Claim: Most adults would not erase all of their personal information online if they could. A software firm survey of 669 randoml
1 answer:
Answer:
a) p=0.39, where p the parameter of interest represent the true proportion of adults that would erase all their personal information online if they could
b) Null hypothesis:
Alternative hypothesis:
Step-by-step explanation:
A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".
The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".
The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".
On this case the claim that they want to test is: "The true proportion of adults that would erase all their personal information online if they could is 0.39 or 39%". So we want to check if the population proportion is different from 0.39 or 0.39%, so this needs to be on the alternative hypothesis and on the null hypothesis we need to have the complement of the alternative hypothesis.
Part a. Express the original claim in symbolic form. Let the parameter represent the adults that would erase their personal information.
p=0.39, where p the parameter of interest represent the true proportion of adults that would erase all their personal information online if they could
Part b. Identify the null and alternative hypotheses.
Null hypothesis:
And for the alternative hypothesis we have
Alternative hypothesis:
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Answer:
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Answer:
a) 0.0025 = 0.25% probability that none of the appeals will be successful.
b) 0.0207 = 2.07% probability that exactly one of the appeals will be successful.
c) 0.9768 = 97.68% probability that at least two of the appeals will be successful
Step-by-step explanation:
For each appeal, there are only two possible outcomes. Either it is succesful, or it is not. The probability of an appeal being succesful is independent of other appeals, so we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.
In which is the number of different combinations of x objects from a set of n elements, given by the following formula.
And p is the probability of X happening.
45% of first-round appeals were successful.
This means that
Suppose 10 first-round appeals have just been received by a Medicare appeals office.
This means that
(a) Compute the probability that none of the appeals will be successful.
This is P(X = 0).
0.0025 = 0.25% probability that none of the appeals will be successful.
(b) Compute the probability that exactly one of the appeals will be successful.
This is P(X = 1).
0.0207 = 2.07% probability that exactly one of the appeals will be successful.
(c) What is the probability that at least two of the appeals will be successful
This is
Either less than two appeals are succesful, or at least two are. The sum of the probabilities of these events is decimal 1. So
0.9768 = 97.68% probability that at least two of the appeals will be successful