diff --git a/09_Scientific_Data_Analysis_Python/exercises/box_plot.py b/09_Scientific_Data_Analysis_Python/exercises/box_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..eefd0c784f8105ddbe45b1892bb7c8f2744c4b75
--- /dev/null
+++ b/09_Scientific_Data_Analysis_Python/exercises/box_plot.py
@@ -0,0 +1,14 @@
+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()
\ No newline at end of file
diff --git a/09_Scientific_Data_Analysis_Python/exercises/stats_for_loop.py b/09_Scientific_Data_Analysis_Python/exercises/stats_for_loop.py
new file mode 100644
index 0000000000000000000000000000000000000000..fd176e1d59f392319b73c0d2d3df276ab8d1e718
--- /dev/null
+++ b/09_Scientific_Data_Analysis_Python/exercises/stats_for_loop.py
@@ -0,0 +1,23 @@
+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))
\ No newline at end of file
diff --git a/09_Scientific_Data_Analysis_Python/exercises/stats_numpy.py b/09_Scientific_Data_Analysis_Python/exercises/stats_numpy.py
new file mode 100644
index 0000000000000000000000000000000000000000..53db3ee62795821130f95d9c2824b4f9d775a98d
--- /dev/null
+++ b/09_Scientific_Data_Analysis_Python/exercises/stats_numpy.py
@@ -0,0 +1,19 @@
+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))
\ No newline at end of file