Answer:
X/2=95
X= 95*2
X=190
Step-by-step explanation:
can i have brainliest please

Step-by-step explanation:
So we go backwards, since we have x= 1/2 , 7

Now we have to foil to get the quadratic
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We must simplify the terms
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Our final result comes out to be
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Answer:
Test statistic = -2.25
P-value = 0.0199
Step-by-step explanation:
We are given the following in the question:
Population mean, μ = 450 gram
Sample mean,
= 441 grams
Sample size, n = 16
Alpha, α = 0.05
Sample variance = 256

First, we design the null and the alternate hypothesis
We use one-tailed t test to perform this hypothesis.
Formula:
Putting all the values, we have
Now,
Degree of freedom =

We can calculate the p-value from the table as:
P-value = 0.0199
Conclusion:
Since the p-value is smaller than the significance level we fail to accept the null hypothesis and reject it.
Thus, there is enough evidence to support the claim that the machine is under filling the bags .
N.O = 4
N is midpoint of M.0
Meaning M.N also has to be 4
4+4= 8
N.P = 6
0.P = 2
8+ 2 = 10
Answer:
P = 0.4812
Step-by-step explanation:
First, we need to use here two expressions and then do the calculations.
The first one is the conditional probability which is:
P(B|A) = P(A∩B)/P(A) (1)
The second expression to use has relation with the Bayes's theorem which is the following:
P(D|C) = P(C|D)*P(D) / P(C|D)*P(D) + P(C|d)*P(d) (2)
Now, the expression (2) is the one that we will use to calculate the probability of a selected random bicyclist who tests positive for steroids.
So, in this case, we will call C for positive and D that is using steroids and d is the opposite of d, which means do not use steroids.
Then, the probabilities are the following:
P(D) = 8% or 0.08
P(C|D) = 96% or 0.96
P(C|d) = 9% or 0.09
P(d) = 1 - 0.08 = 0.92
With these data, let's replace in expression 2
P(D|C) = 0.96 * 0.08 /0.96 * 0.08 + 0.09*0.92
P(D|C) = 0.0768 / 0.1596
P(D|C) = 0.4812 or 48.12%