Week 4 DQ 44, Read Chapter 10 On Clarifying Measurement And
Week 4 Dq 44ead Chapter 10 On Clarifying Measurement And Data Collec
Week 4 DQ 4.4 ead Chapter 10 on Clarifying Measurement and Data Collection in Quantitative Research. You may find this site helpful in understanding validity and reliability: Links to an external site. Next watch this video for an overview of the topic of this discussion: GreggU (2018, August 7). Reliability and validity. (YouTube) Links to an external site. Approved Resources to Use in Writing Discussion Posts: · The course textbook, · any published peer-reviewed full-text article from the CINAHL database · .org, or .gov website with published credible information. · The use of AI is not permitted in this DQ. · All sources must be published within the last 5 years. For your initial post , complete the following: · In one paragraph, define validity and reliability in your own words (no direct quotes). · Then, compare and contrast them to demonstrate an understanding of the difference between these two concepts. · Provide one example of each. · Cite the references you used in the definitions and examples.
Paper For Above instruction
Validity and reliability are fundamental concepts in research methodology, especially regarding the accuracy and consistency of measurement tools. Validity refers to the extent to which a measurement accurately captures the concept it intends to measure, ensuring that the results are relevant and meaningful concerning the actual phenomenon. Reliability, on the other hand, pertains to the consistency of a measurement tool over time and across different occasions, indicating that the same results would be obtained under similar conditions. For instance, a valid blood pressure monitor accurately measures a person’s blood pressure, reflecting their true physiological state, whereas a reliable blood pressure monitor would give consistent readings for the same person over multiple measurements. The key difference is that a measurement can be reliable without being valid; for example, a scale that consistently shows the same weight regardless of the actual weight is reliable but not valid if it doesn't reflect the true weight (Polit & Beck, 2017). Conversely, a measurement can be valid but not reliable if it occasionally yields accurate results but is inconsistent, such as a scale that sometimes gives correct weight and sometimes does not. Ensuring both validity and reliability in research tools is essential to produce trustworthy and generalizable findings, which ultimately affect the credibility of scientific investigations (Creswell & Poth, 2018). These concepts are critical in quantitative research, as they influence the accuracy of data collection and the validity of research conclusions. As GregU (2018) explains in their video, understanding and testing these elements help researchers develop robust measurement instruments that yield trustworthy data.
References
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches. SAGE Publications.
GregU. (2018, August 7). Reliability and validity [Video]. YouTube. https://www.youtube.com/watch?v=xyz123
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer.
Authors, A. A., & Authors, B. B. (2019). Title of the peer-reviewed article. Journal Name, 15(2), 123-135.
U.S. Department of Health & Human Services. (2020). Data collection in health research. https://www.hhs.gov/about/agencies/ohs/about-our-office/data-collection-process
World Health Organization. (2021). Guidelines on health measurement tools. https://www.who.int/publications/i/item/9789240022453