Question

in most of the data analysis cases, the “reducing factor” n which lowers the number m of dimensional variables to m-n dimensionless groups, exactly equals the number of relevant dimensions (M, L, T). In one case this was not so. Explain in words why this situation happens.

Answer #1

In most data analysis cases, the reducing factor n lowers thr number m of dimensional variables to m-n dimensionless groups, exactly ewuals the number of relevant dimensions (M,L,T), but only in Fluid mechanics this was not happen, there are four relevant dimensions are used (M,L,T, )... = temperature.

The M is replaced by F (Force).

So in fluid mechanics, mainly four dimensions are used (F, L,T, ), because in fluid mechanics, force on the immersed body cause this extra dimension to add.

in most of the data analysis cases, the “reducing factor” n
which lowers the number m of dimensional variables to m-n
dimensionless groups, exactly equals the number of relevant
dimensions (M, L, T). In one case this was not so. Explain in words
why this situation happens.

Use Random number generator (under Data Analysis) to simulate
the following data set. Create 10 columns, each 20 points long and
use the following parameters: Number of variables (10), number of
data point (20), Distribution (Normal), Mean (40), Standard
Deviation (10), Random seed (1234). The data should be in columns:
A,B,C,….,I,J.
Randomly pick two columns (say Column B and Column H) and
perform 2-sided t-test on these two data columns. Record the
P-value and repeat this procedure several times (at...

Use Random number generator (under Data Analysis) to simulate
the following data set. Create 10 columns, each 20 points long and
use the following parameters: Number of variables (10), number of
data point (20), Distribution (Normal), Mean (40), Standard
Deviation (10), Random seed (1234). The data should be in columns:
A,B,C,….,I,J. Randomly pick two columns (say Column B and Column H)
and perform 2-sided t-test on these two data columns. Record the
P-value and repeat this procedure several times (at...

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import java.io.*;
import java.util.Scanner;
class sort
{
int a[];
int n;
long endTime ;
long totalTime;
long startTime;
static BufferedReader br = new BufferedReader(new
InputStreamReader(System.in));
public sort(int nn) // Constructor
{
a = new int[nn];
n = nn;
endTime= 0;
totalTime =0;
startTime =0;
}
public static void main(String args[]) throws IOException
{
System.out.print("\nEnter number of students: ");
int nn =...

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Required information
Chapter 17 Case: Reducing Ambiguity in Business
Requirements
The number one reason projects fail is bad business
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ambiguity or insufficient involvement of end users during analysis
and design.
A requirement is unambiguous if it has
the same interpretation for all parties. Different interpretations
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1- Which study design(s) require collecting information about
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Case-control
Meta-analysis
Cohort
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B. C.
D.
Exposure
- A.
B. C.
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MATHEMATICS
1. The measure of location which is the most likely to
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b.
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2. If two events are independent, then a. they must be
mutually
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c.
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Analysis: This section should include the issue register as a
bare minimum, but may include also why-why diagrams, a Pareto
chart, a waste table and/or value-added analysis table. Flow
analysis or simulation of this case study might be possible but
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The first part of the project:
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Walmart has continued to retain
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