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In the study of statistics, understanding the difference between a 'parameter' and a 'statistic' is essential. A parameter is a numerical characteristic that summarizes a feature of an entire population. In contrast, a statistic describes a characteristic of a sample, a subset of the population. In other words, parameters pertain to a complete set of data, while statistics are derived from a portion of that data.

For instance, if you were to measure the mean height of all basketball players worldwide, that number would be a parameter because it would include every relevant individual. However, if you measured the mean height of just a small group of players intended to represent the larger group, the resulting average would be considered a statistic.

Applying this to our NCAA basketball example, the mean height of 77 inches is a parameter since it is based on the entire population of NCAA basketball players for the 2017 season, not a selected sample.

The term 'population' in statistics refers to the totality of items or individuals about which information is sought. Essentially, it's the complete set that we want to analyze or describe. In the context of our example, the population is all 5,341 NCAA basketball players from the 2017 season.

When researchers gather data from every individual within a population, the results can often be considered definitive give the context of the question. However, for extremely large populations, it may not be feasible to include every individual, and sampling is used instead. It's critical to accurately define the population before collecting data, as it directly influences the relevance and the interpretation of the findings.Knowing the population helps to establish the scope of the study and is crucial for calculating accurate parameters.

Calculating the mean height involves adding up all the individual heights and dividing by the total number of players. It gives us a central value that can represent the average height of the group. This calculation is straightforward:

1. Add together the height of every player.
2. Count the total number of players.
3. Divide the total height by the number of players.

In mathematical terms, this can be expressed as the formula \[ \text{Mean Height} = \frac{\text{Sum of all heights}}{\text{Total number of players}} \] The mean height provides us with a useful piece of information about the population, as it is a measure of central tendency, showing where the middle ground lies in terms of height for NCAA players. For the 2017 season, using the process above, the mean height was determined to be 77 inches for the population of NCAA basketball players.