Someone help meeee lollll
1 answer:
Answer:
Step-by-step explanation:
The best way to do this is to first remove the parenthesis by distributing the negative into them. Then we will group the like terms together, moving their respective signs with them, then we will simplify. For the first one, after distributing the negative into the parenthesis (remember that a negative in front of a set of parenthesis containing a polynomial changes the signs in front of each term within the polynomial; negatives become positives and positives become negatives):
and then grouping like terms next to each other:
(this step is not completely necessary; I just encourage new learners to do it so as to not miss any of the like terms)
The above then simplifies to
The next one, after distributing the negative into the parenthesis:
and then grouping like terms next to each other (remember to move their signs with them!):
which simplifies to
Now for the last one:
and
which simplifies to
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Answer:
Yes, we have sufficient evidence at the 0.02 level to support the company's claim.
Step-by-step explanation:
We are given that a sample of 1500 computer chips revealed that 32% of the chips do not fail in the first 1000 hours of their use. The company's promotional literature claimed that above 29% do not fail in the first 1000 hours of their use.
Let Null Hypothesis, : p
0.29 {means that less than or equal to 29% do not fail in the first 1000 hours of their use}
Alternate Hypothesis, : p > 0.29 {means that more than 29% do not fail in the first 1000 hours of their use}
The test statics that will be used here is One-sample proportions test;
T.S. = ~ N(0,1)
where, = proportion of chips that do not fail in the first 1000 hours of their use = 32%
n = sample of chips = 1500
So, <u>test statistics</u> =
= 2.491
<em>Now, at 0.02 level of significance the z table gives critical value of 2.054. Since our test statistics is more than the critical value of z so we have sufficient evidence to reject null hypothesis as it fall in the rejection region.</em>
Therefore, we conclude that more than 29% do not fail in the first 1000 hours of their use which means we have sufficient evidence at the 0.02 level to support the company's claim.