What units could you use to measure the height of a hexagonal prism?
1 answer:
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Answer:
Computation.
Step-by-step explanation:
I'm not really sure if that's the analytical solution of the inital value problem,
because y(0)=11-ln(1-0)(3)=11. Howevwer, let us procede with the given values...
Let us assume that we are going to use euler with n=2 (two steps) and h=0.2(the size of each step)
The update rules of the Euler Methode are
Since the initial value problem tells us that Y=1 when X=0, we know that
and that
. Then, we have
and
which gives us the points (0,1), (0.2, 5.2) and (0.4, 27.12).
Now, since we want to compare the analyticaland the Euler result, we first compute the value of y=11-ln(1-x)(3) for the values x=0, 0.2 and 0.4. We get that
and we compute for each i.
It holds
which tells us that we have a really bad approximation, as I already stated there must be a mistake in the analytical solution since the intial values don't coincide. Also note that the curve that we get using the euler methose is growing faster than the analitical solution.
Answer:
0.64%.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the z-score of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
Mean of 75 grams and a standard deviation of 22 grams.
This means that
Sample of 144:
This means that
More than 80 or less than 70:
Both are the same distance from the mean, so we find one probability and multiply by 2.
The probability that it is less than 70 is the pvalue of Z when X = 70. So
By the Central Limit Theorem
has a pvalue of 0.0032
2*0.0032 = 0.0064.
0.0064*100% = 0.64%
The probability is 0.64%.
Answer:
the answer is 86°
Step-by-step explanation:
look at the photo
