Commit fbc425bb authored by rhaase's avatar rhaase

added exercise solutions

parent 0820e4c9
import matplotlib.pyplot as plt
# data
mutant = [1, 3, 2, 1, 5, 7, 3, 5]
control = [6, 7, 1, 8, 3, 7, 8, 6]
# draw a box plot
data = [mutant, control]
fig1, ax1 = plt.subplots()
ax1.set_title('Basic Plot')
ax1.boxplot(data)
plt.show()
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measurements = [1, 7, 3, 4, 0, 5, 4, 2, 8, 7]
# determine sum of all measurements
sum = 0
for number in measurements:
sum = sum + number
# determine mean of all measurements
number_of_measurements = len(measurements)
mean = sum / number_of_measurements
print("Mean: " + str(mean))
# go through measurements again and calculate standard deviation
squared_sum = 0
for number in measurements:
squared_sum += pow(number - mean, 2) / number_of_measurements
from math import sqrt
standard_deviation = sqrt(squared_sum)
print("Standard deviation: " + str(standard_deviation))
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measurements = [1, 7, 3, 4, 0, 5, 4, 2, 8, 7]
import numpy as np
minimum = np.min(measurements)
print("Mean: " + str(minimum))
maximum = np.max(measurements)
print("Mean: " + str(maximum))
mean = np.mean(measurements)
print("Median: " + str(mean))
median = np.median(measurements)
print("Mean: " + str(median))
standard_deviation = np.std(measurements)
print("Standard deviation: " + str(standard_deviation))
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