Drag each value to the correct location on the table. Identify whether the given numbers are perfect squares, perfect cubes, or
2 answers:
Answer:
Cubes 8, 27, 1331, 1000, 125 Squares 9, 100, 25, 81 and neither are 21, 1332, 126.
Step-by-step explanation:
The given numbers are 8, 9, 21, 27, 1331, 1332, 100, 1000, 126, 125, 25, 81 and we have to find the perfect squares, perfect cubes or neither from these numbers.
21 is neither square nor cube.
27 = 3³
1332 is niether
1331 = 11³
100 = 10²
1000 = 10³
126 neither
125 = 5³
25 = 5²
81 = 9²
So cubes are 8, 27, 1331, 1000, 125 and squares are 9, 100, 25, 81.
Neither are 21, 1332, 126.
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Answer:
No, we can't reject the dealer's claim with a significance level of 0.05.
Step-by-step explanation:
We are given that a local car dealer claims that 25% of all cars in San Francisco are blue.
You take a random sample of 600 cars in San Francisco and find that 141 are blue.
<u><em>Let p = proportion of all cars in San Francisco who are blue</em></u>
SO, Null Hypothesis, : p = 25% {means that 25% of all cars in San Francisco are blue}
Alternate Hypothesis, : p
25% {means that % of all cars in San Francisco who are blue is different from 25%}
The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;
T.S. = ~ N(0,1)
where, = sample proportion of 600 cars in San Francisco who are blue =
= 0.235
n = sample of cars = 600
So, <u><em>test statistics</em></u> =
= -0.866
<em>Now at 0.05 significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics lies within the range of critical values of z so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which we fail to reject our null hypothesis.</em>
Therefore, we conclude that 25% of all cars in San Francisco are blue which means the dealer's claim was correct.