Answer:
The probability of SFS and SSF are same, i.e. P (SFS) = P (SSF) = 0.1311.
Step-by-step explanation:
The probability of a component passing the test is, P (S) = 0.79.
The probability that a component fails the test is, P (F) = 1 - 0.79 = 0.21.
Three components are sampled.
Compute the probability of the test result as SFS as follows:
P (SFS) = P (S) × P (F) × P (S)
Compute the probability of the test result as SSF as follows:
P (SSF) = P (S) × P (S) × P (F)
Thus, the probability of SFS and SSF are same, i.e. P (SFS) = P (SSF) = 0.1311.
Answer:
2/3
Step-by-step explanation:
12/6=2
18/6=3
so
the fraction is 2/3
i think this is what your teachers means, lmk if thats wrong
Answer:
Step-by-step explanation:
Answer:
12
Step-by-step explanation:
Simplify 2+3 to 5.
7+3× 3
/5
Cancel 3
7+5
Simplify.
12
We conclude the hypothesis test as Alternative Hypothesis if the data would be very unusual if the original assumption about our parameter were correct.
- A hypothesis in statistics is a claim or supposition on the properties of one or more variables in one or more populations. There are two hypothesis to choose between because a statement might either be true or wrong.
- The null hypothesis is the assertion that we (or someone else) consider to be true. Our hypothesis test will come to one of two conclusions: "reject H0" or "do not reject H0." Remember that until data provide evidence to the contrary, we always proceed under the null hypothesis.
- If the null hypothesis is incorrect, the alternative hypothesis must be true. The hypothesis test can be different in one of three ways: greater than, smaller than, or just different (not equal). As a result, there will always be an inequality requirement in the notation for H.
Learn more about Alternative hypothesis here: brainly.com/question/17173491
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