Quasi-experimental designs are employed when random assignment to treatment groups is not possible or practical, making them suitable for real-world settings.
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Quasi-experimental designs utilize pre-existing or naturally formed groups, lacking random assignment, which results in a less satisfactory degree of experimental control.
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Pre-experimental designs are characterized by a lack of random assignment and often no control group, offering minimal control over extraneous variables.
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Instrumentation refers to inconsistencies or changes in the measuring tools or procedures during an experiment, which can compromise the reliability of the collected data.
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Statistical regression occurs when subjects are selected based on extreme scores, and subsequent measurements tend to be closer to the average, impacting study validity.
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Mortality, also known as attrition, occurs when participants drop out of a study, and their systematic absence significantly impacts the overall research findings.
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External validity describes the degree to which experimental results can be generalized to other populations, settings, and real-world situations beyond the study's specific context.
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The correct answer is Maturation. This term describes the internal physical or mental changes that naturally occur within subjects over time, independent of any experimental intervention. These changes, such as growing older, becoming more experienced, or simply getting tired, can influence the study's outcomes and pose a threat to internal validity if not accounted for. In contrast, Internal Validity refers to the study's ability to establish a causal link, while External Validity concerns generalizability. History refers to specific external events affecting participants during the study, not internal changes.
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Internal Validity (A) refers to the extent to which a study establishes a trustworthy cause-and-effect relationship, meaning the observed results are solely due to the manipulated independent variable and not extraneous factors. External Validity (B) concerns generalizability, while Maturation (C) and History (D) are threats to internal validity.
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Randomization (D) is the process in which every member of a population has an equal chance of being selected for a sample or assigned to a group. This minimizes bias and helps ensure that groups are comparable, increasing the study's validity. The other options are different research concepts.
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Replication (B) involves repeating a study, often through a number of smaller experiments, to confirm findings and enhance their reliability and generalizability across different contexts or samples. Manipulation (A), Control (C), and Randomization (D) are different experimental procedures.
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Manipulation (A) is the process of intentionally varying or introducing the independent variable to observe its effect on the dependent variable. This is a core component of experimental research. Control (C), Replication (B), and Randomization (D) are distinct research techniques, not the act of using an independent variable.
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Control (C) refers to the researcher's efforts to minimize or eliminate the influence of extraneous variables, ensuring that observed effects are solely due to the independent variable. Manipulation (A) is changing the independent variable, Replication (B) is repeating studies, and Randomization (D) is for group assignment.
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The dependent variable is the outcome measured, which changes in response to the independent variable's manipulation. The independent variable is what the researcher changes. Distractors are incorrect as they misidentify these fundamental experimental components.
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An Independent Variable is the activity or characteristic manipulated by the researcher, believed to cause a difference in another variable; it's the presumed cause. The Dependent Variable is the effect. Behavioural variable and Consequent are not the precise terms for the manipulated cause.
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A Variable is any condition or characteristic that can vary and is controlled, manipulated, or observed by the experimenter. Response, Effect, and Reward are specific outcomes or aspects related to variables, but "variable" is the fundamental term for what is measured or changed.
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The relationship between intelligence and self-esteem is studied via Correlational research, which examines the statistical relationship between two or more variables without implying causation. Causal comparative, Applied, and Descriptive research have different primary objectives, not solely identifying variable relationships.
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Lack of randomization, manipulation, and control are inherent weaknesses in Causal comparative research. Researchers cannot assign subjects or manipulate variables, making definitive cause-effect difficult. Basic and Action research have different methodological limitations, not these specific ones related to pre-existing groups.
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Causal comparative research (ex post facto) begins with an observed effect and retrospectively seeks its possible causes by examining existing group differences. Applied and Action research solve practical problems, while Descriptive research describes current status, not cause-effect from an effect.
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Survey research commonly collects data from a sample using questionnaires or interviews to describe population characteristics. Causal comparative, Action, and Applied research employ diverse methods, but surveys are specifically characterized by these direct data collection tools.
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Descriptive research aims to describe the current characteristics of a population or phenomenon, focusing on "what is." Basic research expands knowledge, Applied solves practical problems, and Causal comparative investigates past cause-effect relationships, none primarily describing current status.
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In Historical research, data analysis is primarily logical, involving reasoning, interpretation, and synthesis of evidence to form a coherent narrative. It is not predominantly Statistical, which quantifies data. While some quantification may occur, the core analytical approach remains qualitative and logical.
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In Historical research, data analysis primarily involves criticism (external for authenticity, internal for credibility) to ensure source validity. Tools, Motives, and Instruments relate to data collection or interpretation, but not the core method for validating historical information.
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Historical research systematically collects and evaluates past data to understand events. Studying past resources directly aligns with this. R and D focuses on new products, Evaluation assesses worth, and Basic research expands theoretical knowledge, none of which primarily study the past.
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The question
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