Answer:
(A)6
Step-by-step explanation:
Given the quadratic expression: 
We factorize:

Therefore, the missing number that will complete the factorization is 6.
Answer: 
Step-by-step explanation:
Given the following expresion provided in the exercise:

You can follow these steps in order to evaluate it when
and
:
1. You need to substitute
and
into the given expression:

2. Now you can solve the mutiplication:

3. Since
, you get:

4. You must solve the division. Divide the numerator 16 by the denominator 4. Then:

5. And finally, you must solve the addition. So, you get this result:

Answer:
First look at the number of bricks alone.
Going from 50 bricks to 60 bricks is more work, thus it will require more people. The number of people would be the ratio of the 2. Since the number must be larger, you know the numerator must be the larger of the 2 numbers, so you get 60/50
Next look at the time alone.
Going from 30 minutes to 20 minutes is more work, thus it will require more people. The number of people would be the ratio of the 2. Since the number must be larger, you know the numerator must be the larger of the 2 numbers, so you get 30/20
Now you can just multiply everything.
= 5*60/50*30/20
= 5*6/5*3/2
= 90\10
= 9.
Answer:
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the
who represent the determination coefficient and we got:

And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables
Step-by-step explanation:
Previous concepts
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the
who represent the determination coefficient and we got:

And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables