Ok
the sets are
natural numbers (or counting numbers), this is like 1,2,3,4,5 etc
whole numbers, this is including 0, so 0,1,2,3,4,5,6 etc
integers, this includes the previoius set and negatives, so -3,-2,-1,0,1,2,3,4,5 etc
rational numbers, this is the set of numbers that can be written in form a/b where b≠0, so all integers can be written like this, like example -3=-3/1, so -7/9 belongs here
-7/9 goes in the rational set
Answer:
Henry's baseball practice starts at 2:00, will last an hour and forty-five minutes, and will end at 3:45.
Step-by-step explanation:
2 + 1 = 3
3 + 45 minutes = 3 : 45
Simplify both sides of the equation
x/16−(x+2/8) = 2x/16 + −1/8x + −1/4 = 2
Distribute
1/16x + −1/8x + −1/4 = 2
(1/16x + −1/8x)+(−1/4) = 2
Combine Like Terms
−1/16x + −1/4 = 2
Add 1/4 to both sides.
−1/16x + −1/4 + 1/4 = 2 + 1/4
−1/16x = 9/4
Multiply both sides by 16/(-1).
(16/−1)*(−1/16x)=(16/−1)*(9/4)
x=−36
The answer is
the first one is x= 18.98
a^2+b^2=c^2
8 cm^2+17 cm^2= x^2
64+289=x^2
√x^2= √353
x=18.89
<span><span>the second one is x= 18.7
a^2+b^2=c^2
7 m^2+ x^2= 20 m^2
49 m+x^2=400 m
-49 -49
</span></span>√x^2=√352
<span><span>x= 18.7
Hope this helps!</span></span>
Answer:
Residual = 11.462
Since the residual is positive, it means it is above the regression line.
Step-by-step explanation:
The residual is simply the difference between the observed y-value which is gotten from the scatter plot and the predicted y-value which is gotten from regression equation line.
The predicted y-value is given as 20.7°
The regression equation for temperature change is given as;
y^ = 9.1 + 0.6h
h is the observed amount of humidity and it's given to be 23 percent or 0.23.
Thus;
y^ = 9.1 + 0.6(0.23)
y^ = 9.238
Thus:
Residual = 20.7 - 9.238
Residual = 11.462
Since the residual is positive, it means it is above the regression line.
