Python Programming: An Introduction to Computer Science
Python Programming: An Introduction to Computer Science
3rd Edition
ISBN: 9781590282779
Author: John Zelle
Publisher: Franklin Beedle & Associates
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Chapter 7, Problem 3D

a)

Program Plan Intro

Given program:

#Get three values from the user using input()

a, b, c = eval( input('Enter three numbers : ' ) )

#Check whether the value of "a" is greater than "b"

if a > b :

    #Check whether the value of "b" is greater than "c"

    if b > c :

        #Print the string

        print("Spam Please!" )

    #Otherwise

    else :

        #Print the string

        print("It's a late parrot!" )

#Check whether the value of "b" is greater than "c"

elif b > c :

    #Print the string

    print("Cheese Shoppe" )

    '''Check whether the value of "a" is greater than or equal to "c"'''

    if a >= c :

        #Print the string

        print("Cheddar" )

    #Check whether the value of "a" is less than "b"

    elif a < b :

        #Print the string

        print ("Gouda" )

    #Check whether the value of "c" is equal to "b"

    elif c == b :

        #Print the string

        print("Swiss" )

#Otherwise

else :

    #Print the string

    print("Trees" )

    #Check whether the value of "a" is equal to "b"

    if a == b :

        #Print the string

        print("Chestnut" )

    #Otherwise

    else :

        #Print the string

        print ("Larch" )

#Print the string

print ("Done" )

b)

Explanation of Solution

Given input:

3, 3, 3

Output:

c)

Explanation of Solution

Given input:

5, 4, 3

Output:

d)

Explanation of Solution

Given input:

3, 5, 2

Output:

...

e)

Explanation of Solution

Given input:

5, 4, 7

Output:...

f)

Explanation of Solution

Given input:

3, 3, 2

Output:

...

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Can you help me solve this problem using Master's Theorem:Solve the recurrence relation f(n) = 3af(n/a) + (n + a)2 with f(1) = 1 and a > 1 byfinding an expression for f(n) in big-Oh notation.
here is example 7.6## Example 7.6 Suppose the sample population is χ 2 (2), which is non-normal but with same variance 4. ▶ Repeat the simulation, but replacing the N(0, 4) samples with χ 2 (2) samples. ▶ Calculate the empirical confidence level.(Empirical confidence level) n <- 20 alpha <- 0.05 UCL <- replicate(1000, expr = { x <- rchisq(n,df=2) (n-1)*var(x)/qchisq(alpha,df=n-1) }) sum(UCL >4) mean(UCL > 4) ## t.test function n <- 20 x <- rnorm(n,mean=2) result <- t.test(x,mu=1) result$statistic result$parameter result$p.value result$conf.int result$estimate
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