WHICH DATA LANDMARK BEST REPRESENTS THE NUMBER OF HOURS A TYPICAL STUDENT WATCHES TELEVISION-- THE MEAN, MEDIAN, OR MODE
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WHY? ____________________________________________________________________________________________________________________________________________________________
"typical" student? I have never met a typical student.
Consider what the mode means.
thanks so much!!!1 and by the way i didn't make the question about typical student if you have a problem about the part typical student you can go to the university of chicago lol im kidding!
To determine which data landmark best represents the number of hours a typical student watches television, we need to understand what each of the measures – mean, median, and mode – represents.
1. Mean: The mean is the average of a set of numbers. To calculate the mean, you add up all the values in the data set and then divide by the number of values. It is sensitive to extreme values.
2. Median: The median is the middle value when the data set is arranged in order. If there is an even number of data points, the median is the average of the two middle values. It is not affected by extreme values.
3. Mode: The mode is the value that appears most frequently in the data set. A data set can have no mode, one mode, or multiple modes.
Now, considering these definitions, let's examine which measure would best represent the number of hours a typical student watches television:
If we have data on the number of hours each student watches television and there are no extreme values or outliers, the mean would likely be a good representation. However, if there are a few students who watch television for an excessive number of hours, the mean could be significantly influenced by these outliers.
If we have a data set where the number of hours a student watches television is reasonably distributed, the median would potentially be the best representation. The median is not affected by extreme values, so it provides a more robust measure for a typical student's viewing hours.
The mode would be useful if we are interested in the most frequently occurring number of hours a student watches television. However, it might not necessarily represent the overall typical value if the distribution of hours is spread out with no clear mode.
Taking all this into consideration, the best data landmark to represent the number of hours a typical student watches television would typically be the median, as it is a more robust measure that is unaffected by extreme values.