Need help right now !!!!! Find the missing part
1 answer:
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Answer:
See below
Step-by-step explanation:
(a) Field lines
A negatively charged particle has an electric field associated with it.
The field lines spread out radially from the centre of the point. They are represented by arrows pointing in the direction that a positive charge would move if it were in the field.
Opposite charges attract, so the field lines point toward the centre of the particle.
For an isolated negative particle, the field lines would look like those in Figure 1 below.
If two negative charges are near each other, as in Figure 2, the field lines still point to the centre of charge.
A positive charge approaching from the left is attracted to both charges, but it moves to the closer particle on the left.
We can make a similar statement about appositive charge approaching from the left.
Thus, there are few field lines in the region between the two particles.
(b) Coulomb's Law
The formula for Coulomb's law is
F = (kq₁q₂)/r²
It shows that the force varies inversely as the square of the distance between the charges.
Thus, the force between the charges decreases rapidly as they move further apart.
Answer:
0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:
Find the probability that the average score of the 64 golfers exceeded 76.
This is 1 subtracted by the pvalue of Z when X = 64.
By the Central Limit Theorem
has a pvalue of 0.9772
1 - 0.9772 = 0.0228
0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.