Psychology Chapter 2 PDF

Chapter 2 Studying behaviour scientifically Psychology, The Science of Mind and Behaviour, 4e © McGraw-Hill Education Scientific Attitudes That which can be asserted without evidence, can be dismissed without evidence – Christopher Hitche...

Chapter 2 Studying behaviour scientifically Psychology, The Science of Mind and Behaviour, 4e © McGraw-Hill Education Scientific Attitudes That which can be asserted without evidence, can be dismissed without evidence – Christopher Hitchens We are all scientists in our everyday lives Curiosity of human nature Develop explanations and test them out Evidence-based practice the psychologist is primarily a scientist a careful, measured scientific approach that informs their professional activities in an evidence-based approach preference for interventions that have evidence to support their use © McGraw-Hill Education Steps in the Scientific Process 1. Curiosity - Identify a question of interest News events, scientific articles, personal experiences, etc. 2. Gather information and form a hypothesis Studies, theories and existing information Hypothesis: a specific prediction about some phenomenon Often an “if-then” statement 3. Test hypothesis by conducting research… © McGraw-Hill Education Steps in the Scientific Process (cont’d) 4. Analyse data, draw tentative conclusions 5. Report findings to scientific community peer reviewed journals 6. Further research and theory building 7. New hypothesis derived from theory Theory: a set of formal statements that explains how and why certain events are related to one another. © McGraw-Hill Education Steps in the Scientific Process Figure 2.2 © McGraw-Hill Education Understanding Behaviour ‘Life is lived forwards, but understood backwards’. - Søren Kierkegaard Hindsight (After-the-Fact): - Reasoning after a conclusion has been drawn - Most common method of understanding behaviour - Limitation: past events can be explained in multiple ways - Strength: useful for providing insight and ideas for further scientific study © McGraw-Hill Education Understanding Behaviour Prediction, control, and theory-building Characteristics of a good theory: Incorporates existing material within broad framework & organizes information in a meaningful way Testable and generates new hypotheses Supported by the findings of new research Conforms to Law of Parsimony: simpler is better Theories are not absolute truth Prediction does not require understanding © McGraw-Hill Education Defining and Measuring Variables Variable - any characteristic or factor that can vary: e.g. gender, weight, age, typing speed Operational Definition: defines a variable in terms of the specific procedures used to produce or measure it © McGraw-Hill Education Defining and Measuring Variables Measuring Techniques: Self-report measures: people report their own attitudes, feelings, and behaviours Social Desirability Bias: the tendency to respond in a socially acceptable manner rather than according to how one truly feels or behaves Reports made by others (parents, teachers, friends) Measurement of overt (directly visible) behaviour Coding systems are developed to increase the reliability of measurements © McGraw-Hill Education Defining and Measuring Variables Measuring Techniques continued: Unobtrusive measures: record behaviour in a way that keeps participants unaware that they are being observed Archival methods: utilize records or documents that already exist © McGraw-Hill Education Defining and Measuring Variables Measuring Techniques continued: Psychological tests: questionnaires or performance tasks Personality tests, intelligence tests, neuropsychological tests Physiological measures Heart rate, blood pressure, brain processes, etc. © McGraw-Hill Education Ethical Principles in Research Safe-guarding: Scientists must weigh possible gains in knowledge against the potential risks to research participants Professional bodies adopt principles of: Competence: maintaining high levels of training Responsibility: performing duties with care Integrity: being honest and accurate Respect: respecting participants’ dignity, confidentiality and self-determination. © McGraw-Hill Education Ethical Principles in Research Human Research Standards: Informed Consent: before people agree to participate in research, they should be informed about: Purpose and procedures Potential risks and benefits Right to decline or withdraw participation without penalty Whether responses will be confidential and how privacy will be safeguarded If study involves vulnerable people – consent must be given from parents/ carers/doctors © McGraw-Hill Education Ethical Principles in Research Distress, Stigma, and Harm Participants should not be made to feel bad in any way Not distressed Not feel stigmatized (e.g., singled out for not participating) Not harmed Deception can be used when no feasible alternative is available Must be disclosed during debriefing © McGraw-Hill Education Ethical Principles in Research Privacy and Confidentiality Those who take part in research should be able to do so with the assurance that their information will be kept private Anonymity Identified by number not name Debriefing explained the background to the research return the participant to the state they were in at the start of the procedure © McGraw-Hill Education Ethical Principles in Research Animal Research Standards: Humane treatment Importance of research must outweigh risks Animal research is highly controversial International Fund for Animal Welfare (IFAW) Animal research must be approved by panel Healthy, psychologically sound animal is more likely to behave normally. © McGraw-Hill Education Methods of Research: Descriptive Descriptive research: seeks to identify how humans and other animals behave, particularly in natural settings Case studies: an in-depth analysis of an individual, group, or event Advantages: Researchers obtain in-depth, detailed information New ideas or challenge existing theories Limitations: Cannot determine cause-effect relationships Difficult to generalize findings Lack of objectivity in gathering and interpreting data © McGraw-Hill Education Methods of Research: Descriptive Naturalistic observation: the researcher observes behaviour as it occurs in a natural setting, and attempts to avoid influencing that behaviour Habituation: the process in which people and other animals typically adapt to and ignore the presence of an observer as time passes Advantages: Behaviour can be observed in natural settings Rich descriptions of behaviour Limitations: Cannot establish a causal relationship Potential bias in researcher’s interpretation of observation © McGraw-Hill Education Methods of Research: Descriptive Survey research: information about a topic is obtained by administering questionnaires or interviews to many people Population: consists of all the individuals that we are interested in drawing a conclusion about Sample: a subset of individuals drawn from the larger population A representative sample is one that reflects the important characteristics of the population © McGraw-Hill Education Methods of Research: Descriptive Types of Sampling: Random Sampling: a procedure in which every member of the population has an equal probability of being chosen to participate in the survey Stratified Random Sampling: a procedure in which the population is divided into subgroups, and sample participants are chosen to correspond with the population percentages © McGraw-Hill Education Methods of Research: Descriptive Figure 2.8 © McGraw-Hill Education Methods of Research: Descriptive Survey Research (continued): Advantages: Can collect large amounts of information quickly and inexpensively Can ask about an almost limitless variety of attitudes and behaviours Limitations: Unrepresentative samples can produce distorted results Cannot indicate causation Self-reports can be biased © McGraw-Hill Education Methods of Research: Correlational Correlational Research: In its simplest form it has three components: Researcher measures one variable (X) Researcher measures a second variable (Y) Researcher statistically determines whether (X) and (Y) are related © McGraw-Hill Education Methods of Research: Correlational Involves measuring variables, not manipulating them Correlation does not equal causation Some interpretive possibilities: X caused Y Y caused X Both variables influenced each other (bidirectionality) A third variable influenced both X and Y (spurious) © McGraw-Hill Education  Methods of Research: Correlational Figure 2.9 © McGraw-Hill Education Methods of Research: Correlational Correlation Coefficient: a statistic that indicates the direction and strength of the relation between two variables (between +1.00 to -1.00) Positive Correlation: higher scores on one variable are associated with higher scores on a second variable Negative Correlation: higher scores on one variable are associated with lower scores on a second variable © McGraw-Hill Education Methods of Research: Correlational Figure 2.10 Scatterplot: a graph that shows the correlation between two variables Direction of relationship: positive or negative Strength of relationship: the closer the correlation coefficient gets to 1 (+ or -), the stronger the relationship © McGraw-Hill Education Methods of Research: Correlational Advantages of correlational research: Can establish generalization outside the laboratory Can generate ideas for further laboratory study Allows the examination of variables that may not be practical or ethical to study in the laboratory Allows researchers to make predictions © McGraw-Hill Education Methods of Research: Experiments Experiments: Can be used to examine cause-and-effect relationships Three characteristics: 1.Researcher manipulates (controls) one or more variables 2.Researcher measures whether this manipulation influences other variables 3.Researcher attempts to control extraneous factors that might influence the outcome of the experiment © McGraw-Hill Education  Methods of Research: Experiments Figure 2.12 © McGraw-Hill Education Methods of Research: Experiments Independent Variable (IV) the factor that is manipulated or controlled by the experimenter Dependent Variable (DV) the factor that is measured by the experimenter and that may be influenced by the independent variable Experimental Group the group that receives a treatment or an active level of the IV Control Group the group that is not exposed to the treatment or receives a zero-level of the IV © McGraw-Hill Education Methods of Research: Experiments Random Assignment: each participant has an equal likelihood of being assigned to any one group within an experiment Groups are equal (in general, on average) Alternately, all participants could be exposed to all conditions of the independent variable Counterbalancing: a procedure in which the order of conditions is varied so that no condition has an overall advantage relative to the others © McGraw-Hill Education Methods of Research: Qualitative Analysis of words in discussions and interviews Analysis of images in books or videos Subjective approach – both strength and weakness Validity is questioned Interviews, questionnaires, focus groups, analysis of text © McGraw-Hill Education Methods of Research: Mixed Methods Use of quantitative and qualitative designs Example: an experiment plus an interview Experiment plus a focus group Experiment plus a structured interview of participants No one approach is better than another There is more than one way to address a research question © McGraw-Hill Education Overview of Research Methods © McGraw-Hill Education Threats to Validity Internal Validity: the degree to which an experiment supports clear causal conclusions Confounding Variables: two variables are intertwined in such a way that we cannot determine which one has influenced a dependent variable © McGraw-Hill Education Threats to Validity Placebo: a substance that has no pharmacological effect Placebo Effect: people receiving a treatment show a change in behaviour because of their expectations, not because the treatment itself had any specific benefit Figure 2.14 © McGraw-Hill Education Threats to Validity Demand Characteristics: cues that participants pick up about the hypothesis of the study and how they are meant to behave Experimenter Expectancy Effects: the subtle and unintentional ways researchers influence their participants to respond in a manner that is consistent with the researcher’s hypothesis Double-Blind Procedure: both the participant and experimenter are kept blind as to which experimental condition the participant is in Minimizes both placebo effects and experimenter expectancy effects © McGraw-Hill Education Threats to Validity Replicating & Generalizing the Findings: External Validity: the degree to which the results of a study can be generalized to other populations, settings, and conditions Replication: the process of repeating a study to determine whether the original findings can be duplicated Cross-cultural replication Currently a replication crisis in psychology © McGraw-Hill Education Science, psychics, and the paranormal Paranormal experiences Those that conflict with the ‘basic limiting principles’ of science We should apply rigorous standards of evaluating psychic phenomena Replication is important We must rule out presently known natural physical or psychological explanations © McGraw-Hill Education Science, psychics, and the paranormal Ganzfeld procedure A participant (the ‘receiver’) listens to a hissing sound played through earphones and sees red light through translucent goggles In another shielded room, the ‘sender’ concentrates on one of four different visual forms presented in random order Some claims of significant high number of correct items reported © McGraw-Hill Education Science, psychics, and the paranormal The original ganzfeld studies may not have fully prevented the receivers from detecting extremely subtle cues that could have influenced their responses Milton and Wiseman (1999) analyzed 30 ganzfeld studies and concluded that ‘the ganzfeld technique does not at present offer a replicable method for producing ESP in the laboratory’ © McGraw-Hill Education Analysing and Interpreting Data “47% of statistics are made up on the spot” – Steven Wright Statistics can be misleading The better informed we are as to how statistics may be used and abused, the less likely to be swindled and fooled by companies, charlatans and even governments © McGraw-Hill Education Analysing and Interpreting Data Descriptive Statistics: statistics summarize and describe the characteristics of a set (or distribution) of data Measures of Central Tendency: ‘what is the typical score?’ Mode: the most frequently occurring score in a distribution Median: the point that divides a distribution of scores in half when those scores are arranged in order from lowest to highest Mean: the arithmetic average of a set of scores © McGraw-Hill Education Analysing and Interpreting Data Measures of Variability: statistics that capture the degree of variation, or spread, in a distribution of scores Range: the difference between the highest and lowest scores in a distribution Standard Deviation: takes into account how much each score in a distribution differs from the mean © McGraw-Hill Education Analysing and Interpreting Data Inferential Statistics tell us how confident we can be in making inferences about a population based on findings obtained from a sample Statistical significance means that it is very unlikely that a particular finding occurred by chance alone Meta-Analysis: a statistical procedure for combining the results of different studies that examine the same topic Limited by ‘file-drawer’ problem © McGraw-Hill Education Critical Thinking in Everyday Life Pseudoscientific Misinformation – nonsense and jargon made to sound scientific Importance of healthy scepticism & balanced open-mindedness Consider quality of evidence and other plausible explanations © McGraw-Hill Education