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In a Programming and AI Lab, Python can be used to perform statistical analysis of marks obtained in five subjects. Statistical measures such as average, minimum, maximum, and standard deviation help in understanding the overall academic performance and the variation in marks. Python provides simple built-in functions and libraries that make such calculations easy, accurate, and efficient. Suppose the marks obtained by a student in five subjects are 78, 65, 82, 71, and 90. These values can be stored in a Python list. The `statistics` module can then be used to calculate the average and standard deviation, while the built-in `min()` and `max()` functions can determine the lowest and highest marks. ```python import statistics # Marks obtained in five subjects marks = [78, 65, 82, 71, 90] # Calculate statistical values average = statistics.mean(marks) minimum = min(marks) maximum = max(marks) standard_deviation = statistics.stdev(marks) # Display the results print("Marks:", marks) print("Average:", average) print("Minimum:", minimum) print("Maximum:", maximum) print("Standard Deviation:", standard_deviation) ``` The first statement, `import statistics`, imports Python's standard `statistics` module. This module contains functions for performing common statistical calculations. In the program, the `mean()` and `stdev()` functions are used from this module. The statement `marks = [78, 65, 82, 71, 90]` creates a list containing the student's marks in five subjects. A Python list is useful because it allows multiple values to be stored in a single variable. The values can represent marks in subjects such as Programming, Mathematics, Artificial Intelligence, Database Management, and Computer Networks. The average is calculated using: ```python average = statistics.mean(marks) ``` The `mean()` function adds all the values and divides their sum _________ _____ ________ _________ _______ ___ ____ ______ __________ ________.
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