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Inspection Method
MODE (Individual Series): Inspection
Method
Marks Marks
2 2
Two times
5 2
7 3 One time
Arrange the data in ascending order
5 5
6 5 Three times
2 5 On inspection of the data it is clear
that the value ‘7’ occurs maximum
5 6 number of times in the series i.e. 4
One time
7 7 times
3 7
Hence, Mode = 7
7 7 Four times
7 7
Mode calculation using Python
Program 3: To calculate the mode of 25 students weight.
50.5, 55.2, 60.3, 65.8, 70.1, 75.6, 80.4, 85.7, 90.2, 95.5, 50.3, 55.8, 60.1, 65.4, 70.9, 75.2, 80.6, 85.3, 90.8,
95.1,50.7, 55.9, 60.5, 65.2, 70.4
import statistics
# New list of weights for 25 students (with mode intentionally set to 60.5)
weights = [50.5, 55.2, 60.3, 65.8, 70.1, 75.6, 80.4, 85.7, 90.2, 95.5,
50.3, 55.8, 60.5, 65.4, 70.9, 75.2, 80.6, 85.3, 90.8, 95.1,
50.7, 55.9, 60.5, 65.2, 70.4]
# Calculate the mode weight using statistics.mode()
mode_weight = statistics.mode(weights)
# Print the mode weight
print("Mode weight of 25 students is:", mode_weight)
Output:
Mode weight of 25 students is: 60.5
When to use mean, median and mode:
Mean Median Mode
Data is Normally Distributed: Skewed Data: The median is Categorical Data: The mode is
The mean is informative when better than the mean for skewed the only measure that can be used
data follows a normal distribution, distributions because it is not for categorical (nominal) data,
as it provides a good central affected by extreme values. indicating the most common
point. category.
288 Touchpad Artificial Intelligence (Ver. 3.0)-XI

