WACC 10%

What is NPV,IRR, for both projects and also solve for the crossover rate.

Define the following terms:

1.      Skepticism

2.      Rationalism

3.      Empiricism

4.      Pantheism

5.      Pragmaticism

6.      Copernican revolution in philosophy

7.      Existentialism

8.      Problem of evil

9.      Transcendental realm

10.   Descartes substance dualism

11.   Philosophy of mind

12.   Turning test

13.   Chinese room

14.   Hume’s view of causation  

WACC 10%

What is NPV,IRR, for both projects and also solve for the crossover rate.

Objectives:
1. using indirect addressing
2. passing parameters
3. generating “random” numbers
4. working with arrays

Description:
Write and test a MASM (assembly language) program to perform the following tasks:
1. Introduce the program.
2. Get a user request in the range [min = 10 .. max = 200].
3. Generate request random integers in the range [lo = 100 .. hi = 999], storing them in consecutive elements of an array.
4. Display the list of integers before sorting, 10 numbers per line.
5. Sort the list in descending order (i.e., largest first).
6. Calculate and display the median value, rounded to the nearest integer.
7. Display the sorted list, 10 numbers per line.

Requirements:
1. The title, programmer's name, and brief instructions must be displayed on the screen.
2. The program must validate the user’s request.
3. min, max, lo, and hi must be declared and used as global constants. Strings may be declared as global variables or constants.
4. The program must be constructed using procedures. At least the following procedures are required:
A. main
B. introduction
C. get data {parameters: request (reference)}
D. fill array {parameters: request (value), array (reference)}
E. sort list {parameters: array (reference), request (value)}
i. exchange elements (for most sorting algorithms): {parameters: array[i] (reference), array[j] (reference), where i and j are the indexes of elements to be exchanged}
F. display median {parameters: array (reference), request (value)}
G. display list {parameters: array (reference), request (value), title (reference)}
5. Parameters must be passed by value or by reference on the system stack as noted above.
6. There must be just one procedure to display the list. This procedure must be called twice: once to display the unsorted list, and once to display the sorted list.
7. Procedures (except main) should not reference .data segment variables by name. request, array, and titles for the sorted/unsorted lists should be declared in the .data segment, but procedures must use them as parameters. Procedures may use local variables when appropriate. Global constants are OK.
8. The program must use appropriate addressing modes for array elements.
9. The two lists must be identified when they are displayed (use the title parameter for the display procedure).
10. The program must be fully documented. This includes a complete header block for the program and for each procedure, and a comment outline to explain each section of code.
11. The code and the output must be well-formatted.
12. Submit your text code file (.asm) to Canvas by the due date.

Extra Credit (Be sure to describe your extras in the program header block):
1. Display the numbers ordered by column instead of by row.
2. Use a recursive sorting algorithm (e.g., Merge Sort, Quick Sort, Heap Sort, etc.).
3. Implement the program using floating-point numbers and the floating-point processor.
4. Generate the numbers into a file; then read the file into the array.
5. Others?
To ensure you receive credit for any extra credit options you did, you must add one print statement to your program output PER EXTRA CREDIT which describes the extra credit you chose to work on. You will not receive extra credit points unless you do this. The statement must be formatted as follows...
--Program Intro--
**EC: DESCRIPTION
--Program prompts, etc—
Notes:
1. The Irvine library provides procedures for generating random numbers. Call Randomize once at the beginning of the program (to set up so you don't get the same sequence every time), and call RandomRange to get a pseudo-random number. (See the documentation in Lecture slides.)
2. The Selection Sort is probably the easiest sorting algorithm to implement. Here is a version of the descending order algorithm, where request is the number of array elements being sorted, and exchange is the code to exchange two elements of array:
for(k=0; k<request-1; k++) {
i = k;
for(j=k+1; j<request; j++) {
if(array[j] > array[i])
i = j;
}
exchange(array[k], array[i]);
}
3. The median is calculated after the array is sorted. It is the "middle" element of the sorted list. If the number of elements is even, the median is the average of the middle two elements (may be rounded).
Example (user input is in italics):
Sorting Random Integers Programmed by Road Runner
This program generates random numbers in the range [100 .. 999],
displays the original list, sorts the list, and calculates the
median value. Finally, it displays the list sorted in descending order.
How many numbers should be generated? [10 .. 200]: 9
Invalid input
How many numbers should be generated? [10 .. 200]: 16
The unsorted random numbers:
680 329 279 846 123 101 427 913 255 736
431 545 984 391 626 803
The median is 488.
The sorted list:
984 913 846 803 736 680 626 545 431 427
391 329 279 255 123 101

1. Given the following data, illustrate Selection Sort.

Consider the following data set.

a) plot the data (y versus x). Are there any points that appear to be outliers? If there are, circle them and label as such.

b) produce a regression of y against x. Add the regression line to the plot in a). Do you think that the regression line captures the most important features of the data set reasonably well?

c) using calculations at a 5% significance level, can you say that there is a significant linear relationship between the x and y? That is, can you say with 95% confidence that y linearly depends on x? Does this result agree with the conclusion you made in b)?

d) testing at a 5% significance level, can you say that the intercept (β0) is not zero? How does this conclusion agree with the plot in b)?

e) Assume that the first data point is an outlier (e.g. the value was misrecorded). Remove the outlier, and redo the parts b)-d). Plot the data set and both regression lines (before and after the outlier was removed). Comment on the difference. Also comment on the difference between the results of the tests in c) and d), if any.

GVC_E(V,E)

1. C =Φ

2. while ( E≠ Φ)

3. do

4. { select an edge (u,v)∈E;

5. C = C∪{u}∪{v};

6. delete u and v from V and edges with u or v as an endpoint from E;

7. }

8. for each u∈C

9. { if C\{u} is a valid cover;

10. C = C\{u};

11. }

How can I complete the pseudo code on line 4 and line 8 by adding a heuristic specifying how to select a node

Consider the following time series data:

Month 1 2 3 4 5 6 7

Value 25 14 19 11 18 22 16

(a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. What is the forecast for month 8? If required, round your answer to one decimal place. Do not round intermediate calculation.

(b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place.

define the following term, please

1. Oppression Olympics

2. Leapfrog Paranoia

3. Willful Blindness

4. Movement Backlash

5. Defiant Ignorance

6. Compassion Deficit Disorder

7. Categorical Multiplicity

8. Categorical Intersection

. Time Dynamics

10. Matrix of domination