Mark 302 Final Test Flashcards by Ben Grenier

Q1: What is observation research?
A) Asking consumers for opinions
B) Recording behaviors without communication
C) Conducting interviews
D) Sending out surveys

✅ Answer: B — It systematically records behaviors without questioning people.

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When is observation research most useful?
A) When behaviors are long-term and hidden
B) When behaviors are repetitive or observable
C) When motivations are private
D) When data is purely cognitive

✅ Answer: B — Works best for short, visible, repetitive behaviors.

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Which of the following is not a benefit of observation?
A) Avoids self-report bias
B) Can record all activities over long periods
C) Provides real behavior data
D) Complements other methods

✅ Answer: B — Only short periods can usually be observed.

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What is a limitation of observation?
A) Easy data interpretation
B) Can observe cognitive phenomena
C) Observer bias
D) No invasion of privacy

✅ Answer: C — Observer bias may distort data.

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What type of observation is a “mystery shopper”?
A) Structured
B) Mechanical
C) Disguised
D) Indirect

✅ Answer: C — Mystery shoppers disguise their role to observe authentic behavior.

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“Garbology” (studying trash) is an example of:
A) Direct observation
B) Indirect observation
C) Structured observation
D) Natural observation

✅ Answer: B — It infers behavior from physical traces, not direct viewing.

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Using traffic counters or scanners represents:
A) Mechanical observation
B) Human observation
C) Disguised observation
D) Unstructured observation

✅ Answer: A — Machines automatically record behaviors.

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Eye-tracking is used to measure:
A) Blood pressure
B) Emotional recall
C) Visual attention and fixation
D) Brand loyalty

✅ Answer: C — It captures where and how long people look at stimuli.

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Galvanic Skin Response (GSR) measures:
A) Eye movement
B) Brain activity
C) Arousal or tension through skin conductivity
D) Voice tone

✅ Answer: C — GSR tracks emotional arousal.

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Neuromarketing tools such as EEG and fMRI measure:
A) Purchase intention directly
B) Biological responses to infer psychological states
C) Verbal feedback
D) Survey responses

✅ Answer: B — They infer mental processes through biological signals.

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Gender and age recognition systems are used to:
A) Collect anonymous data
B) Tailor digital ads in real time
C) Conduct interviews
D) Measure brain activity

✅ Answer: B — They adjust ads based on who is detected.

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In-store tracking helps:
A) Identify private thoughts
B) Measure store layout effectiveness
C) Replace employee training
D) Eliminate sampling bias

✅ Answer: B — It tracks movement to improve layout and display strategies.

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Online tracking often uses:
A) Eye cameras
B) Cookies and beacons
C) Physiological sensors
D) Paper surveys

✅ Answer: B — Cookies and beacons track digital activity.

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The variable that is manipulated in an experiment is the:
A) Dependent variable
B) Control variable
C) Independent variable
D) Random variable

✅ Answer: C — It’s what researchers change to see its effect.

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The variable that is measured is the:
A) Dependent variable
B) Independent variable
C) Random variable
D) Confounding variable

✅ Answer: A — It’s the outcome or response.

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What increases internal validity?
A) Field settings
B) Random assignment and control
C) Natural environments
D) Small sample sizes

✅ Answer: B — Controlling variables and randomization reduce bias.

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External validity refers to:
A) Control of time and setting
B) The ability to generalize results
C) Matching participants
D) Eliminating confounds

✅ Answer: B — It shows how widely results can apply.

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History effects occur when:
A) Participants mature naturally
B) External events influence results
C) The test causes change itself
D) Participants drop out

✅ Answer: B — Outside events coincide with the experiment.

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Maturation effect happens when:
A) People change over time naturally
B) Equipment fails
C) There’s selection bias
D) Testing is repeated

✅ Answer: A — Results change due to natural development.

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Mortality (attrition) refers to:
A) Death of respondents
B) Dropout of participants between treatments
C) Low sales
D) Poor randomization

✅ Answer: B — Uneven dropout affects results.

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Selection bias occurs when:
A) Groups differ before treatment
B) Instruments change mid-study
C) Subjects are randomly assigned
D) Samples are too large

✅ Answer: A — Groups aren’t equivalent at the start.

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Testing effects occur when:
A) Pre-testing changes later responses
B) Subjects drop out
C) Researchers misinterpret data
D) Instruments are stable

✅ Answer: A — Taking a test influences future behavior or awareness.

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The notation “O1 X O2” represents:
A) After-only design
B) Before-and-after single group design
C) True experimental design
D) Randomized design

✅ Answer: B — Observation before and after treatment.

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Adding a control group makes it a:
A) Quasi-experiment
B) Correlational study
C) Pre-experimental design
D) Field observation

✅ Answer: A — It helps account for external factors but may lack full control.

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“R” in an experimental design means: A) Repetition B) Random assignment C) Regression D) Reliability

✅ Answer: B — It indicates randomization.

Which software is used in this course for statistical analysis? A) Excel B) SPSS C) Python D) Tableau

✅ Answer: B — SPSS is used for data analysis in this course.

Which of the following is a descriptive statistical analysis? A) ANOVA B) Frequency Tables C) Regression Analysis D) Chi-Square Test

✅ Answer: B — Descriptive analyses summarize data using frequencies and averages.

Which type of analysis studies relationships between two variables? A) Descriptive B) Inferential C) Associative D) Predictive

✅ Answer: C — Associative analysis examines how variables move together.

Regression analysis is an example of which type of statistical analysis? A) Descriptive B) Predictive C) Inferential D) Bivariate

✅ Answer: B — It predicts one variable based on another.

The null hypothesis (H₀) states that: A) There is no difference or effect B) There is a significant difference C) The data is non-normal D) The sample size is large

✅ Answer: A — H₀ always assumes no difference or relationship.

The alternative hypothesis (H₁) states that: A) No difference exists B) Sampling error occurred C) A difference or relationship exists D) Variables are identical

✅ Answer: C — H₁ assumes there is an effect or difference.

Which of the following is an example of a null hypothesis? A) Men and women spend differently on skincare B) Men and women have equal skincare spending C) Younger people are happier than older people D) Income affects shopping frequency

✅ Answer: B — The null always claims equality or no difference.

The Chi-Square test is used for: A) Comparing means B) Testing frequencies or proportions C) Predicting outcomes D) Measuring correlations

✅ Answer: B — It’s used for categorical data to test frequency differences.

The Chi-Square statistic compares: A) Means vs. standard deviations B) Observed vs. expected frequencies C) Two independent samples D) Dependent variables

✅ Answer: B — It measures how far observed counts differ from expected ones.

A Goodness-of-Fit Chi-Square test checks: A) Correlation between variables B) Whether observed frequencies match expected ones C) Difference between means D) Variance equality

✅ Answer: B — It assesses how well data fits a theoretical distribution.

What test compares the means of two independent groups? A) One-way ANOVA B) Paired t-test C) Independent samples t-test D) Regression test

✅ Answer: C — Used when groups are separate (e.g., male vs. female).

What test compares two scores from the same participants? A) Paired sample t-test B) Independent t-test C) Regression analysis D) Chi-Square test

✅ Answer: A — Used when the same subjects are measured twice.

ANOVA is used when comparing: A) Two groups B) More than two groups C) Only paired data D) Frequencies

✅ Answer: B — One-way ANOVA compares means across 3+ groups.

In hypothesis testing, if p < 0.05, we: A) Fail to reject H₀ B) Reject H₀ C) Accept H₀ D) Ignore the result

✅ Answer: B — A small p-value means the result is statistically significant.

What are the independent and dependent variables in this test? A) Both are categorical B) Independent = categorical; Dependent = interval/ratio C) Both are continuous D) Independent = interval; Dependent = categorical

✅ Answer: B — Grouping variable is categorical; outcome variable is continuous.

Example: Users vs. non-users’ safety beliefs about online banking. If p = 0.001, what is the conclusion? A) Fail to reject H₀ B) Reject H₀ — beliefs differ significantly C) Samples are identical D) Results are not significant

✅ Answer: B — The low p-value means users and non-users differ in beliefs.

When would you use a paired t-test? A) Comparing two unrelated groups B) Comparing the same subjects under two conditions C) Comparing more than two groups D) Testing frequency data

✅ Answer: B — The same participants are tested twice (e.g., pre/post).

Example: Comparing enjoyment of Taylor Swift vs. Beyoncé concerts by the same people — which test? A) Independent t-test B) Paired t-test C) ANOVA D) Regression

✅ Answer: B — Same respondents, two measures.

ANOVA tests whether: A) Two groups differ B) Variances are equal C) Three or more group means differ D) Variables are correlated

✅ Answer: C — It checks if at least one group mean differs.

Example: Attitudes toward socially responsible brands across age groups — which test? A) Independent t-test B) Chi-Square C) One-way ANOVA D) Regression

✅ Answer: C — Three age groups = One-way ANOVA.

What is internal validity? A) How well results generalize B) How well we can say X causes Y C) How real-world conditions are D) Randomness of sampling

✅ Answer: B — Internal validity = proving cause and effect.

xternal validity means: A) Control of variables B) Ability to generalize to other settings C) Random assignment D) Lab accuracy

✅ Answer: B — External validity = real-world generalizability.

Which type of experiment has higher internal validity? A) Lab experiment B) Field experiment C) Observational study D) Survey

✅ Answer: A — Controlled lab settings reduce alternative explanations.

Which type of experiment has higher external validity? A) Field experiment B) Lab experiment C) Randomized study D) Survey

✅ Answer: A — Field experiments happen in natural settings.

What is a history effect? A) Participants maturing B) External events influencing results C) Measurement error D) Dropout of participants

✅ Answer: B — Events outside the study impact outcomes.

Maturation effect means: A) Participants change naturally over time B) Data entry errors C) Instrument failure D) Random assignment issues

✅ Answer: A — Example: teenagers naturally aging during study.

Testing effect refers to: A) Loss of subjects B) Repeated measurement influencing responses C) External event bias D) Data manipulation

✅ Answer: B — Pretesting can alter future answers.

nstrument variation occurs when: A) Participants change B) Measurement method changes between tests C) Results are missing D) Testing conditions are constant

✅ Answer: B — Different instruments yield inconsistent data.

Mortality (attrition) refers to: A) Death in the sample B) Uneven dropout across conditions C) Equipment malfunction D) Small sample sizes

✅ Answer: B — Losing more participants from one condition.

Selection bias happens when: A) Participants are randomly assigned B) Groups differ before the experiment C) Data is missing D) Time order is incorrect

✅ Answer: B — Non-equivalent groups before treatment.

What is the main advantage of random assignment? A) Creates equal groups B) Reduces sample size C) Prevents maturation D) Improves external validity

✅ Answer: A — It balances individual differences across groups.

Which of the following is not a type of relationship between variables? A) Monotonic B) Non-monotonic C) Randomized D) Curvilinear

✅ Answer: C — Randomized refers to design, not a type of relationship.

A monotonic relationship means: A) The relationship changes direction B) The variables move in only one direction (increasing or decreasing) C) Variables have no relationship D) The relationship forms a curve

✅ Answer: B — Monotonic relationships move in a consistent direction.

Which relationship type is represented by a straight line? A) Linear B) Curvilinear C) Random D) Non-monotonic

✅ Answer: A — Linear relationships have a constant rate of change.

The characteristics of relationships include: A) Scale, bias, error B) Presence, direction, and strength C) Randomness, causality, frequency D) Normality, skewness, kurtosis

✅ Answer: B — These are the three core relationship descriptors.

A correlation close to 0 suggests: A) A strong relationship B) No linear relationship C) A causal effect D) A perfect negative relationship

✅ Answer: B — Little to no linear association exists.

A correlation shows: A) Causation B) Random association C) Statistical relationship between variables D) Confounding factors

✅ Answer: C — Correlation measures association, not causation.

What type of correlation exists if one variable increases as another decreases? A) Positive B) Negative C) Curvilinear D) Monotonic

✅ Answer: B — As one rises, the other falls = negative correlation.

Predictive analysis is used to: A) Describe patterns in data B) Forecast outcomes based on past data C) Compare group means D) Test independence

✅ Answer: B — It forecasts future outcomes.

The two main approaches to prediction are: A) Randomization and estimation B) Extrapolation and predictive modeling C) ANOVA and t-tests D) Sampling and inference

✅ Answer: B — Past trends or statistical models are used to predict.

What does the ANOVA table tell you in regression analysis? A) Sample size B) Whether the overall model is significant C) Normality of data D) Direction of correlation

✅ Answer: B — A significant p-value (<0.05) means the regression model fits.

A higher R-square (R²) means: A) Poorer model fit B) Better model fit C) Lower prediction accuracy D) No relationship

✅ Answer: B — It indicates the model explains more variance in y.

To confirm a coefficient is statistically significant, its p-value must be: A) > .10 B) < .05 C) = .50 D) > .20

✅ Answer: B — A p-value under 0.05 means a significant effect.

The regression model formula using significant coefficients is used to: A) Collect data B) Make predictions C) Compute correlation D) Conduct sampling

✅ Answer: B — The model estimates future dependent variable values.

Multiple regression predicts: A) A single variable B) A dependent variable using several independent variables C) Two variables only D) Group differences

✅ Answer: B — It includes several predictors (X₁, X₂, X₃...).

How are nominal variables represented in regression? A) Standardized z-scores B) Dummy coding (0s and 1s) C) Random values D) Ranked orders

✅ Answer: B — Dummy variables represent group membership.

Collinearity refers to: A) Correlation among dependent variables B) Correlation among independent variables C) Error term dependency D) Outliers in data

✅ Answer: B — High intercorrelation between predictors can bias results.

What is a common fix for collinearity? A) Increase sample size B) Drop one correlated variable C) Ignore the problem D) Add more predictors

✅ Answer: B — Removing one correlated predictor reduces bias.

Regression does not show: A) Prediction B) Relationship C) Causation D) Correlation

✅ Answer: C — Regression shows association, not causation.

Internal validity measures: A) How well results apply to the real world B) How confidently we can say X causes Y C) Random sampling D) Strength of correlation

✅ Answer: B — It ensures causal accuracy.

External validity measures: A) Causal direction B) Generalizability to other settings C) Sampling error D) Reliability

✅ Answer: B — Results should hold across contexts.

Which has higher internal validity? A) Field experiment B) Lab experiment C) Survey D) Observation

✅ Answer: B — Labs provide more control.

Which has higher external validity? A) Lab experiment B) Field experiment C) Meta-analysis D) Simulation

✅ Answer: B — Field studies mimic real-world conditions.

“O” in experimental design stands for: A) Observation or measurement B) Outcome variable C) Operation D) Objectivity

✅ Answer: A — It’s when the dependent variable is measured.

A history effect occurs when: A) Participants mature B) External events influence results C) Instruments fail D) Participants drop out

✅ Answer: B — Outside events bias experimental outcomes.

Selection bias occurs when: A) Random assignment is used B) Groups differ before treatment C) Instruments are consistent D) Observations are matched

✅ Answer: B — Unequal groups before intervention.

Mortality (attrition) in experiments refers to: A) Deaths B) Unequal dropout rates across groups C) Random assignment issues D) Fatigue during testing

✅ Answer: B — Differential dropouts distort results.

Mark 302 Final Test Flashcards

(82 cards)