Final Exam Review Guide (Chapter 1-12) Flashcards
(132 cards)
1
Q
How to define science?
A
Process of obtaining knowledge through systematic observations, critical thinking, and empirical evidence.
Involves forming hypotheses, conducting experiments, analyzing data, and drawing conclusions based on evidence.
2
Q
What makes cultural transmission so special?
A
Process by which knowledge, customs, and behaviors are passed from one generation to another. This allows humans to preserve solutions, share knowledge, and learn from others whether orally in writing or by observing and modeling behaviors.
3
Q
What is one byproduct of cultural transmission? And can you give examples using modern life?
A
One byproduct of cultural transmission is evolution of prestige. Individuals who possess above-average knowledge or skill are often valued and admired.
Examples: Influencers or thought leaders on social media who gain following because they share valuable knowledge. Professionals are respected for their expertise and become role models.
4
Q
What is so special about symbolism?
A
Ability to abstract physical reality into symbols and have reflective thoughts and communicate with language.
Ability to use symbols to represent ideas or concepts. Allow us to have reflective thought and communicate complex ideas through language, art, and math.
5
Q
What is so special about prosociality?
A
Capacity to be sensitive to other needs and emotions which lead to behaviors like helping, sharing, and cooperating. Plays a role in social bonding and empathy.
6
Q
Why “two heads are better than one”?
A
Highlights the value of collaborative thinking. Working together helps people generate better solutions and broader perspectives than they might individually. Collaboration fosters creativity and problem-solving.
7
Q
What is so special about ancient Greek philosophers?
A
Ancient Greek Philosophers like Plato and Aristotle laid the foundation of critical thinking (practice of evaluating evidence and reasoning logically to reach sound conclusions)
Plato categorized the world into sensible (through our senses) and intelligible (through reasoning).
8
Q
What is critical thinking and how is it relevant to science?
A
Critical thinking is relevant to science because it involves analysis, synthesis, and evaluation of information.
9
Q
When was the birth of modern science?
A
Birth of Modern Science (The Renaissance)
Key People: Descartes, Hume. Galileo, Aristotle
10
Q
Philosophical Underpinnings of Science
A
Plato categorized the world into sensible and intelligible. Galileo used direct observation to prove his heliocentric theory and make points about the universe’s structure.
Descartes (Rationalism) Hume (Empiricism)
11
Q
Inductive Reasoning
A
Reasoning from specific to general
Bottom-Up Approach
12
Q
Deductive Reasoning
A
Reasoning from general to specific.
Science uses both (Inductive reasoning to develop theories and deductive reasoning to test them)
13
Q
What are the basic stages of science?
A
- Personal Experiences/Other Published Empirical Studies. Developing theory/refining general knowledge
- Generate research questions
- Formulate a hypothesis and research plan
- Observation and Analysis
- Making Conclusions and Report Results)
14
Q
Can you list three characteristics of a good research question?
A
Falsifiable (Question is testable)
Clearly Articulated (Even the most innovative idea is useless if it cannot be coherently expressed and conveyed to others)
Grounded in Previous Research and Carries Important Implications
15
Q
Hypothesis
A
Statement that makes a specific prediction about a phenomenon of interest.
16
Q
Theory
A
Explanation of phenomenon based on substantiated evidence.
17
Q
Do Hypothesis and Theories Have to Be Linked?
A
Yes, a hypothesis is derived from a theory. Theories guide predictions.
18
Q
Why do we have to conduct a literature review before formulating a hypothesis?
A
Literature reviews help to understand what is already known, identify gaps in research, and build on existing research.
19
Q
Empirical Article
A
Reports on a scientific study conducted by an author of the article.
20
Q
Theoretical Article
A
Reports on a theory.
21
Q
Review Article
A
Provides a brief or an extensive review of an existing body of empirical and/or theoretical work written on a particular topic.
22
Q
Professional Journals
A
Peer-reviewed, rigorous standards.
23
Q
Predatory Journals
A
Low quality, often pay-to-publish, no proper review
24
Q
Fact
A
Undisputed piece of information based on science.
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Claim of Fact
Statement that may be true but needs evidence.
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Opinion
Subjective belief or interpretation.
27
Can you define a variable?
Variables are any measurable characteristic.
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Dependent Variable
Measured outcome and value predicted by IV.
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Independent Variable
Manipulated by researcher.
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Criterion Variable
Variable being predicted.
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Predictor Variable
Variable that precedes or predicts another variable.
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Extraneous Variables
Any variable that influences DV but is not of interest.
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Confounding Variables
Specific type of extraneous variable that systematically varies with the IV and threatens internal validity.
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Conceptual Hypothesis
Based on abstract ideas but grounded in theory. Referred to as an educated guess or predicting the relationship between a set of variables.
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Operational Hypothesis
Defines how variables are measured. Describes a construct in quantifiable and observable terms.
36
Nominal Scale
Scale that categorizes things or people into two or more categories based on characteristics. Categorizes things
Ex: Gender and Political Affiliation (Men and Women)) (Gender, Type of News)
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Ordinal Scale
Variable measured on an ordinal scale places items or people into categories. Rank order things.
Ex: Rankings and Satisfaction Levels (Rating Scale from 0 to 7)
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Interval Scale
Contains information about order and distance between ranks. Distance between ranks of scale is equal and meaningful. Order and distance between ranks with no true zero.
Ex: Temperature
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Ratio Scale
Contains information about order and distance between ranks. Distance between ranks of scale is equal and meaningful. Contains a true zero representing a true absence of what’s measured. Order, Distance, True Zero
Ex: Frequency and Age
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External Validity
Degree of ability to generalize results to real world and the population of interest. How generalizable findings are to other people.
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Internal Validity
Degree of ability to establish causal relationships. How well study isolates cause and effect relationships.
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Sample Selection
Why is this an important part of the scientific process?
Impacts generalizability (external validity) Helps reduce sampling bias. Ensures representativeness of population.
43
How is content analysis different from the other methods?
Content analysis is a research technique used to systematically analyze content of any meaningful body of communication (verbal, written, pictorial) with the purpose of understanding symbolic meaning making inferences and predictions.
44
What is a construct?
Constructs are abstract ideas.
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What is an operational definition?
Operational definitions are expressed in concrete and measurable terms that can be directly observed and measured.
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What is a coding scheme?
Coding schemes are based on using observable content to obtain measurable data of qualitative constructs and latent content.
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What is a unit of analysis?
The unit of analysis is the primary element or object being studied in a research project. In content analysis, this could be a sentence, paragraph, or an entire article.
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What is a unit of coding?
The unit of coding is the segment of content you categorize or assign codes to using coding scheme. Often smaller than units of analysis.
Ex: Gestures, Images, Word or Phrase
49
What is a unit of sampling?
The unit of sampling refers to items selected from a population for inclusion in analysis. Defines what gets chosen to be analyzed.
Ex: Sample of 100 newspaper articles.
50
What is the link between a coding scheme and scale of measures?
Coding scheme converts qualitative data into quantifiable form by assigning codes. The coding scheme determines how data can be statistically analyzed by defining scale of measurement.
51
What is inter-rater reliability?
Inter-rater reliability assesses degree of agreement between two or more coders who independently assign codes to same content. Ensures consistency and objectivity.
52
How to calculate Inter-Rater Reliability?
Two Most Common Tests (Cohen’s Kappa and Intra-Class Correlations)
Cohen’s Kappa (Used for two raters with categorical data) (Adjusts for agreement that happen by chance)
Intra-class Correlation Coefficient (ICC): Used for continuous or ordinal ratings. Assesses how strongly units in the same group resemble each other. Suitable for more than two raters and interval/ratio data.
53
What is similar between an observational study and a content analysis?
Both are non-experimental, involve systematically recording and coding behaviors, and use predefined codes to interpret data. Data collected is quantitative or qualitative.
54
What is different between an observational study and a content analysis?
Observational Study
Real-Time Behaviors or Interactions
Often in Natural Environments
Observable Actions/Behaviors
Involves observing people directly
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What is different between an observational study and a content analysis?
Content Analysis
Pre-Existing Content
Works with documents or archival records
Communication Patterns, Language, and Themes
Analyze content produced by people
56
What is the strengths of an observational study?
Strengths: Allow research in natural settings or with real-world data. Useful when manipulation is unethical. Provide rich, detailed data. Study both frequency and quality of behaviors. Non-Intrusive Methods
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What is the weakness of an observational study?
Weaknesses: Risk of observer bias cannot establish causality; data may lack context or missing information and can be time-consuming to code and analyze systematically.
58
When would you want to do an observational study?
When wanting to examine natural behaviors. Manipulating variables would be unethical. Studying nonverbal or spontaneous behaviors. Want high ecological validity.
59
What kind of research question would you address with an observational study and content analysis?
Observational Study: Real-Time Behavior, Natural Settings, Nonverbal Behavior, Reactivity, Observer Bias
Content Analysis: Existing Texts/Media; Documents, Social Media, TV; Media Bias, Cultural Trends; Context Loss, Coding Subjectivity.
60
What makes a study a true experiment?
A true experiment includes three critical components. Manipulation (Researcher actively manipulates one or more independent variables) Random Assignment (Participants are randomly assigned to different groups) Control (Experiment includes control of extraneous variables) Establish a cause-and-effect relationship between variables.
61
Can you list all the elements of a true experiment?
Independent Variable (Variable being manipulated) Dependent Variable (Variable being measured) Random Assignment (Ensures individual differences are eliminated) Control Group (Used for comparison) Control of Confounds
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What is unique about an experiment?
Help to demonstrate causality. The controlled setting where variables are manipulated. Use of random assignment reduces biases and confounding variables.
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Between-Subjects Experimental Design
Different participants receive different levels of experimental manipulation. Comparison is between different groups and avoids carryover effects which require more participants.
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Factorial (Experimental) Design
Experiment that includes two or more independent variables with each having multiple levels being tested simultaneously. Tests for main and interaction effects.
Factor A (Drug (Placebo and Drug)) Factor B (Therapy (CBT, No Therapy))
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Main vs Interaction Effects
Main Effect: Individual effect of one IV on DV
Interaction Effect: When the effect of on IV depends on the level of another IV
66
Carryover Effects
Occur in within-subjects design where exposure to one condition influence performance in another. Most common reasons for carryover effects are order and timing between conditions practice and fatigue.
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How to Manage Carryover Effects
- Counterbalancing (Vary conditions across participants)
- Randomization
- Rest Periods (Reduce Fatigue)
68
Mixed Analysis (Experimental)
Combines within subjects and between-subjects variables in the same experiment. One IV is within subjects and another is between subjects.
69
Within-Subjects (Experimental) Design
Each participant receives all levels of the independent variable. Same individuals across conditions with the risk of carryover effects.
70
Quasi-Independent Variable
An independent variable cannot be randomly assigned. Has no random assignment. Between-subjects factor (age, gender) because each participant undergoes one of the levels (male or female).
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Pretest-Posttest Design
Measures participants before and after intervention or treatment. Can be Between-Subjects (Control) and Within-Subjects (Repeated Measure). Helps evaluate change over time and control baseline differences.
72
What makes a study quasi-experimental?
A quasi-experimental study has some but not all features of an experiment. There is no random assignment of participants to groups. Use pre-existing groups and may still involve manipulating the independent variable. Lacks full control of confounding variables.
73
Why are developmental studies are quasi-experimental?
Age cannot be randomly assigned and can’t be manipulated experimentally.
74
Strengths of Quasi-Experimental Studies
Useful for studying real life. Natural development across lifespan.
Ethically and practically appropriate
Observe long-term trends and changes. Less time consuming and less expensive.
75
Weaknesses of Quasi-Experimental Studies
No random assignment (risk of confounding variables)
Hard to infer true causality
May be affected by maturation, testing effects, and dropout.
76
Sequential Design
Combines cross-sectional and longitudinal methods.
This allows researchers to track age-related changes, isolate cohort effects (compare different age groups over time), and compare cohorts at different points.
77
Why are not all studies sequential?
Too time consuming (must follow participants over multiple time periods), Too expensive, Too Complex
78
When is it necessary to conduct sequential study?
When researchers need to identify developmental trends while accounting for generational differences and disentangle age effects from cohort effects.
79
Why do we need to compute descriptive statistics?
Descriptive statistics help us summarize large amounts of data clearly and efficiently. Understand distribution of data. Identify patterns and variability. Choose appropriate statistical tests. Provide foundation for inferential statistics.
80
Central Tendency
Typical or average value. Mean (Average) Median (Middle Value) Mode (Most Frequent) Dispersion (How spread-out values are) (Range, Variance, Standard Deviation, IQR)
81
Central Tendency for Nominal Data
(Mode with no dispersion) (Most common eye color)
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Central Tendency for Ordinal Data
(Median or Mode) (Range or IQR) (Ranks in a Contest)
83
Central Tendency for Interval and Ratio Data
(Mean, Median, Mode) (Standard Deviance, Variance, Range) (Test Scores and Height)
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Bar Chart
Central Tendency
Ex
Nominal or Ordinal Data
Ex: Favorite Color Frequency
85
Histogram
Central Tendency
Ex
Interval/Ratio (Continuous) Data
Ex: Distribution of Test Scores
86
Boxplot
Central Tendency
Ex
Showing Dispersion and Outliers
Ex: Comparing Scores Across Groups
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Scatterplot
Central Tendency
Ex
Showing Correlation/Relationship
Ex: Height vs. Weight
88
Positive Correlation
As one variable increase, so does the other.
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Negative Correlation
As one variable increases the other decreases.
90
What does statistical testing actually test?
Tests the null hypothesis (No difference or no relationship) (P-Value less than 0.05 (Reject Null) Result is statistically significant)
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Type I Error
False Positive
Reject a true null hypothesis.
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Type II Error
False Negative
Fail to reject a false null hypothesis.
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Higher Alpha
More lenient threshold has greater risk of Type I error
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Lower Alpha
Stricter threshold, reduced risk of Type I error but increased risk of Type II error
Lowering Alpha reduces Type I errors but increases Type II errors.
95
Independent Samples T-Test
When to Use?
Ex:
Compare two groups (different people)
Ex: Do males and females differ in math scores?
96
Paired Samples T-Test
When to Use?
Ex:
Compare two conditions within same group
Ex: Do participants score higher before or after training?
97
One-Way ANOVA
When to Use?
Ex:
Compare more than two groups
Ex: Do three teaching methods affect test scores differently?
98
Two-Way ANOVA
When to Use?
Ex:
Compare effects of two IVs and interaction
Ex: Do gender and teaching style both affect exam performance?
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Linear Regressions
Predict one continuous variable from another.
Ex: Can GPA predict SAT scores?
100
Multiple Regressions
Predict from 2 or more predictors.
Ex: Can GPA and study hours predict SAT scores?
101
Chi-Square
When to Use?
Ex:
Compare frequencies between two categorical variables.
Ex: Is there a relationship between gender and voting preference?
102
Phi Coefficient
When to Use?
Ex:
For 2 by 2 Chi-Square Tables
Ex: Gender (M/F) and Smoker (Y/N)
103
Cramer’s V
When to Use?
Ex:
For Larger Than 2 by 2 Chi-Square Tables
Ex: Education Level and Voting Preference
104
What is APA style
Writing and citation format providing standardized rules for how to format papers, cite sources, organize content, and write clearly and objectively.
105
Facts
Description
How to handle APA-Style writing
Verifiable Truths
State Clearly, Cite Source if Needed
106
Claim of Fact
Description
How to handle APA-Style writing
Assertions needing evidence
Always support with credible sources
107
Opinions
Description
How to handle APA-Style writing
Personal Views
Avoid subjective language, attribute to sources
108
How to write objectively
Use neutral and formal language. Avoid personal bias. Don’t use first-person opinions unless allowed. Focus on evidence not beliefs. Describe what research shows.
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What is desired perspective and voice
Perspective: Mostly third person.
Voice: Active voice preferred over passive.
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Tenses Used for Each Sections
Literature Review (Past Tense)
Method (Past Tense)
Results (Past Tense)
Discussion (Past (Findings)) /Conclusion (Present (Interpretations and Implications)
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Main Sections
Introduction (Background, Rationale, Research Question/Hypothesis)
Methods (Participants; Materials, Measures; Procedure; Design)
Results (Statistical Analysis and Findings)
Discussion (Interpret Findings, Implications, Limitations, Future Directions)
References (Full Citations)
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Skepticism
Genuine desire to know truth and aversion to falsehood. Thoughtful, open-minded questioning of claims until evidence is presented. Based on reason, inquiry, and evidence.
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Cynicism
Dismissive, negative attitude that assumes dishonesty or failure. Based on distrust or negativity.
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How to evaluate the evidence
Is the source credible and peer-reviewed? Was the sample size adequate? Was study well-designed? Were results statistically and practically significant? Are conclusions supported by data? Have findings been replicated?
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Importance of having a representative sample
Representative sample accurately reflects population studying.
Important: Increases External Validity, Reduce Sampling Bias, Prevent Misleading Conclusions
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Converging Evidence
When different methods or studies all point to same conclusion. Multiple different lines of support for a theory.
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Replication
Repeating a study to see if same results are obtained. Same method and same results.
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How to spot pseudoscience
Unfalsifiable claims, heavy reliance on anecdotes, lack of peer review, claims sound too good to be true, no replication, use scientific-sounding language, appeal to authority over evidence.
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Why people are attracted to pseudoscience
Simplicity (Easy answers to complex problems) Hope (Especially in health or crisis situations) Confirmation Bias, Authority, Distrust in Institutions
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What is a conspiracy theory
Subset of false beliefs in which the ultimate cause of an event is believed to be due to a plot by multiple actors working together with a clear goal in mind. Characteristics: Unfalsifiable, Overreliance on suspicion, often based on mistrust of experts and lacks empirical evidence.
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Distinguish a Scientific Theory
Build on empirical data.
Can be tested and disproved.
Reviewed and tested by other scientists.
Explains and predicts phenomenon.
Changes with new evidence.
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Distinguish a Conspiracy Theory
Based on suspicion and anecdote.
Designed to be unfalsifiable.
Rejected or ignored by experts.
Rarely predicts anything new.
Rigid and resistant to change.
123
Principle of Parsimony
When we have no reason to do otherwise and two theories account for the same facts preferring the one which is briefer. Simple explanation fits evidence usually preferred. Don’t multiply assumptions unnecessarily. Helps avoid overcomplicated explanations.
124
Scientific Inquiry
Description
Key Traits
Distinct because it demands observable evidence, testable claims, and systematic methods.
Uses controlled methods, data, peer review
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Philosophical Inquiry
Description
Key Traits
Uses logic, reasoning, argument
Not empirical and often abstract
126
Historical Inquiry
Description
Key Traits
Interprets Past Events Through Documents
Based on archival and contextual evidence
127
Experimental Method
Description
Strengths
Researcher manipulates an independent variable and randomly assigns participants to groups.
Can determine cause and effect.
High Internal Validity
Random Assignment reduces confounding
128
Experimental Method Weaknesses
May lack real-world applicability
Can be expensive and time-consuming
Not always ethical or feasible
129
Quasi-Experimental Method
Description
Strengths
Researcher manipulates IV but doesn’t randomly assign participants.
More practical and realistic in applied settings
Useful for real-world groups
130
Quasi-Experimental Method Weaknesses
Lower internal validity (confounding variables)
No random assignment
131
Non-Experimental Method
Description
Strengths
No manipulation of variables. Data is observed or measured as naturally occurring.
Easier, Cheaper, Naturalistic
Good for descriptive or predictive research
Allows research on topics unethical to manipulate
132
Non-Experimental Method Weaknesses
Cannot determine causality
Risk of Confounding Variables
May have bias in self-reported data
