Research Claims & Validity Overview

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Questions and Answers

What is the primary goal of frequency claims in research?

  • To correlate two independent measures
  • To establish causation between variables
  • To describe the rate or frequency of a variable (correct)
  • To predict the relationship between two variables

Which statement best defines an association claim in research?

  • It looks at the frequency of a single variable.
  • It determines the cause-and-effect relationship between two variables.
  • It measures the direct impact of one variable on another.
  • It predicts the relationship between two variables. (correct)

What does the correlation coefficient (r) indicate?

  • The strength and direction of the relationship between two variables (correct)
  • The statistical significance of the study's outcomes
  • The degree of manipulation applied to the variables
  • The rate of frequency of the variables being studied

What is an example of a manipulated variable?

<p>Type of meditation used in a mindfulness study (B)</p> Signup and view all the answers

Which of the following correctly describes a causal claim?

<p>It identifies a cause-and-effect relationship between two variables. (B)</p> Signup and view all the answers

Which statement about correlation is true?

<p>A correlation of r = 0.0 indicates no association between the variables. (B)</p> Signup and view all the answers

What type of claim seeks to provide insight into the relationship between gratitude and relationship satisfaction?

<p>Association claims (B)</p> Signup and view all the answers

Which of the following is a characteristic of internal validity?

<p>The ability to establish a cause-and-effect relationship (C)</p> Signup and view all the answers

What does internal validity primarily assess?

<p>The elimination of third-variable explanations (C)</p> Signup and view all the answers

Which aspect does external validity evaluate?

<p>The ability to replicate results in different contexts (A)</p> Signup and view all the answers

What does effect size measure in the context of statistical validity?

<p>The strength of the association between variables (A)</p> Signup and view all the answers

What happens in a Type I error?

<p>An association is incorrectly concluded to exist (C)</p> Signup and view all the answers

Which of the following is NOT a criterion for establishing causation between two variables?

<p>Statistical significance (B)</p> Signup and view all the answers

Why is a larger sample size significant in statistical validity?

<p>It reduces the chances of Type II errors (D)</p> Signup and view all the answers

What is meant by 'confidence interval' in the context of statistical validity?

<p>The range of values within which a population parameter falls (C)</p> Signup and view all the answers

What is the purpose of assessing the power of a study?

<p>To gauge the likelihood of detecting an effect if one exists (C)</p> Signup and view all the answers

What type of claim is made when gratitude is asserted to be related to greater relationship satisfaction?

<p>Association claim (C)</p> Signup and view all the answers

Which of the following is not a criterion for making a causal claim?

<p>Sample size (A)</p> Signup and view all the answers

What is the relationship between gratitude and relationship satisfaction in terms of research classification?

<p>Gratitude is the predictor variable. (B)</p> Signup and view all the answers

Which type of research goal involves determining how common a behavior or phenomenon is?

<p>Descriptive goal (A)</p> Signup and view all the answers

What does manipulating gratitude in an experiment allow researchers to establish?

<p>The causal relationship between gratitude and relationship satisfaction (A)</p> Signup and view all the answers

Which claim suggests that expressing gratitude increases relationship satisfaction?

<p>Causal claim (B)</p> Signup and view all the answers

Which of the following best describes the function of temporal precedence in causal claims?

<p>Establishing that the cause occurs before the effect (B)</p> Signup and view all the answers

In the context of research validity, which aspect evaluates how well the measures actually assess the concepts they are intended to?

<p>Construct validity (B)</p> Signup and view all the answers

What does internal validity specifically require in an experiment?

<p>There is only one explanation for the change in the dependent variable (D)</p> Signup and view all the answers

What is meant by random assignment in an experimental context?

<p>Everyone has an equal chance of being selected for any condition (B)</p> Signup and view all the answers

Which aspect is not evaluated under internal validity?

<p>Generalization of findings (D)</p> Signup and view all the answers

What is the primary goal of external validity?

<p>To ensure findings are applicable to various populations and settings (D)</p> Signup and view all the answers

Which statement defines statistical validity in research?

<p>It examines if the findings are quantitatively significant and reliable (B)</p> Signup and view all the answers

In a study where violent video games are assessed for their impact on aggression, what does the hypothesis predict?

<p>Participants playing violent video games will be more aggressive than those playing non-violent games (B)</p> Signup and view all the answers

What does an effect size of d = .20 typically suggest?

<p>A small effect is present (A)</p> Signup and view all the answers

What is an important factor to consider for construct validity?

<p>If the measurements accurately reflect the intended concept (D)</p> Signup and view all the answers

Flashcards

External Validity

How well a study's results can be generalized to other people, situations, and settings outside the original study.

Statistical Validity

The accuracy and reasonableness of the statistical conclusions drawn from a study.

Construct Validity

The extent to which a study measures the intended construct or concept.

Internal Validity

The degree to which a study successfully rules out alternative explanations for the observed effect, ensuring that the relationship between variables is causal.

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Type 1 Error

The probability of finding a statistically significant result when there is no real effect in the population.

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Type 2 Error

The probability of failing to find a statistically significant result when there is a real effect in the population.

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Effect Size

The strength of the association between two variables.

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Confidence Interval

A range of values that likely contains the true population parameter. It helps to understand how precise an estimate is.

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Frequency Claim

A research claim that describes the rate or frequency of a single variable. For example, "10% of people in a committed relationship met their partners through online dating."

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Association Claim

A research claim that describes the relationship between two variables. For example, "Gratitude is correlated with relationship satisfaction."

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Correlational Study

A type of research study that measures the relationship between two variables.

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Correlation Coefficient (r)

A numerical value between -1 and +1 that indicates the strength and direction of the relationship between two variables.

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Positive Association

A type of association in which an increase in one variable is related to an increase in another variable.

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Negative Association

A type of association in which an increase in one variable is related to a decrease in another variable.

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No Association

A type of association in which there is no relationship between two variables.

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Correlation Does Not Equal Causation

Just because two variables are correlated, it does not mean that one causes the other. For example, ice cream sales and crime rates may be correlated, but one does not cause the other.

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Independent Variable

The variable that is thought to affect the outcome, the cause.

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Dependent Variable

The outcome of interest, the effect that depends on the independent variable.

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Random Assignment

Every participant has an equal chance of being assigned to any condition in the experiment.

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Tradeoffs

The ability to confidently conclude that the independent variable caused the changes in the dependent variable, without any other possible explanations.

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Causal Claim

A research claim that asserts that one variable directly causes another. For example, a study might find that taking a particular medication causes a decrease in symptoms.

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Study Notes

Research Claims & Validity

  • Research claims categorize research goals as describing, predicting, or explaining.
  • Frequency claims describe the rate or frequency of a variable.
  • Association claims predict the relationship between two variables.
  • Causal claims explain the relationship between variables.
  • Association claims can be correlational studies or measure the strength of a relationship using a correlation coefficient.
  • Positive and negative associations between variables follow specific patterns in scatterplots.
  • A correlation does not imply causation
  • Frequency claims look at a single variable to describe how common it is. Example: the percentage of people in committed relationships who met through online dating

Evaluating Research

  • Four types of validity evaluate a study's quality: construct, external, statistical, and internal validity.
  • Construct validity assesses how well variables are measured or manipulated in a study.
  • External validity describes how generalizable the study results are to other people, contexts, or methods.
  • Statistical validity examines how strong an effect is and the precision of an estimate.
  • Internal validity determines whether A (the independent variable) or C (some other variable) explains changes in B (the dependent variable) in a relationship.
  • Causal claims require covariance, temporal precedence, and internal validity
  • Evaluating frequency claims involves looking at the margin of error and confidence intervals.
  • Evaluating association claims involves using effect size and confidence interval.
  • Evaluating causal claims requires identifying confounds and using random assignment.

Variables

  • Independent variables are manipulated, while dependent variables are measured to see their impact.
  • Correlational studies typically involve predictor and outcome variables.
  • Variables need clear and specific operational definitions for precise measurements.
  • Independent variables are the causal factors.
  • Dependent variables are the outcomes
  • Constant factors do not change with an experiment
  • Different levels or conditions of an independent variable change outcomes depending on their influence on the dependent variable.

Operational Definitions

  • Operational definitions precisely specify how variables are measured or manipulated.
  • This clarity avoids ambiguity and ensures consistent measurement.
  • Operational definition is important as different measurement techniques will affect the end result.
  • Providing distinct and verifiable operational definitions of variables is critical for accurately measuring them and ensuring that the outcome of an investigation is not influenced or distorted by the lack thereof

Practice Questions Example

  • Research goal examples (frequency, association, causal)
  • Examples involving the variables selfies and narcissism.

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Lecture 5: Research Claims & Validity PDF

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