probability of something being true of a population.
  • statistical significance: a statistical statement of how likely it is that an obtained result occurred by chance.

Special Topics and Common Research Criteria

  • falsifiable (hypothesis): it must at least in principle be possible to make an observation that would disprove the hypothesis.
  • bimodal distribution: a distribution characterized by two distinct peaks, indicating subgroups with different characteristics.
  • convenience sampling: using respondents who are “convenient” to the researcher. There is no pattern in acquiring these respondents—they may be recruited by approaching people who are present in a location.
  • generalizability: a measure of how useful the results of a study are for a broader group of people or situations.
  • social desirability bias: a response bias where survey respondents provide answers according to society's expectations rather than their own beliefs or experiences.
  • qualitative research: a method that produces descriptive (non-numerical) data, such as observations of behavior or personal accounts of experiences.
  • quantitative research: the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.
  • Likert scales: a rating scale used to measure opinions, attitudes, or behaviors; consists of a statement followed by five or seven response options.
  • peer review: a quality control process used by publications to ensure that only high-quality, methodologically sound information is presented.
  • effect sizes: measures the strength of the relationship between two variables on a numeric scale. The larger the effect size, the more practical significance.
  • informed assent: the process whereby minors may agree to participate in clinical trials.

Quick reference formulas (highlighted for study use)

  • Correlation coefficient range: −1.000≤r≤1.000-1.000 \le r \le 1.000
  • Normal distribution characteristic: approximately 68%68\% of scores fall within ±1σ\pm 1\sigma of the mean.
  • Standard deviation (sample): s=1n−1∑<em>i=1n(x</em>i−xˉ)2s = \sqrt{\dfrac{1}{n-1} \sum<em>{i=1}^n (x</em>i - \bar{x})^2}
  • Range: Range=max⁡(x)−min⁡(x)\text{Range} = \max(x) - \min(x)
  • Descriptive statistics: central tendency includes mean=1n∑<em>i=1nx</em>i\text{mean} = \dfrac{1}{n} \sum<em>{i=1}^n x</em>i, median=middle value\text{median} = \text{middle value}, mode=most frequent value\text{mode} = \text{most frequent value}
  • Descriptive distribution shapes: bimodal, skewed, normal, etc.