The Table below shows the number of hours ten students spent studying for a test and their svores

Mathematics

1 answer:

wlad13 [49]3 years ago

5 0

Answer:

Step-by-step explanation:

By using linear regression calculator,

Linear regression equation representing the data set will be,

y = 7.79x + 34.27

Correlation coefficient of the line will be,

R = 0.98

Since, correlation coefficient of the line is (+0.98), relation between the two variables is a strong linear relationship.

That means hours spent studying has the strong relation with test scores obtained.

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Eight percent of all college graduates hired by companies stay with the same company for more than five years. The probability,

Maurinko [17]

Answer:

0.1662 = 16.62% probability that exactly 2 will stay with the same company for more than five years

Step-by-step explanation:

For each graduate, there are only two possible outcomes. Either they stay for the same company for more than five years, or they do not. Graduates are independent. This means that we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

And p is the probability of X happening.

Eight percent of all college graduates hired by companies stay with the same company for more than five years.

This means that $p = 0.08$

Sample of 11 college graduates:

This means that $n = 11$

The probability, rounded to four decimal places, that in a random sample of 11 such college graduates hired recently by companies, exactly 2 will stay with the same company for more than five years is: the absolute tolerance is +-0.0001

The tolerance means that the answer is rounded to four decimal places.

The probability is P(X = 2). So

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

$P(X = 2) = C_{11,2}.(0.08)^{2}.(0.92)^{11} = 0.1662$