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vfiekz [6]
2 years ago
12

UCLA Extension's marketing department wants

Computers and Technology
1 answer:
damaskus [11]2 years ago
7 0

The measure of central tendency to determine the effectiveness can be the mean, median or mode

It is true that you can calculate the mean as a measure of central tendency for reading the email

<h3>How to determine the true statement?</h3>

The survey result is given as:

  • Sample size, n = 40
  • Enrolled in one course = 26
  • Enrolled in three courses = 8
  • Not enrolled = 6

To determine if the email is effective or not, we simply carry out a test of significance.

However, if the central of tendency is to be used to determine the effectiveness; it is best to use the mean.

Hence, it is true that you can calculate the mean as a measure of central tendency for reading the email

Read more about measure of central tendency at:

brainly.com/question/17631693

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Consider two different implementations, M1 and M2, of the same instruction set. There are three classes of instructions (A, B, a
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Explanation:

A.)

we have two machines M1 and M2

cpi stands for clocks per instruction.

to get cpi for machine 1:

= we multiply frequencies with their corresponding M1 cycles and add everything up

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30/100 x 3 = 0.9

CPI for M1 = 0.5 + 0.4 + 0.9 = 1.8

We find CPI for machine 2

we use the same formula we used for 1 above

50/100 x 2 = 1

20/100 x 3 = 0.6

30/100 x 4 = 1.2

CPI for m2 =  1 + 0.6 + 1.2 = 2.8

B.)

CPU execution time for m1 and m2

this is calculated by using the formula;

I * CPI/clock cycle time

execution time for A:

= I * 1.8/60X10⁶

= I x 30 nsec

execution time b:

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= I x 35 nsec

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vazorg [7]

Answer:

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Explanation:

Collaborative filtering uses a community-based approach to filter spam. It works by collecting numerous email users from around the world. By doing this, it becomes possible for users to flag emails that are spam and those that are legitimate.

Also Collaborative Filtering is one of the most efficient techniques for building a system that can help a user when it comes to recommending best choices based on information from a large number of users.

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Answer:

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