1. why is it important to take many random samples when collecting population or biodiversity data? support…

Brief Explanations:

Taking many random samples helps reduce sampling bias. A single sample might not be representative of the entire population or biodiversity. For example, if studying plant biodiversity in a forest, a single sample could be in an area with more sunlight (unusual for the whole forest) and have different plant species. Multiple random samples average out such anomalies. Also, the law of large numbers in statistics (a concept related to data collection in natural science - biology here) states that as the number of samples increases, the sample mean (or in this case, the representation of the population/biodiversity) approaches the true population mean. So, more samples give a more accurate picture.

Answer:

Taking many random samples is important as it reduces sampling bias and, by the law of large numbers (a statistical concept relevant to data collection in natural science - biology), gives a more accurate representation of the population or biodiversity. Evidence: A single sample can be an outlier (e.g., a non - typical area in a forest for plant biodiversity study), multiple samples average out such non - representative cases.