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3 years ago

Which gives the best estimate and the exact product of (5.9)(8.28)? A: estimate: 40; exact product: 48.852

2 answers:

7 0

Answer:
B: estimate: 48; exact product: 48.852

Explanation:
First, let's get the exact product:
5.9 * 8.28 = 48.852

Ten, let's get the estimated product:
5.9 will be rounded up giving us 6
8.28 will be rounded down giving us 8
Now the estimated product = 6 * 8 = 48

Based on the above calculations, we have:
estimate : 48
exact : 48.825
This corresponds to option B

Hope this helps :)

Evgesh-ka [11]3 years ago

5 0

I think B gives the best estimate and exact product because

1). 5.9 x 8.28 is very similar to 6 x 8 which equals 48.

and

2. 5.9 x 8.28 = 48.852.

Hopefully that made sense. :)

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The test statistic of zequals2.32 is obtained when testing the claim that pgreater than0.3. a. Identify the hypothesis test as b

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Answer:

a) We need to conduct a hypothesis in order to test the claim that the true proportion p is greatr than 0.3, so then the system of hypothesis are.:

Null hypothesis: $p \leq 0.3$

Alternative hypothesis: $p > 0.3$

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c) So the p value obtained was a very low value and using the significance level given $\alpha=0.1$ we have $p_v$ so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of interest is higher than 0.3

Step-by-step explanation:

Part a: Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the true proportion p is greatr than 0.3, so then the system of hypothesis are.:

Null hypothesis: $p \leq 0.3$

Alternative hypothesis: $p > 0.3$

Right tailed test

When we conduct a proportion test we need to use the z statisitc, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

Calculate the statistic

For this case the statistic is given by $z_{calc}= 2.32$

Part b: Statistical decision

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The next step would be calculate the p value for this test.

Since is a right tailed test the p value would be:

$p_v =P(z>2.32)=0.0102$

Part c

So the p value obtained was a very low value and using the significance level given $\alpha=0.1$ we have $p_v$ so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of interest is higher than 0.3

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