Convert the matrix of observations to mean-deviation form, and construct the sample covariance matrix.[10 13 1 4]3 06318 6 6 6Select one:O A.30 -3 -15 -12]-3 18 -12 -3-15 -12 18-12 -3 9O B.-30 12 -1212 -6 0-12 0-36]90 -36 36S = -36 18 036 0 10830 -12 12600 36]C.O D.S=S=S=-1212392

In this question we have to convert matrix of observation to mean-deviation form, and construct the…

Convert the matrix of observations to mean-deviation form, and construct the sample covariance matrix. [10 13 1 4] 3063 [18 6 6 6 30 -3 -15-12] -3 18-12-3 -15 -12 18 9 -12 -3 2 [-30 12-12] S= 12 -6 0 -12 0 -36] 90 -36 36 S = -36 18 0 36 0 108 30 -12 12] 60 0 36 Select one: О А. O B. O C. O D. S= S = -12 12 69

Convert the matrix of observations to mean-deviation form, and construct the sample covariance matrix. [10 13 1 4] 3063 [18 6 6 6 30 -3 -15-12] -3 18-12-3 -15 -12 18 9 -12 -3 2 [-30 12-12] S= 12 -6 0 -12 0 -36] 90 -36 36 S = -36 18 0 36 0 108 30 -12 12] 60 0 36 Select one: О А. O B. O C. O D. S= S = -12 12 69

Database System Concepts

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ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

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Requirement Analysis

A process that determines the user expectations for a software product is called requirement analysis. In software engineering, requirement analysis is known as requirement engineering. It involves communication with end-users and stakeholders to determine whether the system or software requirements are validated, conflicts are solved, and key requirements are documented. The first activity of the Software Development Life Cycle (SDLC) is requirement analysis.

Question

Convert the matrix of observations to mean-deviation form, and construct the sample covariance matrix.
[10 13 1 4]
3 063
18 6 6 6
Select one:
O A.
30 -3 -15 -12]
-3 18 -12 -3
-15 -12 18
-12 -3 9
O B.
-30 12 -12
12 -6 0
-12 0-36]
90 -36 36
S = -36 18 0
36 0 108
30 -12 12
60
0 36]
C.
O D.
S=
S=
S=-12
12
392

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