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nirvana33 [79]
3 years ago
15

Need help right now !!!!! Find the missing part

Mathematics
1 answer:
oksian1 [2.3K]3 years ago
3 0

What kind of mathematics are you learning?

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PLEASE HELP ME NOW! THIS IS DUE AND I NEED HELP, please and thank you.
GaryK [48]
Hfdjuggb 77₽+I /2-1₽5
3 0
2 years ago
BRAINLIESTTT ASAP!! PLEASE HELP ME :)
Lostsunrise [7]

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.

5 0
3 years ago
Criminal investigators use biometric matching for fingerprint recognition, facial recognition, and iris recognition. When matchi
Daniel [21]

Answer:

Type I error.

Step-by-step explanation:

Let's remember the definition of Type I error and Type II error:

A type I error is the rejection of a true null hypothesis, this means that we would get a "false positive" with this error.

A type II error is the non rejection of a not true null hypothesis, this error would give us a "false negative".

In this problem, we are told that the mean match score to identify a suspect is 80. However, the test shows that the mean match score is more than 80 when the person doesn't have a fingerprint match (and therefore the person would not be a suspect). Therefore, this person would appear as a suspect when he/she really isn't one. This means that the test is giving a "false positive". Thus, this is a type I error.

6 0
3 years ago
$12 for 6 bagels; $9 for 24 bagels.
BabaBlast [244]

Answer:

What is the question that you are asking?

Step-by-step explanation:

3 0
3 years ago
The average score of all golfers for a particular course has a mean of 75 and a standard deviation of 4. Suppose 64 golfers play
Vilka [71]

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 \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

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 \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

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:

\mu = 75, \sigma = 4, n = 64, s = \frac{4}{\sqrt{64}} = 0.5

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.

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{76 - 75}{0.5}

Z = 2

Z = 2 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.

6 0
3 years ago
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