Respuesta :
Answer:
1) Count the number of data points .
2)Determine the range of the sample - the difference between the highest and lowest values.
3))Determine the number of class intervals.
You can use either of two methods as general guidelines in determining the number of intervals:
A. Use 1010 intervals as a rule of thumb.
B. Calculate the square root of the number of data points and round to the nearest whole number. In the case of our height example, the square root of 5050 is 7.077.07, or 77 when rounded.
4)You may wish to experiment with different interval numbers. If there are too many, the distribution will spread out, and the histogram will look flat. Likewise, if there are too few intervals, the distribution can look artificially tight.
Determine the interval class width by one of two methods:
A. \text{Width} = \dfrac{\text{Range}}{\# \text{of Intervals}} = \dfrac{8.1}{10} = 0.81Width=
#of Intervals
Range
=
10
8.1
=0.81
B. Divide the Standard Deviation by three. In this case, the height data has a Standard Deviation of 1.851.85, which yields a class interval size of 0.620.62 inches, and therefore a total of 1414 class intervals (Range of 8.18.1 divided by 0.620.62, rounded up). This is slightly more class intervals than our rule of thumb indicated.
Develop a table or spreadsheet with relative frequencies for each interval, which becomes a tabular histogram:
