This is where you reflect on the quality of the investigation.
Consider how quality the design and production was and how it contributes to reliability of data
Consider the reliability of collected data (outliers, spread, error) and how it may affect the quality of conclusion
Answer your Research Question, considering the data collected and the evaluation into the quality of the products and the data.
In reflecting on the quality of the investigation, the design and production of the study should be evaluated. The design refers to the structure and methodology employed, while the production refers to the execution and implementation of the study. Ideally, a well-designed and executed investigation enhances the reliability of the data collected.
The design and production of the investigation should ensure that the research question is effectively answered. The methods chosen should be appropriate and relevant to the question, enabling the collection of useful data. For example, if the research question aims to investigate the effects of a new medication on a specific condition, a well-designed and produced study would incorporate control groups, randomization, and standardized protocols to minimize biases and confounding variables.
The reliability of the collected data is crucial in drawing accurate and valid conclusions. Data reliability is assessed by examining outliers, spread, and errors. Outliers are data points that are significantly different from the majority, and their presence may indicate potential issues with data collection or measurement. If outliers are not justified and are not accounted for appropriately, they can skew the data and affect the quality of conclusions drawn.
The spread of the data, referring to the variability or dispersion among the different data points, should also be considered. If the spread is too large, it may indicate a lack of consistency or precision in data collection. Conversely, if the spread is too small, it may suggest a potential limitation in the comprehensiveness of the investigation.
Errors can arise from various sources, including measurement errors, sampling errors, or data entry errors. It is essential to consider the nature and extent of these errors, as they can impact the accuracy and reliability of the results. Proper statistical analysis techniques may help identify and address these errors appropriately.
In answering the research question, the evaluation of the quality of the products and the data becomes pertinent. If the design and production of the investigation were of high quality, incorporating appropriate methods and minimizing biases and errors, the reliability of the data is enhanced. However, if the research question is not effectively answered due to limitations in the design and production, the quality of the conclusions drawn may be compromised.
In summary, reflecting on the quality of the investigation involves assessing the design and production of the study and how it contributes to the reliability of the data. Additionally, evaluating the reliability of the collected data, including outliers, spread, and errors, is important in determining the quality of the conclusions drawn. It is only by considering these factors collectively that one can confidently answer the research question using the data collected.