One type of Error involves rejecting the positive side of a problem, for example, a disease, which is called false positive, and another type of error, on the other hand, involves failing to reject negative side of the disease, known as a false negative. However, confusion arises because it doesn’t align with usual concerns about error. To address this point, we have introduced new terms including sensibility and specificity. Sensibility refers to the ability to correctly identify a positive case and specificity refers to the ability to correctly identify a negative case.
On one hand, sensibility guides us to effectively identify and validate instances where something went wrong or is considered a mistake. On the other hand, we use specificity to accurately determine and work towards what is right. Both play a crucial role in decreasing loss to an acceptable level. When building a model, we expect the model to fit well to achieve the goal of consistency and high quality, which we will reduce noise of randomness due to irrelevant information. It is essential to address the error through sensitivity, ensuring that mistakes or abnormalities are identified properly. Conversely, we thrive in lessening the false negative rate to achieve the goal of specificity, ensuring that genuine positives or normal instances are not overlooked. By considering the balance of the principle of sensitivity and specificity, we are now ready to work towards normality and accuracy in our model analysis.
I first encountered the error problem was five years ago when working with college students Statistics. It became apparent that many students struggled with understanding errors throughout their semester. I, too, found a challenging situation in explaining the concepts to the students successfully. Confusion surrounding the concept is common among learners, and often stems from their learning styles regarding the concept. Many often attempt to memorize the definition to grasp knowledge quickly, but our memory has a limitation. Simply memorizing without a deep understanding hinders our true comprehension and application. To overcome these challenges, we need to explore strategies with specificity. The majority prefer to learn information straightforwardly, akin to sit in a train with mostly empty seats. However, our brain doesn’t work simply like a train, but engaging in cognitive processes that allows us to transform and integrate new information with existing knowledge, facilitating a deeper level understanding and memorization. In truth, the learning process extends the straightforward, enabling deep learning and long-term retention.
The understanding of error can be visualized as a network of interconnected concepts with the core part being types of errors. Furthermore, through the tools of sensitivity and specificity, we address the errors, in a context of a larger size data realization, which provides us richer information to identify and rectify error problems effectively. By considering these criteria alongside the concept of error, we navigate the analysis to the large size dataset, enabling us to make informed decisions, iteratively, to address and to rectify.
I feel comfortable about the concepts of false positive and false negative as well as their associations. However, understanding errors is a crucial aspect that is intricately connected to hypothesis and applications of theorems such as the Bayesian theorem. This understanding imbues our knowledge with meaning about errors. emphasizing the significance of consistency regardless of the time spent in the learning process. At each stage of becoming aware of the meaning of errors, bias is inevitable, but we endeavor to minimize its negative impact. Bias, often associated with randomness, can undermine our confidence, and reduce confirmation of our entrenched beliefs. Consequently, we may also be less confident than we were initially, which is a disadvantage.
Again, what is the disadvantage of learning concepts of the errors by memorization? Many adult students seeking help often express concerns about their age, believing memorization is more challenging for them compared to those younger individuals. The direct consequence of simply relying on memorization is that their learning suffers. Thus, solely depending on memorization approach isn’t reliable in the long run.
Nevertheless, it is important to recognize understanding the concepts requires a learning process. Throughout this process, we gather information from various sources, which may not always align with our initial expectations. Though it may seem frustrating at first, eventually, we will find they are valuable but in a different time. Finally, a brief comment about the application of teaching errors: we experience a sense of freedom through the journey from the beginning to the ending, as well as the process of coming and going.
