Frequency, Association, and Causal Claims

Questions and Answers

What is a variable?

What we're looking at measuring, has levels/values.

What is a constant?

Has only one level. What you use to compare.

What are measured variables?

Are simply observed and recorded.

What are manipulated variables?

What is controlled by assignments. Signup and view all the answers

What are demographic variables?

Like age, race, etc. Can't be measured, while variables like school quality are unethical to manipulate. Signup and view all the answers

What are conceptual variables?

Abstract terms that require conceptual definitions for understanding. Signup and view all the answers

What is a conceptual definition?

A researcher's definition of a variable at the theoretical level. Signup and view all the answers

What are operational variables?

Used when doing empirical research so the concept can be measured/manipulated. Signup and view all the answers

What is a frequency claim?

Claims about the %/rate/proportion of an event based on data. Signup and view all the answers

What is an association claim?

Suggests a relationship between 2 variables, no causation. Signup and view all the answers

What is a causal claim?

Indicates one variable causes another. Signup and view all the answers

What are the four big validities?

Construct, external, statistical, internal. Signup and view all the answers

What does validity refer to?

Appropriateness of the conclusion/decision. Signup and view all the answers

What is construct validity?

Refers to how well a conceptual variable is operationalized. Signup and view all the answers

What is reliability?

The measure yields similar results on repeated testings. Signup and view all the answers

What is external validity?

How well the results generalize to other contexts or populations. Signup and view all the answers

What is statistical validity (frequency claims)?

The extent to which a study's statistical conclusions are accurate. Signup and view all the answers

What is margin of error?

A statistical figure that attempts to include the true value in the population. Signup and view all the answers

What is statistical validity?

The extent to which the statistical conclusions are accurate and reasonable. Signup and view all the answers

What is statistical significance?

A statement of how likely it is that an obtained result occurred by chance. Signup and view all the answers

What is a Type 1 error?

A study might conclude an association exists when it does not in the full population. Signup and view all the answers

What is a Type 2 error?

A study might mistakenly conclude there is no association when there actually is. Signup and view all the answers

What are the three criteria for causation?

Covariance, temporal precedence, internal validity. Signup and view all the answers

What is covariance?

The extent to which two variables are observed to go together. Signup and view all the answers

What is temporal precedence?

One variable must come first in time for causation to be considered. Signup and view all the answers

What is internal validity?

Indicates a study's ability to eliminate alternative explanations for the association. Signup and view all the answers

What is manipulation in research?

Assigning participants to different levels of the experiment. Signup and view all the answers

What is statistical validity (causal claims)?

Measures the strength of the causation relationship. Signup and view all the answers

Study Notes

Key Definitions and Concepts

Variable: Measurable element with multiple levels or values.
Constant: Element having only one level; used for comparison purposes.
Measured Variable: Observed and recorded, reflecting real-life data.
Manipulated Variables: Controlled variables assigned by the researcher to establish causation.

Variable Types

Demographic Variables: Include age, race, etc.; cannot be ethically manipulated, unlike measurable variables.
Conceptual Variables: Abstract concepts, such as "time spent socializing" and "school achievements," requiring theoretical definitions for clarity.
Conceptual Definition: The theoretical expression of a variable defined by the researcher.
Operational Variables: Used in empirical research to measure or manipulate concepts of interest.

Types of Claims

Frequency Claim: Describes the percentage or rate of an event, based purely on data, without suggesting an association.
Association Claim: Indicates a relationship between two variables but does not imply causation; typically supported by correlational studies.
Causal Claim: Suggests that one variable directly influences another. For a valid causal claim:
- Must show temporal precedence.
- The causal variable must precede the outcome variable.
- Must rule out alternative explanations for the relationship.

Validity in Research

Four Big Validities: Construct, external, statistical, and internal validity.
Validity: The accuracy and justifiability of conclusions drawn from research.
Construct Validity: Assesses how well a conceptual variable is operationalized and measured. Reliable measurements are essential.
Reliability: The consistency of results upon repeated testing.
External Validity: Indicates how well study results generalize to broader populations and contexts.
Statistical Validity (Frequency Claims): Evaluates the accuracy and reasonableness of statistical conclusions; varies based on specific claims.

Statistical Analysis Concepts

Margin of Error: Accompanies frequency claims, representing a statistical estimate based on sample size, to indicate the accuracy of population assumptions.
Statistical Significance: A measure of the likelihood that results occurred by chance.

Errors in Research

Type 1 Error: False positive; concludes an association exists between variables when none exists in the population.
Type 2 Error: False negative; fails to detect an existing association in the sample.

Criteria for Causation

Covariance: Assess the extent to which two variables vary together.
Temporal Precedence: Establishes the order of variables, confirming which one occurred first.
Internal Validity: Determines a study's capacity to eliminate alternative explanations for observed associations.

Causal Research Methodology

Manipulation: Essential for establishing causal claims, involving the assignment of participants to different conditions (treatment vs. control).
Statistical Validity (Causal Claims): Evaluates the strength of causal relationships, including statistical significance and standard deviation among groups.

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Description

Test your understanding of key concepts in research such as variables, constants, and demographic data. This quiz will help reinforce your knowledge of how these elements interact in frequency and causal claims. Ideal for students studying psychology or social sciences.