Research Methodology MCQs

A Teaching Method is an example of an independent variable because it can be manipulated by the researcher to observe its effect.

• Learning and Response are typically dependent variables, representing outcomes influenced by the independent variable.

Inductive reasoning moves from specific observations to broader generalizations, forming an inductive hypothesis.

• Deductive reasoning starts with a general theory, while research and non-directional hypotheses are types of statements, not reasoning processes.

Test scores are a classic example of a dependent variable, as they are the outcome measured and expected to change in response to an independent variable.

• Reward and Punishment are often independent variables or interventions.

A deductive hypothesis is derived from a general theory and then tested with specific observations.

• Inductive hypotheses move from specific observations to generalizations. Research and non-directional hypotheses are broader categories, not specific to theoretical derivation.

In Action Research, the researcher is actively involved in the setting or problem being studied, often to bring about practical change.

• Applied and Experimental research typically involve more detached observation or manipulation of variables.

Studying the "impact" of CAI on achievement implies a cause-and-effect relationship, which is the primary goal of Experimental Research.

• Action and Applied research have different primary objectives than establishing causality through manipulation.

A correlation coefficient, such as Pearson's r, ranges from -1.00 to +1.00. Positive values indicate a direct relationship, while negative values indicate an inverse relationship.

• Therefore, it encompasses both positive and negative ranges.

A correlation coefficient near +1.00 signifies a strong positive linear relationship. This means as one variable increases, the other variable also tends to increase proportionally.

• A negative coefficient indicates an inverse relationship.

The independent variable is the factor manipulated or changed by the researcher. It is the 'cause' (C) that produces an effect, the 'treatment' (B) applied in an experiment, and it 'antecedes' (A) the outcome. Therefore, all listed options are correct synonyms for an independent variable.

The dependent variable is the outcome measured, which is presumed to be 'effected' (C) by the independent variable. While 'Consequent' (A) is also a synonym, 'Effect' is a more direct and widely used term in research. 'Behavioural' (B) is too specific, as dependent variables can be non-behavioral.

For correlational research, a sample size of 30 subjects (A) is generally considered the minimum acceptable. This size helps ensure statistical power and representativeness, allowing for reliable correlation analysis. Smaller samples risk unreliable results, while larger samples (B, C, D) are not the *minimal* requirement.

Mortality, also known as attrition, occurs when participants drop out of a study, and their systematic absence significantly impacts the overall research findings.

This question directly addresses the authenticity and genuineness of the source, which is the primary focus of external criticism. External criticism aims to determine if a document or relic is original and not a forgery. Internal criticism assesses the accuracy and trustworthiness of the content.

Statistical regression occurs when subjects are selected based on extreme scores, and subsequent measurements tend to be closer to the average, impacting study validity.

refers to the consistency of data. This indicates how similar or aligned the findings are across different sources. Validity of data concerns whether it accurately measures what it intends to, and oral testimony is a type of evidence.

Instrumentation refers to inconsistencies or changes in the measuring tools or procedures during an experiment, which can compromise the reliability of the collected data.

Pre-experimental designs are characterized by a lack of random assignment and often no control group, offering minimal control over extraneous variables.

Quasi-experimental designs utilize pre-existing or naturally formed groups, lacking random assignment, which results in a less satisfactory degree of experimental control.

Quasi-experimental designs are employed when random assignment to treatment groups is not possible or practical, making them suitable for real-world settings.

True experimental designs utilize randomization to ensure equivalence between groups and control exposure to treatments, establishing cause-and-effect relationships effectively.

Action research typically has the least precision and control as it is conducted in real-world settings to solve immediate problems, often with limited rigor.

Basic research aims to expand fundamental knowledge. Animal models allow for highly controlled experiments and precise manipulation of variables, which is often ethically or practically impossible with human subjects, thus facilitating foundational scientific discoveries. Applied research focuses on practical problems.

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.

Deductive reasoning involves starting with a general principle or theory and applying it to specific cases to reach a logical conclusion. Conversely, inductive reasoning moves from specific observations to broader generalizations. Data analysis is a process, and a hypothesis is a testable statement.

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.