Answer:
a) Figure attached
b) If we see the scatter plot we can conclude that the possible relation between x and y is linear and with a positive correlation since when the values of x increases the values for y increases as well.
c) 
We can find the numerator like this:

And then:

d)
Step-by-step explanation:
Part a
For this part we use excel in order to create the scatterplot and we got the result on the figure attached.
Part b
If we see the scatter plot we can conclude that the possible relation between x and y is linear and with a positive correlation since when the values of x increases the values for y increases as well.
Part c
The sample covariance is defined as:

We can find the numerator like this:

And then:

Part d
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:
For our case we have this:
n=5
So then the correlation coefficient would be r =0.693
Answer:7m^5 - 3m^3 + 9
Step-by-step explanation: You’d have to remove the brackets, but remember that the second has to have everything multiplied by -1, because there’s a minus sign in front of the second bracket. Then you’d group like terms, then add or subtract. Here’s the step by step
6m^5 + 3 - m^3 - 4m + m^5 - 2m^3 + 4m + 6
2. 6m^5 + m^5 - 2m^3 - m^3 + 4m - 4m + 6 + 3
Subtract or add what’s needed, which would be figures with the same variable and coefficient.
3. 7m^5 - 3m^3 + 9
After this, there’s nothing you can add, since the remaining figures don’t have the same variable.
Hope it’s clear and this wasn’t that long
Answer: =x2+7x+5
Step-by-step explanation:
−3x2+2x−4+4x2+5x+9
=−3x2+2x+−4+4x2+5x+9
Combine Like Terms:
=−3x2+2x+−4+4x2+5x+9
=(−3x2+4x2)+(2x+5x)+(−4+9)
=x2+7x+5
Answer:
=x2+7x+5
True of False? It depends on the scenario of the data size.
Answer:
The square root of -16 would be 4 i. Hope this helps!
Step-by-step explanation: