Answer:
percentage change in volume = 0.00285 %
Explanation:
given data
bulk modulus = 3.5 ×
N/m²
bulk stress =
N/m²
solution
we will apply here bulk modulus formula that is
bulk modulus =
...............1
put here value and we get
3.5 ×
=
solve it we get
bulk strain = 2.8571 ×
and
bulk strain =
so that percentage change in volume is = 2.8571 ×
× 100
percentage change in volume = 0.00285 %
Answer:
The expression is shown in the explanation below:
Explanation:
Thinking process:
Let the time period of a simple pendulum be given by the expression:

Let the fundamental units be mass= M, time = t, length = L
Then the equation will be in the form


where k is the constant of proportionality.
Now putting the dimensional formula:
![T = KM^{a}L^{b} [LT^{-} ^{2}]^{c}](https://tex.z-dn.net/?f=T%20%3D%20KM%5E%7Ba%7DL%5E%7Bb%7D%20%20%5BLT%5E%7B-%7D%20%5E%7B2%7D%5D%5E%7Bc%7D)

Equating the powers gives:
a = 0
b + c = 0
2c = 1, c = -1/2
b = 1/2
so;
a = 0 , b = 1/2 , c = -1/2
Therefore:

T = 
where k = 
Answer: No
Explanation:
Length= 2cm= 20mm
Now meter stick can read to nearest millimeter.
It is given that length is to be measured with a precision of 1% of 20mm= 1/100 * 20= 0.2mm
Since the least count is 1mm of meter stick and precision required is less than that. So, meter stick cannot be used for this, travelling microscope can be used for this as it can read to 0.1mm.
Answer:
a) 
b) 
Explanation:
Previous concepts
The cumulative distribution function (CDF) F(x),"describes the probability that a random variableX with a given probability distribution will be found at a value less than or equal to x".
The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution".
Part a
Let X the random variable of interest. We know on this case that 
And we know the probability denisty function for x given by:

In order to find the cdf we need to do the following integral:

Part b
Assuming that
, then the density function is given by:

And for this case we want this probability:

And evaluating the integral we got:
