Which One Of The Following Types Of Variables Is Most Diffic

Question

Which One Of The Following Types Of Variables Is Most Difficult To Eva Which one of the following types of variables is most difficult to evaluate objectively in a true experiment? Explain why you think that (See instructions below). a) Dependent variable b) Independent variable c) Confounding variable d) Extraneous variable e) None of the above Instructions: Make selection, provide a concept definition (text), and support your opinion on the selection with an example from research that illustrates the concept. Do so in a maximum of 250 words. Make use of the participation rubric, found in the Instructor Policy document, as a personal checklist. By answering this question and wrestling with answers given from peers, we ought to achieve a level of UOPX Learning Objectives/competencies 4.1 and 4.2.

Dr. Jack HW Helper · Accepted Answer

Introduction In conducting true experiments, researchers aim to establish causal relationships between variables. Among the various types of variables, some are more challenging to evaluate objectively due to inherent characteristics and potential confounding factors. This paper will argue that confounding variables are the most difficult to evaluate objectively in a true experiment, supporting this claim with relevant research examples. Definition of Key Variables A confounding variable is an extraneous factor that influences both the independent and dependent variables, potentially skewing the results (Shadish, Cook, & Campbell, 2002). Unlike independent or dependent variables, which are manipulated and measured respectively, confounding variables are uncontrolled factors that threaten internal validity by introducing alternative explanations for the observed effects. Why Confounding Variables Are Most Difficult to Evaluate Confounding variables are inherently difficult to evaluate objectively because their influence is often subtle and unnoticed during the experiment. Researchers may inadvertently overlook subtle confounders or fail to control for them adequately, leading to biased results. For example, in a study examining the effect of a new teaching method on student achievement, variables such as prior knowledge, motivation, or classroom environment can act as confounders (Cook & Campbell, 1979). These factors can influence outcomes independently of the teaching method, complicating the attribution of effects solely to the independent variable. Research Illustration A notable example is the 1960s research on the effects of vitamin A on health outcomes. Initial studies suggested a protective effect, but subsequent analyses revealed confounding variables such as socioeconomic status and overall nutritional intake influenced the results. Properly identifying and controlling for confounders is essential but challenging, illustrating the difficulty inheren

Which One Of The Following Types Of Variables Is Most Diffic ✓ Solved

Which One Of The Following Types Of Variables Is Most Difficult To Eva

Sample Paper For Above instruction

Introduction

Definition of Key Variables

Why Confounding Variables Are Most Difficult to Evaluate

Research Illustration

Conclusion

References