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3 years ago

Which is bigger one hundred or ten squared?

Mathematics

2 answers:

pochemuha3 years ago

8 0

It is the same outcome

Leviafan [203]3 years ago

8 0

Answer:

They're both the same. 100 = 100

Step-by-step explanation:

Hi there! I'm glad I was able to help you!

One hundred (100) and 10^2 (also 100) are the same number.

We can tell that they are the same number by using a calculator to solve 10^2.

When we have an exponent, it means that the main number (10) is being multiplied by itself as many times as the exponent's number is (in this case, 2 (if that makes any sense at all)).

10 x 10 = 100, and, therefore, neither 100 or 10^2 are bigger nor smaller than each other.

100 = 100

I hope this helped you a little bit! If you need anything else, feel free to leave a comment below with questions or concerns! :)

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<em>The question is incomplete:</em>

<em>The store A has a sample mean of 4.05 and a sample standard deviation of 0.039. The store B has a sample mean of 3.99 and a sample standard deviation of 0.025.</em>

We have to perform an hypothesis test for the difference between means.

The claim will state that satisfaction ratings differ. So, the null and alternative hypothesis are:

$H_0: \mu_1-\mu2=0\\\\H_a: \mu_1-\mu2\neq0$

being μ1: the actual staisfaction rating of store A, and μ2: the actual satisfaction rating of store B.

The significance level is 0.05.

We know that, for both samples, the sample size is n=100.

The difference between means is:

$M_d=\mu_1-\mu_2=4.05-3.99=0.06$

The standard error of the diffence between means is calculated as:

$s_M=\sqrt{\dfrac{s_1^2+s_2^2}{n}}=\sqrt{\dfrac{0.039^2+0.025^2}{100}}=\sqrt{\dfrac{0.0021}{100}}=\sqrt{0.000021}=0.0046$

The z-statistic can be calculated as:

$z=\dfrac{M_d-(\mu_1-\mu_2)}{s_M}=\dfrac{0.06-0}{0.0046}=13.04$

The P-value for this test statistic in a two tailed test is

$P-value=2P(z>13.04)=0.000$

The P-value is smaller than the significance level, so the effect is significant. The null hypothesis is rejected.

There is enough evidence that the customer satisfaction rating differs from store A to store B.

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