Solve the following recurrence relations: (find an asymptotic
upper bound O(?) for each one)
a. T(n) = T(2n/3)+T(n/3) + n^2
b. T(n) = √nT(√n) + n
c. T(n) = T(n-1)+T(n/2) + n
The base case is that constant size problems can be solved in
constant time (O(1)). You can use the induction, substitution or
recursion tree method
Give asymptotic upper and lower bounds for T(n). Assume that
T(n) is constant for n <= 2.
Make your bounds as tight as possible, and justify your
answers.
T(n) = T(n-2) + n^2
Use a recursion tree to determine a good asymptotic upper bound
on the recurrence T(n) = 2T(n/3) + 2n.
Use the substitution method to verify your answer
Write a program in JAVA that prompts the user for a lower bound
and an upper bound. Use a loop to output all of the even integers
within the range inputted by the user on a single line.
(Lower bound for searching algorithms) Prove: any
comparison-based searching algorithm on a set of n elements takes
time Ω(log n) in the worst case. (Hint: you may want to read
Section 8.1 of the textbook for related terminologies and
techniques.)
Given the data listed in the table, calculate the lower and
upper bound for the 95% confidence interval for the mean at X = 7.
The regression equation is given by y^ = b0 +
b1x.
Regression Statistics
Statistic
Value
b0
4.3
b1
0.50
x
5.36
se
3.116
SSX
25.48
SST
58.25
n
40
Give your answers to 2 decimal places. You may find this
Student's t distribution table useful.
a) Lower bound =
b)Upper bound =