PSY144 Exam 3 Study Guide PDF

Exam 3 is on 12/19 at 11 am Introduction & Scientific Psychology (Use Ch 1 | 1_Notes) - Falsifiability: Definition and significance in psychological research, evidence that can be used against the claim - Basic Research: Research conducted for the purpose of achieving a more detailed a...

Exam 3 is on 12/19 at 11 am Introduction & Scientific Psychology (Use Ch 1 | 1_Notes) - Falsifiability: Definition and significance in psychological research, evidence that can be used against the claim - Basic Research: Research conducted for the purpose of achieving a more detailed and accurate understanding of human behavior, not trying to address a specific issue - Applied Research: Research conducted to address a practical problem Presenting Research (Use Ch 11 | 2_Notes) - Title page. First page of the paper presents the article title and author names and affiliations. - Abstract. Second page of the paper summarizes the research. - Introduction. Describes previous research and the rationale for the current study. - Method. Describes how the study was conducted. - Results. Describes the results of the study. - Discussion. Summarizes the study and discusses its implications. - References. Lists the references cited throughout the article. - Article: Scruton, R. (1996). The eclipse of listening. The New Criterion, 15(3), 5–13. - Book Chapter: Armstrong, D. (2019). Malory and character. In M. G. Leitch & C. J. Rushton (Eds.), A new companion to Malory (pp. 144-163). D. S. Brewer. - Book: Stoneman, R. (2008). Alexander the Great: A life in legend. Yale University Press. Research Basics & Theories (Use Ch 2 & Ch 4 | 3_notes) Types of variables - Independent Variable: Variables that are manipulated/controlled by the researcher to determine their effect on the dependent variable Ex. Sleep study, how does sleep affect cognitive performance, the number of hours sleeping is being examined, not measured - Dependent Variable: Variables that are measured to see if they change due to the manipulation of the independent variable Ex. Sleep study, how does sleep affect cognitive performance, cognitive performance is being measured based on the number of hours slept - Mediator/Mediating Variable: Variables that explain the relationship between the IV and DV Ex. Exercise and happiness study, endorphin levels could be a mediating variable that explains why exercise increases happiness - Moderator/Moderating Variable: Variables that affect the strength/direction of the relationship between an IV and DV, mediate Ex. Exercise and happiness study, age could be a moderating variable if the effect of exercise on happiness varies by age group, modify/change - Confounding Variable: Variables the researcher failed to control/eliminate that affect the results of the variables being studied Ex. Teaching method study, student’s prior knowledge could affect their performance Variable classification - Quantitative: Continuous and discrete - Continuous Variables: Variables that can take on an infinite number of values within a range Ex. Response time in a cognitive task, time, height, weight, or temperature can be measured Exam #3 - PSYCH 144 - Discrete Variables: Quantitative variables that can only take on specific, separate values, they represent counts or measurements where fractions or decimals are not meaningful Ex. Number of children in a family - Dummy/Dichotomous: A form of categorical variable that can be used in analyses that require continuous variables Ex. Presence/absence of a symptom Population and sampling - Population: A large group of people - Sample: A smaller group of the large group used to more easily study/generalize the population - Convenience Sampling: Participants are chosen on availability, may lead to unrepresentative samples Ex. Taking a sample from a specific major at a college and not other majors - Random Sampling: Every member of the population has an equal chance of being selected, less biased results Ex. Randomly selecting participants from a college - Operational Definition: How a concept or term is going to be defined/measured in practice - Correlation: Clarifies relationships, does not predict or imply causation Ex. Study may find a correlation between ice cream sales and crime rates but it doesn’t mean one causes the other, hot weather could be a 3rd variable - Pearson’s r: Strength of a relationship measured by the closeness of +1 or -1 Differences Between Groups - Group Differences: Statistical differences between two or more groups in terms of their means or other characteristics - Can use SD and mean - Standard Deviation: A measure of the amount of how dispersed the data is in relation to the mean Ex. Low/small deviation = closer to the mean, high/large = more spread out data - Can use t-test and ANOVA - Quantitative data - Bar graphs Basic statistical concepts - Bell curve that describes the distribution of many naturally occurring phenomena, mean (center) and standard deviation (spread) - Mean, median, mode - SD - Cohen’s d: Calculated by taking the difference between the means of two groups and dividing by the SD of the groups, form of an effect size, used to examine group differences - Effect sizes help researchers/practitioners understand the practical significance of their findings - Small effect size: ~0.2 - Medium effect size: ~0.5 - Large effect size: ~0.8 Theory and Hypothesis - Theory: A coherent explanation of one or more phenomena, incorporating unobserved variables, structures, or processes Exam #3 - PSYCH 144 - Broaden-and-Build Theory: Positive emotions not only make people feel good in the moment but help expand our awareness/increase thinking and actions - Theory can guide empirical studies which can help prove/disprove the theory - Hypothesis: A prediction based on a theory, tested to validate the theory - Ethics (Use Ch 3 | 4_notes) - Informed Consent: Ensuring participants’ agreement to partake in research after fully understanding its implications - Debriefing: The process of informing research participants as soon as possible of the purpose of the study, revealing misconceptions that might have been a result of participating Survey (Use Ch 9 | 5_notes) - Survey: The broader process of collecting information from a group of people, which often involves distributing and collecting questionnaires, includes a questionnaire, methodology for sampling, data collection, and analysis - Questionnaires: A set of written questions designed to gather information from respondents Simple Random Sampling, Stratified Random Sampling, Cluster Sampling - Simple Random Sampling: Each member of the population has an equal probability of being selected Ex. Putting names of everyone in a sampling frame in a box and picking one randomly - Stratified Random Sampling: Population is first divided into different subgroups or strata and a separate random sample is selected from each stratum Ex. 12.5% of the US is Black, stratified sampling ensures that in a survey of 1,000 Americans, there will be 125 Black respondents to accurately represent the sample - Cluster Sampling: Larger clusters of individuals are sampled first and then individuals are sampled from these clusters Ex. To select a sample of small-town residents, a researcher randomly selects several small towns and then randomly selecting individuals within each town Measurement (Use Ch 5 | 6_notes | 6_activity) - Self-Report Measures: Participants report their own thoughts, feelings, or behaviors Ex. Rosenberg Self-Esteem Scale, participants rate their self-esteem on a scale from 1-5 - Behavioral Measures: Observing and recording behavior to assess psychological variables Ex. Recovering the number of times a person looks away during a conversation to measure social anxiety - Physiological Measures: Recording biological data such as heart rate, blood pressure, or hormone levels Ex. Measuring cortisol levels to assess stress Cronbach’s Alpha - A statistic used to measure internal consistency/how well the items in a test measure the same underlying construct - Ranges from 0 to 1 - 0.70 or higher: Acceptable reliability - 0.80 or higher: Strong reliability - 0.90 or higher: Items may be redundant Exam #3 - PSYCH 144 Validity in Psychological Measurement - Face Validity: Does the test appear to measure what it’s supposed to, at face value? Ex. A math test looks like it measures math ability - Content Validity: Does the test cover the entire range of the construct it aims to measure? Ex. A depression scale covering both emotional and physical symptoms of depression - Criterion Validity: Do the test results relate to another measure that is known to be valid Ex. A new self-esteem scale correlating with scores on the Rosenberg Self-Esteem Scale - Discriminant Validity: Is the test uncorrelated with measures of different constructs? Ex. A self-esteem measure that does not correlate with a measure of anxiety, showing they are distinct - Predictive Validity: Can the test predict future outcomes? Ex. A college entrance exam predicting future academic success Test-Retest Reliability - Consistency of scores over time Ex. Administering the same test to the same people at two different points in time Testing memory recall today and again two weeks later Self-Report Measures - Participants report their own thoughts, feelings, or behaviors - Can be influenced by social desirability bias - It may not always produce reliable data. Experimental research design (Use Ch 6 | 7_notes | 7_activity) - Experiment: An empirical study designed to determine if a causal relationship exists between two variables Ex. Researchers might manipulate the amount of light in a room to see how it affects people’s moods - Independent variable: The variable that is manipulated in an experiment to observe its effect Ex. In a study examining the impact of sleep on cognitive performance, the amount of sleep participants receive is the independent variable - Dependent variable: The outcome that is measured in an experiment Ex. In a study examining the impact of sleep on cognitive performance, score or reaction time is the dependent variable - Manipulation of variables: Researchers actively change the independent variable across conditions Ex. Varying the level of noise (quiet, moderate, loud) in a testing environment to assess its impact on concentration and test scores - Confounding variable: An extraneous variable that varies across conditions and can provide alternative explanations for observed differences Ex. If a study on exercise and weight loss does not control for diet, changes in weight could be attributed to diet rather than exercise - Internal validity: How well a study design supports the conclusion that changes in the independent variable caused changes in the dependent variable Ex. If a study shows that increased sleep leads to improved test scores, and no other variables influenced this relationship, it has high internal validity - External validity: How well a study design supports the conclusion that changes in the independent variable caused changes in the dependent variable Ex. If a study shows that increased sleep leads to improved test scores, and no other variables influenced Exam #3 - PSYCH 144 this relationship, it has high internal validity - Between-subjects design: Each participant experiences only one condition Ex. In a study testing two different teaching methods, one group learns via method A, while another group learns via method B. This design avoids carryover effects but requires random assignment to ensure comparability. - Within-subjects design: Each participant experiences all conditions Ex. In a study on memory recall, participants might be tested on two types of words to see which is remembered better. This design controls for individual differences but may lead to carryover effects. - Control condition: These conditions do not receive the treatment being tested Ex. In a study on the effectiveness of a new medication, one group receives the medication while a control group receives a placebo, which helps identify the treatment’s true effects - Treatment condition: A condition in which participants receive some treatment or intervention Ex. In a study assessing a new therapy for anxiety, the treatment condition would be the group receiving the therapy sessions - Random assignment: Participants are assigned to conditions randomly to control for extraneous variables Ex. Flipping a coin to assign participants to treatment or control groups. Random assignment ensures that groups are similar at the start of the experiment - Counterbalancing: A method to control for carryover effects by varying the order of conditions across participants Ex. If a within-subjects design includes conditions A and B, some participants could experience A followed by B, while others experience B followed by A Descriptive and inferential statistics (Use Ch12 & Ch13 | 8_notes | 8_stat_class_activity | 8_stats_assignment) Distribution types - Unimodal: SIngle peak, common in psychology research Ex. IQ scores centered around an average. - Biomdal: Two distinct peaks Ex. Age distributions with peaks at young and older ages in a mixed-age study Central tendencies - Mean: Best used when data are symmetrical without outliers - Median: Best used when skewed data, provides a midpoint - Mode: Best used when categorical data with a common category Type I and Type II errors - Type I Error: False positive, concluding an effect exists when it does not Ex. Concluding a treatment works when it does not - Type II Error: False negative, missing an effect that does exist Ex. Failing to detect a significant effect in a new teaching method Type of analyses - Independent samples t-test: Compare means of two independent groups Ex. Testing if anxiety levels differ between two therapy groups - Paired-samples t-test (Dependent t-test): Compare two related sample means Ex. Comparing the same students’ scores before and after a study program Exam #3 - PSYCH 144 - One-way ANOVA: Compare more than two group means Ex. Testing stress levels across three different occupational groups - Repeated measures ANOVA: Within-subject design comparison across conditions Ex. Comparing memory recall under three lighting conditions for the same participants - Pearson Correlation: Measures strength and direction of relationship Ex. Examining the relationship between stress and job satisfaction - Simple regression: Predicting one DV based on one IV Ex. Predicting job performance based on years of experience - Chi-Square test: Tests the associations between categorical variables Ex. Testing if gender is associated with program preference Non-experimental research design (Use Ch 7 | 9 _notes | 9_activities) - Experimental: An empirical study designed to determine if a causal relationship exists between two variables Ex. Researchers manipulating the amount of light in a room to see how it affects people’s moods - Non-experimental: Crucial for studying topics in psychology where manipulation of variables or random assignment is either impossible or unethical Ex. Main types of non-experimental research: single-variable research, correlational research, quasi-experimental research, and qualitative research - Single-Variable Research: Focuses on understanding or describing a single variable Ex. Milgram’s obedience study, where only the extent of obedience was measured without comparing it to other variables - Correlational Research: Assesses the statistical relationship between two variables without any manipulation Ex. Appropriate when causation isn’t the focus and when manipulation of the variable is unethical - Quasi-Experimental Research: Involves the manipulation of an independent variable but lacks random assignment to conditions Ex. Used when experimental control is limited by real-world conditions, such as comparing pre-existing groups - Non-equivalent groups: Involves comparing two or more pre-existing groups Ex. Comparing school performance between students in a new after-school program and those in a traditional program - Pretest-Posttest: Measures the dependent variable before and after an intervention Ex. Measuring stress levels before and after a wellness program - Qualitative Research: Uses nonnumerical data to explore experiences, behaviors, or perspectives Ex. Interviews, focus groups, observations Big picutre (Read Ch 14) - Meta-analysis: A set of techniques for finding all the studies that address a particular research question and then combining the results of those studies statistically to see the overall pattern Ex. Identify the research question, find all the research that addresses that question, find or compute the effect size in each study, combine all the effect sizes into a single overall effect size, and test potential moderators of the effect size - Replication crisis: The idea that many results in psychology cannot be replicated and therefore do not reflect real psychological phenomena