Answer: 60
Step-by-step explanation:
The three interior (inside) angles in a triangle will always add up to 180°.
60 + 60 + y = 180
120 + y = 180
-120
y = 60
60 * 3 = 180
Answer:
And we can find this probability with the complement rule:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the average homicide rate for the cities of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability with the complement rule:
Answer:
x = 25.8
Step-by-step explanation:
- Add 7.6 to each side, so it now looks like this: x = 25.8
I hope this helps!
First 700-25=675
Poppy= 2F (F as in Felix, since she sells twice as much)
Alex = (Now equals 2F as well, cus we already took away the 25)
And well.... Felix is just felix so add that all up
F+F+F+F+F=5F
675/5=135!
Now according to that 135 is how many felix sold
Felix=135
Poppy=270
Alex=295
Answer:
a) P value = 0.0013
b) No, it is not plausible that the silicon content of the water is no greater than it was 10 years ago
Step-by-step explanation:
The null hypothesis here is “Mean is equal to 5” while alternate hypothesis is that “Mean is greater than 5”
Given
Mean = 5, x’ = 5.4 and sigma = 1.2 and n = 85
Z = x-u’/sigma/sqrt n
Substituting the given values, we get –
Z = 3.02
A) P value = 0.0013 which is less than 0.05 and thus we will reject the null hypothesis
B) There is enough evidence to reject the null hypothesis