Answer:
3) the pressure drop across high MERV filters is significant.
Explanation:
MERV (Minimum-Efficiency Reporting Value) is used to measure the efficiency of filter to remove particles. A filter of high MERV can filter smaller particles but this causes an increase in reduced air flow that is an increase in pressure drop. High MERV filters capture more particles causing them to get congested faster and thereby increasing pressure drop.
Excessive pressure drop can cause overheating and lead to damage of the filter. The pressure drop can be reduced by increasing the surface area of the filter.
Answer:
The statement can be written as
int result = cube(4);
Explanation:
A function is a block of reusable codes to perform some tasks. For example, the function in the question is to calculate the cube of a number.
A function can also operate on one or more input value (argument) and return a result. The <em>cube </em>function in the question accept one input value through its parameter <em>number </em>and the <em>number</em> will be multiplied by itself twice and return the result.
To call a function, just simply write the function name followed with parenthesis (e.g. <em>cube()</em>). Within the parenthesis, we can include zero or one or more than one values as argument(s) (e.g. <em>cube(4)</em>).
We can then use the "=" operator to assign the return output of the function to a variable (e.g. <em>int result = cube(4)</em>)
Answer:
awnsers should be added to know to show additional
Answer:
The temperature gauge showing that the vehicle has been running warmer or has recently began to have issues from overheating is an idication that your vehicle may be developing a cooling system problem.
Explanation:
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:
