Scientific and Statistical Reasoning Exam UvA Year 2

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Questions and Answers

What is the primary benefit of randomization in research?

It ensures all variables are measured accurately.

It allows researchers to observe natural occurrences.

It reduces the sample size required for the study.

It eliminates confounder bias. (correct)

What does the 'do-operator' signify in causal inference?

A variable that is correlated with both X and Y.

A measure of the uncertainty in the randomization process.

An automatic adjustment made for confounders in observational studies.

An intervention or action that sets a variable to a specified value. (correct)

Which statement accurately describes a confounder?

A variable that affects both the exposure and outcome independently. (correct)

A variable that is only associated with either X or Y.

A variable that is not correlated with the exposure X.

A variable that operates along the causal pathway between exposure and outcome.

What is one limitation of the classical epidemiological definition of confounding?

It does not account for unobserved variables. Signup and view all the answers

How does randomization quantify uncertainty in research?

Through the known outcomes of the randomization process. Signup and view all the answers

What is necessary to establish causal relationships beyond mere associations?

Additional assumptions Signup and view all the answers

Which of the following is NOT a current practice in causal inference according to the article?

Bidirectional arrows are encouraged in DAGs Signup and view all the answers

What does a Directed Acyclic Graph (DAG) represent in causal inference?

The direction of causal influence between variables Signup and view all the answers

Why is misunderstanding causal inference harmful?

It can misinform lay readers and policymakers Signup and view all the answers

According to the article, which statement about causal inference is true?

Human reasoning heavily relies on understanding causality. Signup and view all the answers

What does the term 'predictive' indicate in the context of the article?

A type of relationship misconstrued as causal Signup and view all the answers

Which of the following is a major goal of psychology mentioned in the article?

To improve the lives of humanity Signup and view all the answers

What characteristic is true of a Directed Acyclic Graph?

It has directed edges without closed paths. Signup and view all the answers

What is the concatenation operation primarily used for?

To combine two or more strings, sequences, or sets Signup and view all the answers

What does the property of identity in scaling signify?

The ability to reflect differences among categories Signup and view all the answers

Which scale of measurement is exemplified by hair color?

Nominal Signup and view all the answers

What is an example of an interval scale of measurement?

Temperature Signup and view all the answers

What does the theory of admissible statistics propose?

Different levels of measurement should not determine statistical analysis choices Signup and view all the answers

Which of the following best describes relative zero in measurement?

It is the lowest value on a specific scale of measurement Signup and view all the answers

In the context of scaling, what does the property of order signify?

It reflects the ranking of items Signup and view all the answers

Why is it inadmissible to perform a t-test on non-interval data?

Mean values cannot be calculated reliably Signup and view all the answers

What does falsifiability refer to in a theory?

The theory must be open to being proven false. Signup and view all the answers

Which of the following describes parsimony in theory development?

The idea that the simplest theory that explains a phenomenon is preferred. Signup and view all the answers

What does breadth in a theory indicate?

The range of phenomena the theory can explain. Signup and view all the answers

What is the main advantage of formal models in research?

They can simulate different conditions to evaluate theories. Signup and view all the answers

What does coherence refer to in the context of theory evaluation?

The theory's consistency with other established models and its internal coherence. Signup and view all the answers

How is precision defined in the context of theory evaluation?

The clarity and specificity of a theory's language. Signup and view all the answers

What does post-diction refer to in a theory's evaluation?

Providing explanations that can only be affirmed afterward. Signup and view all the answers

Which of the following best describes the significance of theory originality?

The theory should introduce new concepts rather than reiterating others. Signup and view all the answers

What does a large value of S SM indicate about the model's predictions?

The linear model significantly improves prediction over the mean. Signup and view all the answers

How is R^2 calculated?

R^2 = S S<del>M</del> / S S<del>T</del> Signup and view all the answers

What is indicated by a small value of S SM?

The model is a little better than using the mean. Signup and view all the answers

In the F-statistic formula, what does a larger numerator signify?

Good model fit. Signup and view all the answers

What does the t-statistic test regarding individual predictors?

Whether the slope differs from zero. Signup and view all the answers

What might standardised residuals greater than 3.29 suggest?

Significant outliers that could affect the model. Signup and view all the answers

How is the number of predictors represented in the F-statistic formula?

k Signup and view all the answers

What outcome is suggested if more than 1% of standardised residuals are greater than 2.58?

The model has significant inaccuracies needing attention. Signup and view all the answers

What does a confidence interval of the indirect effect containing zero suggest about the mediator?

The mediator does not mediate the relationship. Signup and view all the answers

In the context of moderation, what does the interaction effect indicate?

Whether moderation has occurred. Signup and view all the answers

What is the purpose of simple slopes analysis in moderation?

To examine moderation effects at different levels of the moderator. Signup and view all the answers

What does centering a variable involve?

Adjusting deviations from the mean. Signup and view all the answers

Which step is NOT part of conducting moderation analysis in SPSS?

Perform bootstrapping on the predictor. Signup and view all the answers

What does the zone of significance indicate in moderation analysis?

Where the predictor significantly predicts the outcome. Signup and view all the answers

When interpreting SPSS output in moderation analysis, which common analysis does NOT occur?

Calculating the total effect without interaction terms. Signup and view all the answers

Which is a key focus of moderation in research?

The conditions affecting the relationship strength or direction. Signup and view all the answers

Study Notes

Summary Exam 3 Scientific and Statistical Reasoning UvA Year 2

Exam covers scientific and statistical reasoning, focusing on causal inference and developmental psychology.
Important to move from association to causation, not just assuming it based on an association between variables. Additional assumptions are necessary
Causal inference is crucial to developmental psych for improving human lives
Directed acyclic graphs (DAGs) and potential outcomes frameworks help understand causal relationships.
DAGs use arrows to represent the direction of causal influence and are acyclic to prevent loops.
Potential Outcomes Framework assesses the difference outcomes would have been if an intervention hadn't happened.
Confounders are variables associated with both the independent and dependent variables in a study.
Mediators are variables on the causal pathway between the independent and dependent variable, offering insights to underlying mechanisms.
Colliders are variables influenced by two or more variables.
Understanding and controlling for these variables leads to more accurate causal inferences.
Avoiding confounds and appropriately controlling for variables is essential for accurate causal understanding in study design and data analysis.

Causal Inference and Developmental Psychology

Causal inference is fundamental for understanding the world.
Key goal is to improve human lives, which often requires understanding the causes of events.
Causal thinking is a universal human tendency.
Distinguishing associations and causal relationships is often challenging, even for researchers.
Inaccurate causal inferences can have harmful consequences for various stakeholders.

Conceptual Tools

Directed acyclic graphs (DAGs) illustrate causal pathways.
Arrows in a DAG represent causal influence.
Acyclic structure prevents loops.
Potential outcomes framework defines the causal effect based on hypothetical counterfactuals.

Variables in Causal Inference

Confounders: Variables associated with both the independent and dependent variables.
Mediators: Variables on the causal pathway between the independent and dependent variable.
Colliders: Variables influenced by two or more variables.

Summary Exam 3: Scientific and Statistical Reasoning

Avoiding confounds and appropriately controlling for variables are essential for accurate causal understanding in study design and data analysis.
The use of statistical tools and frameworks in developmental psychology.

Correlation

Covariance measures how variables change together, but is not standardized.
Correlation is standardized covariance, and ranges from -1 (perfect negative) to +1 (perfect positive).
Pearson's r is the most common correlation coefficient.
A p-value exceeding 0.05 means there is no statistical significance.
Confidence intervals show the range where the population value might lie.
Coefficient of determination (R²) shows the proportion of variance in one variable explained by the other.

Quasi-Experiments

Quasi-experiments are research designs similar to experiments, but without random assignment of participants.
Common threats include history, maturation, selection, attrition, instrumentation, testing, and regression to the mean.
These issues can distort causal inferences from observational studies.

Problems with Multicollinearity

Multicollinearity occurs when predictors are highly correlated with each other.
Multicollinearity increases the variability of the regression coefficients for the predictors, making the importance of individual predictor variables difficult to assess.
The variance inflation factor (VIF) and tolerance statistic can help detect multicollinearity.

Mediation and Moderation

Mediation indicates an indirect effect of a predictor on an outcome through a third variable (mediator); a mediating variable is a causal variable between predictor and outcome but needs to be tested.
Moderation refers to conditions where the influence of a predictor on an outcome depends on the level of a third variable (moderator).
Mediation and moderation analyses in SPSS use structural equation modelling or PROCESS procedures.

Qualitative Research

Qualitative research aims to understand real-world phenomena in detail.
It uses methods like interviews, observations, and text analysis.
Qualitative research adopts a reflexive stance: researchers acknowledge the influence of their assumptions on their interpretations.
Qualitative research distinguishes itself from quantitative research in its emphasis on the exploration of concepts and themes.

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Description

This quiz tests knowledge on scientific and statistical reasoning with an emphasis on causal inference and developmental psychology. Key concepts include directed acyclic graphs (DAGs), potential outcomes frameworks, and the roles of confounders and mediators in causal analysis. Understanding these principles is vital for applying statistical reasoning effectively.