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In this case, we create a frequency table using class interval, shown as follows:
Class Interval Tally Frequency
0-10 0
11-20 / 1
21-30 0
31-40 // 2
41-50 //// / 6
51-60 /// //// 8
61-70 /// 3
71-80 / 1
81-90 //// 4
91-100 0
Total 25 25
Graphs and Shapes of Distributions
Data can be summarized through various methods such as data matrices, frequency tables, or graphs. In graphs, the
data points are distributed throughout the chart. These distributions show the extent (dispersion, variability, scatter) of
the data. The extension can be stretched (over a larger area) or compressed (over a narrower area).
Here we learn about data distribution and the importance of the distribution. The shape of a distribution is described by
its number of peaks and their symmetry, their tendency to skew, or their uniformity.
The distribution shape shows:
• spread of the data i.e., scatter, variance, etc.
• where the mean lies in the data distribution
• range of the dataset
Distributions that are skewed have more data points plotted on one side of the graph than on the other.
Shapes of distribution are determined by factors such as:
Number of Peaks
The peaks are usually called modes. The mode represents that the data count is higher in some areas than in other areas
of the graph.
• A unimodal distribution has a single peak or mode. The single peak can have different shapes (e.g., very high and
thin or short and fat). One of the most common types of unimodal distributions is the normal distribution (single
peak at the centre), also called the “bell curve” because its shape resembles a bell.
• A bimodal distribution has two peaks or modes.
• A multimodal distribution has three or more peaks.
Mode First mode Second mode Mode Mode Mode
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