<span>At least 75% of the data will fall within 2 standard deviations of the mean.
This is tricky problem. Usually when you're dealing with standard deviation, you have a bell curve, or something close to a bell curve and for such a data distribution, there will be approximately 95% of the data within 2 standard deviations of the mean. But if you don't know that you have a bell curve, you have to fall back to Chebyshev’s Theorem, which states that at least 75% of the data points will fall within 2 standard deviations of the mean for any set of numbers.</span>
Number > 5 - round up
Number = 5 - round up
Number < 5 - round and keep the number the same
7526.442
Hundredth = 2nd decimal place = 4
2 < 5
Round and keep the number the same
7526.44
Answer:
<em>H₀</em>: <em>μ</em>₁ = <em>μ</em>₂ vs, <em>Hₐ</em>: <em>μ</em>₁ > <em>μ</em>₂.
Step-by-step explanation:
A two-sample <em>z</em>-test can be performed to determine whether the claim made by the owner of pier 1 is correct or not.
It is provided that the weights of fish caught from pier 1 and pier 2 are normally distributed with equal population standard deviations.
The hypothesis to test whether the average weights of the fish in pier 1 is more than pier 2 is as follows:
<em>H₀</em>: The weights of fish in pier 1 is same as the weights of fish in pier 2, i.e. <em>μ</em>₁ = <em>μ</em>₂.
<em>Hₐ</em>: The weights of fish in pier 1 is greater than the weights of fish in pier 2, i.e. <em>μ</em>₁ > <em>μ</em>₂.
The significance level of the test is:
<em>α</em> = 0.05.
The test is defined as:

The decision rule for the test is:
If the <em>p</em>-value of the test is less than the significance level of 0.05 then the null hypothesis will be rejected and vice-versa.
Answer:
m=24
Explanation: 120/5=24 just caculate it.