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grin007 [14]
3 years ago
5

Suppose that a certain college class contains students. Of these, are juniors, are mathematics majors, and are neither. A studen

t is selected at random from the class. (a) What is the probability that the student is both a junior and a mathematics major
Mathematics
1 answer:
ipn [44]3 years ago
7 0

Answer:

<h2>2/5</h2>

Step-by-step explanation:

The question is not correctly outlined, here is the correct question

<em>"Suppose that a certain college class contains 35 students. of these, 17 are juniors, 20 are mathematics majors, and 12 are neither. a student is selected at random from the class. (a) what is the probability that the student is both a junior and a mathematics majors?"</em>

Given data

Total students in class= 35 students

Suppose M is the set of juniors and N is the set of mathematics majors. There are 35 students in all, but 12 of them don't belong to either set, so

|M ∪ N|= 35-12= 23

|M∩N|=  |M|+N- |MUN|= 17+20-23

           =37-23=14

So the probability that a random student is both a junior and social science major is

=P(M∩N)= 14/35

=2/5

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What are relating data sets ?
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Answer:

Step-by-step explanation:

Data sets are a collection of numbers related by a topic. The three ways to work with data sets include mean, median, and mode. The mean is the average of the data set, the median is the middle of the data set, and the mode is the number or value that occurs most often in the data set.

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4 years ago
A very large data set (N &gt; 10,000) has a mean value of 1.65 units and a standard deviation of 72.26 units. Determine the rang
Romashka [77]

Answer:

z=-0.674

And if we solve for a we got

a=1.65 -0.674*72.26=-47.05

z=0.674

And if we solve for a we got

a=1.65 +0.674*72.26=50.35

So then the limits where 50% of the data lies are -47.05 and 50.35

Step-by-step explanation:

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 variable of interest of a population, and for this case we know the distribution for X is given by:

X \sim N(1.65,72.26)  

Where \mu=1.65 and \sigma=72.26

For this case we want the limits for the 50% of the values.

So on the tails of the distribution we need the other 50% of the data, and on ach tail we need to have 25% since the distribution is symmetric.

Lower tail

For this part we want to find a value a, such that we satisfy this condition:

P(X>a)=0.75   (a)

P(X   (b)

Both conditions are equivalent on this case. We can use the z score again in order to find the value a.  

As we can see on the figure attached the z value that satisfy the condition with 0.25 of the area on the left and 0.75 of the area on the right it's z=-0.674. On this case P(Z<-0.674)=0.25 and P(z>-0.674)=0.75

If we use condition (b) from previous we have this:

P(X  

P(z

But we know which value of z satisfy the previous equation so then we can do this:

z=-0.674

And if we solve for a we got

a=1.65 -0.674*72.26=-47.05

So the value of height that separates the bottom 25% of data from the top 75% is -47.05.  

Upper tail

For this part we want to find a value a, such that we satisfy this condition:

P(X>a)=0.25   (a)

P(X   (b)

Both conditions are equivalent on this case. We can use the z score again in order to find the value a.  

As we can see on the figure attached the z value that satisfy the condition with 0.75 of the area on the left and 0.25 of the area on the right it's z=0.674. On this case P(Z<0.674)=0.75 and P(z>0.674)=0.25

If we use condition (b) from previous we have this:

P(X  

P(z

But we know which value of z satisfy the previous equation so then we can do this:

z=0.674

And if we solve for a we got

a=1.65 +0.674*72.26=50.35

So the value of height that separates the bottom 75% of data from the top 25% is 50.35.  

So then the limits where 50% of the data lies are -47.05 and 50.35

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Answer:

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Step-by-step explanation:

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Answer:

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Step-by-step explanation:

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