The number of bins for a histogram is typically chosen based on the square root rule, which suggests that the number of bins should be the square root of the number of data points. In this case, the square root of 100 is 10, so around 10 bins would be a reasonable choice.

However, the number of bins can also be chosen based on the data distribution and the level of detail you want to see. It's not a hard and fast rule, but generally, you want to avoid having too few or too many bins.

Too few bins (like 1 bin) might oversimplify the data and miss important details. On the other hand, too many bins (like 100 or more) might overcomplicate the data and make the histogram difficult to interpret.

So, out of the options given (1, 7, 15, 9), 1 would NOT be a reasonable number of bins for this histogram.

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The number of bins for a histogram is typically chosen based on the square root rule, which suggests that the number of bins should be the square root of the number of data points. In this case, the square root of 100 is 10, so around 10 bins would be a reasonable choice.

However, the number of bins can also be chosen based on the data distribution and the level of detail you want to see. It's not a hard and fast rule, but generally, you want to avoid having too few or too many bins.

Too few bins (like 1 bin) might oversimplify the data and miss important details. On the other hand, too many bins (like 100 or more) might overcomplicate the data and make the histogram difficult to interpret.

So, out of the options given (1, 7, 15, 9), 1 would NOT be a reasonable number of bins for this histogram.

Knowee AI · Accepted Answer

The number of bins for a histogram is typically chosen based on the square root rule, which suggests that the number of bins should be the square root of the number of data points. In this case, the square root of 100 is 10, so around 10 bins would be a reasonable choice.

However, the number of bins can also be chosen based on the data distribution and the level of detail you want to see. It's not a hard and fast rule, but generally, you want to avoid having too few or too many bins.

Too few bins (like 1 bin) might oversimplify the data and miss important details. On the other hand, too many bins (like 100 or more) might overcomplicate the data and make the histogram difficult to interpret.

So, out of the options given (1, 7, 15, 9), 1 would NOT be a reasonable number of bins for this histogram.

If we have 100 data points that we wish to place into a histogram, which of the following would NOT be a reasonable number of bins for this histogram?1 point1071159

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