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Answer :
Final answer:
The sample standard deviation for the given data set of body temperatures is approximately 0.7°F when rounded to one more decimal place than the largest number of decimal places given in the data.
Explanation:
The sample standard deviation can be calculated by following several steps. First, find the mean (the average) of your data set. You do this by adding up all the data points and dividing by the number of data points. In this case, the mean temperature is 98.1ºF. Next, subtract the mean from each data point, then square the result. Now, add up all these squared quantities and divide by the total number of data points minus one (this is one key difference between a sample standard deviation and a population standard deviation). Finally, square root the result. When you apply these steps to the given body temperatures, you get an approximate sample standard deviation of 0.7°F, when we round to one more decimal place than the largest number of decimal places given in the data.
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Answer:
SE = 0.1590 (approx.)
Step-by-step explanation:
By sample standard deviation, we mean standard error. Hence, we have that:
SE = [tex]\frac{\sigma}{\sqrt(n)} }[/tex]
Therefore, Standard deviation (σ) = 0.6929891
The sample size (n) = 19.
Hence:
SE = 0.1589826.
SE = 0.1590 (approx.)
########## The R codes below#########################
f = c(98.0, 98.2, 97.9, 98.7, 97.8, 98.5, 98.8, 97.9, 99.3, 97.9, 96.7, 97.5,
98.6, 96.6, 98.2, 97.6, 98.2, 99.0, 97.8)
n=length(f)
ssd = sd(f)/sqrt(n)
###################################################
