About 68% of sixth-grade students will have heights between inches and inches.

It seems like there might be a slight misunderstanding or a typo in your question. Usually, when we talk about a percentage of a population falling within a certain range, like 68%, we are referring to a concept in statistics called the "empirical rule" or the "68-95-99.7 rule". This rule applies to normal distributions (oftentimes called bell curves), where approximately 68% of the data falls within one standard deviation of the mean.

For your question regarding sixth-grade students' heights, if we assume that their heights are normally distributed, we would need to know the mean (average) height and the standard deviation to provide a precise range. So, the sentence could be completed as follows: "About 68% of sixth-grade students will have heights between [mean - standard deviation] inches and [mean + standard deviation] inches."

For example, if the average (mean) height of the sixth-graders is 55 inches and the standard deviation is 3 inches, then: - The range where about 68% of sixth-grade students' heights would fall between [55 - 3] and [55 + 3] inches, which is between 52 and 58 inches.

Without the specific mean and standard deviation values, the exact range cannot be determined. The 68% indicates that we're talking about the distance from the mean within one standard deviation in a normal distribution, but without the actual data, we cannot fill in the specific values for "inches."

Extra: In statistics, the empirical rule is a handy way to understand the spread of data in a normal distribution. Normal distributions are symmetrical and have a bell-shaped curve. The empirical rule states:

- About 68% of data falls within one standard deviation of the mean. - About 95% of data falls within two standard deviations of the mean. - About 99.7% of data falls within three standard deviations of the mean.

The mean is the average of all data points, and the standard deviation is a measure of how spread out the numbers are. The higher the standard deviation, the more spread out the data is. In practical terms, understanding this rule helps you gauge quickly how much of your data falls near the average and how much is more extreme. For example, in a classroom if the students' heights are normally distributed, you can predict that most of the students (68%) will be within one standard deviation of the average height; very few (2.35% on either end of the distribution) will be more than two standard deviations above or below that average. This is a fundamental concept used in many fields that rely on statistical analysis, such as psychology, finance, and biology.