Step-by-step explanation:
The electrical force between two unlike charge is given by :

k is electrostatic constant
q₁ and q₂ are two charges
r is the distance between charges
It is clear that the electric force is inversely proportional to the square of the distance between them.
The graph F as a function of r for two positive charges is shown in the attached figure. It is a hyperbola.
Answer:
yesyes
Step-by-step explanation:
Answer:

Step-by-step explanation:
The probability density function is :

With 0 < x < 3
To be a valid probability density function :

Where a < x < b
And also
f(x) ≥ 0 for a < x < b
Applying this to the probability density function of the exercise :





We can verify by replacing ''c'' in the original probability density function and integrating :


Also, f(x) ≥ 0 for 0 < x < 3
Answer:
And we can find this probability using the normal standard distribution or excel and we got:
Step-by-step explanation:
For this case we assume the following complete question: "The pucks used by the National Hockey League for ice hockey must weigh between 5.5 and 6 ounces. Suppose the weights of pucks produced at a factory are normally distributed with a mean of 5.86 ounces and a standard deviation of 0.13ounces. What percentage of the pucks produced at this factory cannot be used by the National Hockey League? Round your answer to two decimal places.
"
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the normal standard distribution or excel and we got: