Why should I generate random numbers for the indicators that we will be using?

<p id="isPasted">Generating random numbers for indicators is crucial because it ensures impartiality and avoids bias in your analysis. Using random numbers allows you to create a sample that is representative of the larger population, leading to more reliable and trustworthy results. It also helps in simulating scenarios and testing the robustness of your indicators, ensuring they perform consistently across different conditions.&nbsp;</p><p>Here's a more detailed explanation:</p><p>Eliminating Bias:</p><p>When manually selecting data points for your indicators, you might unconsciously introduce bias based on your expectations or preferences. Random number generation removes this subjective element, leading to a more objective assessment. According to ScienceDirect.com, a random sample is chosen by chance and could potentially be unrepresentative of the population, but this is preferable to introducing bias.&nbsp;</p><p>Representativeness:</p><p>Random sampling ensures that every data point in the population has an equal chance of being included in your sample. This increases the likelihood that your indicators will accurately reflect the characteristics of the overall population you are studying, says ScienceDirect.com.&nbsp;</p><p>Simulation and Testing:</p><p>Random numbers are essential for simulating various scenarios and testing the behavior of your indicators under different conditions. This helps you identify potential weaknesses or limitations in your indicators before deploying them in real-world applications.&nbsp;</p><p>Reproducibility:</p><p>Using a specific seed value with a random number generator allows you to reproduce the same sequence of random numbers, which is vital for debugging and ensuring the repeatability of your analysis.&nbsp;</p><p>Statistical Validity:</p><p>Random sampling is a cornerstone of statistical inference. It allows you to apply statistical tests and draw meaningful conclusions about your data with a higher degree of confidence.&nbsp;</p>