A normally distributed data set has a mean of 0 and a standard deviation of 2. The closest to the percent of values between -4.0 and 2.0 would be 84%.
<h3>What is the empirical rule?</h3>
According to the empirical rule, also known as the 68-95-99.7 rule, the percentage of values that lie within an interval with 68%, 95%, and 99.7% of the values lies within one, two, or three standard deviations of the mean of the distribution.
A normally distributed data set has a mean of 0 and a standard deviation of 2.
……….(by symmetry)
=.49865+.3413
.83995…….(by (http://83995…….by) table value)
=.8400 × 100
=84%
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This is the answer not sure if you wanted it graph or not
The arcsine,
, is the inverse of the
function. This means that it takes as <em>inputs </em>what would usually be <em>outputs </em>for the
function and produces as <em>outputs </em>what would usually be <em>inputs </em>for the
function.
This can be particularly useful when you're trying to find an angle on a right triangle, but you've only been given the lengths of the sides. To find any angle
in a right triangle, just take
, where o is the side opposite
and h is the hypotenuse of the right triangle.
Because the more years you go without receiving it the more it comes out to after you cash out. It starts to add up year by year :)
Answer:
0.2364
Step-by-step explanation:
We will take
Lyme = L
HGE = H
P(L) = 16% = 0.16
P(H) = 10% = 0.10
P(L ∩ H) = 0.10 x p(L U H)
Using the addition theorem
P(L U H) = p(L) + P(H) - P(L ∩ H)
P(L U H) = 0.16 + 0.10 - 0.10 * p(L u H)
P(L U H) = 0.26 - 0.10p(L u H)
We collect like terms
P(L U H) + 0.10P(L U H) = 0.26
This can be rewritten as:
P(L U H)[1 +0.1] = 0.26
Then we have,
1.1p(L U H) = 0.26
We divide through by 1.1
P(L U H) = 0.26/1.1
= 0.2364
Therefore
P(L ∩ H) = 0.10 x 0.2364
The probability of tick also carrying lyme disease
P(L|H) = p(L ∩ H)/P(H)
= 0.1x0.2364/0.1
= 0.2364
