Answer:
The sum is 1575.
Step-by-step explanation:
Consider the provided information.
It is given that positive integers smaller than 1000 and that can be written in the form 
Where n is integer that means the value of n can be a positive number or a negative number.
For n = 0

For n=-1

For n=-2

For n = -3 the obtained number is not an integer.
Now consider the positive value of n.
For n=1

For n=2

For n=3

For n=4 the obtained number is greater than 1000.
Now add all the numbers.

Hence, the sum is 1575.
Answer:
It is in the tenths place
Step-by-step explanation:
In the number 9.365, 3 is in the tenths place.
Answer:
The answer is 3√5 mi.
The formula is: d = √(3h/2)
Wyatt:
h = 120 ft
d = √(3 * 120/2) = √180 = √(36 * 5) = √36 * √5 = 6√5 mi
Shawn:
h = 270 ft
d = √(3 * 270/2) = √405 = √(81 * 5) = √81 * √5 = 9√5 mi
How much farther can Shawn see to the horizon?
Shawn - Wyatt = 9√5 - 6√5 = 3√5 mi
Answer:
A) The theoretical probability of choosing a heart is 1/16 greater than the experimental probability of choosing a hear
Step-by-step explanation:
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