ADV 281 Exam 1 Study Notes
Pierce's Four Paths
Worst to Best:
Method of Tenacity
Method of Authority
A Priori Method
Scientific Method
Method of Tenacity
Defined as clinging to familiar beliefs because they provide peace of mind.
Method of Authority
Based on the premise that someone who is older, wiser, or more experienced (possibly holding a title) informs what is right or wrong.
Example: The Pope declaring the Earth as the center of the universe, which led to widespread belief.
A Priori Method
Involves reasoning from cause to effect.
Entails careful thought and self-reflection in deciding matters.
Scientific Method
Centers on reliance on empirical inquiry, which must be observable by anyone.
Characterizes by specific rhetoric involving independent and dependent variables.
Recognizes limits and boundaries to scientific truths, asserting that they are probabilistic.
Involves systematic techniques or procedures for analyzing empirical evidence in an unbiased attempt to confirm or disprove prior conceptions.
Scientific Method (Step by Step)
Observation/Question
Research Topic Area
Hypothesis
Test with Experiment
Analyze Data
Report Conclusions
Basic vs. Applied Research
Basic Research: Conducted to enhance knowledge about a topic.
Example: Investigating visual attention in 4-6 year old children, often conducted in a lab.
Applied Research: Aimed at solving practical problems with findings that can be directly applied to real-world issues.
Example: Investigating effective methods for teaching reading to children, often conducted in the field.
Lab vs. Field Research
Lab Research:
Has fewer confounds; greater control in study design.
May be artificial in nature.
Field Research:
May contain more confounds.
Researchers have less control over variables.
Inductive vs. Deductive Reasoning
Inductive Reasoning:
Involves developing generalizations from specific observations.
Deductive Reasoning:
Entails developing specific predictions from general principles.
Quantitative vs. Qualitative Research
Quantitative Research:
Measures differences in the amount of behavior exhibited.
Qualitative Research:
Describes differences in the kind or quality of behavior shown.
Basic / Lab Research Characteristics
Knowledge-driven
Lab-based
Experimental approach
Nomothetic (aimed at broad generalization)
Field / Applied Research Characteristics
Problem-driven
Field-based
Correlational approach
Idiographic (very narrowly focused)
Possible Ways to Measure Reading
Methods:
Self-report
Observation
Existing data (archives or secondary data)
Self-Report
Not ideal due to limitations in human memory.
Particularly problematic for sensitive subjects.
Example: Asking individuals how much they read newspapers may yield inaccurate responses.
Observation
Challenging because it does not confirm whether people are actively engaged or just glancing at the material.
Requires willingness from people being observed or must occur in public spaces.
Example: Observing behavior in locations where newspapers are present.
Existing Data "Archives" or Secondary Data
Example: Analyzing leftover newspapers.
Advertising-Related Concepts
Advertising Efficacy:
Questions regarding how we assess the effectiveness of an advertisement.
Brand Equity:
Refers to the strength of a brand in relation to competing brands.
Product Use:
Noting that a product might be purchased but never utilized.
Brand Loyalty:
Can be defined or conceptualized in numerous ways.
Conceptual Definition
A verbal explanation delineating the meaning of a variable.
Clarifies what the concept encompasses and what it excludes.
Resembles a dictionary definition.
Example: Defining "attitude" which is a tendency that may change over time.
Indicators: Metrics to assess various dimensions of an attitude.
Aaker's Brand Personality Dimensions
Sincerity
Excitement
Competence
Sophistication
Ruggedness
Operational Definition
A detailed description of how something is measured.
Specifies the operations necessary to obtain data.
Can involve observable indicators such as a yawn that signals tiredness.
Measures of Central Tendency
Mean: Average
Median: Middle value
Mode: Most frequently occurring value
Measures of Dispersion
Range: Distance between the smallest and largest value in a dataset.
Formula: Range = Largest Value - Smallest Value
Variance: Measurement of how far each number in the dataset is from the mean.
Expressed in squared units.
Relationship to Standard Deviation: Standard deviation is the square root of variance.
Conceptualization vs. Operationalization
Conceptualization: The process of defining a variable.
Operationalization: The methodology for measuring that concept.
Example:
Age can be conceptualized as the total years lived since birth.
Normal Distribution
Described as a bell-shaped curve.
Almost all values within the distribution fall within plus or minus 3 standard deviations.
Example: IQ scores typically reflect normal distribution.
Ethics
Defined as moral principles that guide the determination of right or wrong actions.
Deontology
A branch of knowledge focused on moral obligations.
Asserts that certain actions are inherently immoral or unethical regardless of consequences.
Two Critical Principles of Deontology
Rights Principle:
Evaluated based on universality and reversibility (treat others as you wish to be treated).
Justice Principle:
Distributive Justice: Fair distribution of benefits based on contribution.
Retributive Justice: Makes amends for harm caused.
Compensatory Justice: Ensures fair compensation for injuries.
Utilitarianism
Focuses on the consequences of actions, aiming for "the greatest good for the greatest number."
Common Concerns in Codes of Ethics
Respect for Persons: Ensuring inform consent and protecting individuals with diminished autonomy.
Beneficence: Striving to maximize benefits while minimizing harm during research.
Justice: Identifying who deserves the benefits of research and who should bear its burdens.
Ethical Issues in Researcher-Participant Relationship
Voluntary participation.
No harm to participants.
Anonymity and confidentiality.
Informed consent.
Minimizing deception in the research process.
Confidentiality and Privacy
Confidentiality is absolute unless participants are informed otherwise.
Research Question vs. Hypothesis
Research Question: Widely framed inquiries that are broad in scope.
Hypothesis: Specific predictions articulated as statements to be tested.
Levels of Measurement
Nominal Scale:
Uses numbers or letters as labels for identification or classification without meaningful numeric representation.
Appropriate only for mode as a measure of central tendency.
Example: User/nonuser or occupations.
Ordinal Scale:
Arranges objects according to their magnitude in an ordered relationship, indicating relative size without precise distances.
Example: Football rankings.
Interval Scale:
Organizes objects by magnitude and distinguishes them using equal unit distances.
Example: Temperature or GPA, applicable for mean, median, and mode.
Ratio Scale:
Reflects absolute quantities, possessing an absolute zero point representing absence of an attribute.
Example: Units sold or income, applicable for mean, median, and mode.
Higher Levels of Measurement:
Higher scales encompass the properties of lower levels (e.g., Ratio includes Nominal, Ordinal, and Interval properties).
Criteria for Good Measurement
Reliability
Validity
Sensitivity
Reliability & Assessment
Defines as consistency in results over time.
Assessing Reliability:
Test-Retest Reliability: administering the same test to the same group under equivalent conditions.
Alternative Form: offering different forms of the same test to the same group at two separate times.
Validity & Assessment
Indicates that a measure assesses what it is supposed to measure.
Reliability must precede validity.
Assessing Validity:
Face Validity: Consensus agreement among experts.
Concurrent Validity: Comparison with accepted measures.
Predictive Validity: Ability of the measure to forecast future outcomes.
Sensitive Measure
Captures subtle changes in the target response accurately.
Cross-Sectional Surveys
Provide insights on whether two variables are correlated.
Limitations:
Cannot ascertain a cause-and-effect relationship.
Establishing Cause-and-Effect Relationships
Covariation: There is a relationship between cause and effect.
Temporal Precedence: The cause precedes the effect chronologically.
Internal Validity: Ability to rule out plausible alternative explanations.
Conceptual & Operational Definitions
Must align consistently with one another to ensure clarity in research.
Sample
The group of all respondents in a study.
Subjects/Respondents/Participants
Terms that can be used interchangeably to describe individuals involved in a study.
Sampling
The process involved in selecting the respondents for research.
Representative Sample
A sample reflecting the larger population, selected using statistical random techniques.
Population
The larger group that researchers intend to study.
Non-Representative Sample
Does not accurately represent all respondents across the target population.
Applying Conceptual/Operational Definitions to Cassandra's Example
Conceptual: Defines "reading the newspaper" in terms of minutes spent engaged with it per day.
Operational: Must correlate with how it will be measured effectively.
Reasons Samples Fail to Represent a Population
Bias: Samples may inadvertently favor a particular type of participant.
Error: Random chance discrepancies in representation.
Archives
A collection of existing resources (information or data) available for research purposes.
Note: Notably includes other forms of data beyond just numerical information.
Empirical Questions
Questions answerable through direct observation of the world; can yield qualitative or quantitative data.
Histogram
A graphical representation of score frequencies for a variable.
Plotted with the variable's scores along the x-axis and frequency counts on the y-axis.
Z-score
Indicates how far an individual score lies from the mean in terms of standard deviations, with positive indicating above the mean and negative indicating below the mean.
Directional vs. Nondirectional Hypothesis
Directional Hypothesis: Specifies the direction of the expected relationship.
Nondirectional Hypothesis: Does not specify the direction of the association between variables.
Common Mistakes in Hypothesis Testing
Testing hypotheses by merely asking if people believe the hypothesis to be true, rather than through experimental or observational methods.
Measurement Levels Classification
Categorical: Number of categories not arranged in any order.
Ordinal: Categories are ordered but not indicative of exact distances.
Interval: Numerous categories indicating specific amounts arranged from one extreme to the other.
Levels of Measurement Examples
Biological Sex: Categorical/Nominal
Time Taken to Run 100 Meters: Interval
Computer Operating System Type: Categorical/Nominal
Feelings Today: Ordinal (unhappy, meh, happy)
Support for Increased Defense Spending: Ordinal (very low to very high)
Functions of Theory
Provides insights on necessary observations to validate the theory.
Acts as a repository for research aiding in building or modifying existing theories.
Correlation
A statistic measuring the strength of association between two variables, ranging from -1 to 1.
Effect Size
Describes the strength of the relationship between two variables.
Confidence Level
Denotes the probability that the true population correlation coefficient lies within a confidence interval.
Note: Wider confidence intervals usually signify higher confidence.
Null Hypothesis
Represents the assumption that there is no significant difference between specified populations, attributing any observed differences to sampling or experimental errors.
Statistical Significance
Indicates that it is highly improbable that the true population value of a correlation is zero, suggesting that the null hypothesis is false.
Confidence Interval
A range of values surrounding the observed sample mean.
As sample sizes increase, confidence intervals tend to narrow.
If a confidence interval does not include zero, the correlation is statistically significant.