Step-by-step explanation:

Rearranging the terms, we get

We then integrate the expression above to get


or

where I is the constant of integration.
Answer:
The correct answer is 6.8.
Explanation:
63.92 ÷ 92 ≈ 6.8
Hope this helps :)
we know that
<u>The correlation coefficient</u> is a measure of linear association between two variables. Values of the correlation coefficient are always between −1 and +1.
Using a mathematical tool-------> Excel software
Find the correlation coefficient
see the attached table N 1 and N 2
the answer is
Part 1) The correlation coefficient of the data is 0.02
Part 2) The correlation coefficient of the data is 0.98
If we want to find when the population of species A will be equal to the population of species B, we need to see when the two equations for the population of each species are equal, ie. equate them and solve for t. Thus:
2000e^(0.05t) = 5000e^(0.02t)
(2/5)e^(0.05t) = e^(0.02t) (Divide each side by 5000)
2/5 = e^(0.02t) / e^(0.05t) (Divide each side by e^(0.05t))
2/5 = e^(-0.03t) (use: e^a / e^b = e^(a - b))
ln(2/5) = -0.03t (use: if b = a^c, then loga(b) = c )
t = ln(2/5) / -0.03 (Divide each side by -0.03)
= 30.54 (to two decimal places)
Therefor, the population of species A will be equal to the population of species B after 30.54 years.
I wasn't entirely sure about the rounding requirements so I've left it rounded to two decimal places.
Answer:
The relationship between two variables is positive when _increase in one causes the increase in the other._______
Step-by-step explanation:
in statistics two variables may be associated or not associated. Normally we define variables as x and y.
If change of x does not affect value of y, then we can say there is no relationship between x and y.
Examples are a person Intelligence quotient and height, a vehicle's weight and its speed, etc.
Sometimes one variable affects another.
Examples are no of hours studied and scores obtained.
Exercises done and health condition etc.
If increase of x causes increase of y then the relationship is positive.
Instead if increase of one variable causes decrease of other variable then the relationship is negative
So
The relationship between two variables is positive when _increase in one causes the increase in the other._______