So they both go into 24 so
20/24 - 24/24
They answer is 4/24
You can ruduce that to 2/12 or 1/6
Answer:
Step-by-step explanation:
Hello!
The variable of interest is:
X: height of seaweed.
X~N(μ;σ²)
μ= 10 cm
σ= 2 cm
You have to find the value of the variable X that separates the bottom 0.30 of the distribution from the top 0.70
P(X≤x)= 0.30
P(X≥x)= 0.70
Using the standard normal distribution you have to find the value of Z that separates the bottom 0.30 from the top 0.70 and then using the formula Z= (X-μ)/σ translate the Z value to the corresponding X value.
P(Z≤z)= 0.30
In the body of the table look for the probability of 0.30 and reach the margins to form the Z value. The mean of the distribution is "0" so below 50% of the distribution you'll find negative values.
z= -0.52
Now you have to clear the value of X:
Z= (X-μ)/σ
Z*σ= X-μ
X= (Z*σ)+μ
X= (-0.52*2)+10= 8.96
The value of seaweed height that divides the bottom 30% from the top 70% is 8.96 cm
I hope this helps!
Answer:
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Step-by-step explanation:
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Answer:
A. 12.68 - 14.72 hours
B. Normal distribution.
Step-by-step explanation:
Part A
This question is using quantitative data. A 99% confidence interval means that you want to know the range where 99% of the population will be. To find this you have to convert the 99% CI into the z-score which is -2.58SD to + 2.58SD.
Note that the standard deviation(SD) is from the sample, not the population. We still need to find the standard deviation of the population. The formula is:
population SD = ![\frac{o}{\sqrt[]{n} }](https://tex.z-dn.net/?f=%5Cfrac%7Bo%7D%7B%5Csqrt%5B%5D%7Bn%7D%20%7D)
Where the o= sample SD = 7.4
n= number of sample = 463
The calculation will be:
population SD = ![\frac{o}{\sqrt[]{n} }](https://tex.z-dn.net/?f=%5Cfrac%7Bo%7D%7B%5Csqrt%5B%5D%7Bn%7D%20%7D)
population SD =
= 0.3951
The bottom limit will be:
Mean - SD * z-score= 13.7 - 0.3951*2.58 = 12.68 hours
The upper limit will be:
Mean + SD * z-score= 13.7 + 0.3951*2.58 =14.72 hours
The 99% CI range will be 12.68 - 14.72 hours
Part B
The table used to convert confidence interval into z-score depends on the distribution type of the data. Most data is classified as normal distributed, a data type that will concentrated at mean and spread equally from the mean. Normal distribution data will look like a bell which make it also called bell curve.
The question tells you that the data is normal distribution, but that doesn't mean every data is normally distributed. There are a lot of other data distribution type so we have to do some tests to know the normality of the data in real-life data.