This is an interesting example of rhythm in that the rhythm varies greatly from line to line. The first line is a very straightforward example of trochaic pentameter. After that line, however, there are many shifts in rhythm. The shifts are even more interesting because the first line seems to set up a very standard rhythm. Yet then we see iambs and an example of a spondee, in “cracked hands,” and even sets of three stressed syllables in a row, such as “blueblack cold” and “banked fires blaze” (this more uncommon type of meter is called molossus). The end of this excerpt then returns to a trochaic meter with “No one ever thanked him.” The trochaic lines seem plodding in their straightforward meter and indeed refer to the father’s relentless work, whereas the spondee and molossus examples correspond to the intensity of his work and indeed the most vivid imagery . Hayden uses rhythm brilliantly to suggest the different aspects of the father’s work.
“Estimation statistics” is a fancy way of saying that you are estimating population values based on your sample data. Let’s think back to our sample ice cream data. First, let’s assume that we had a true random sample of 35 people on this globe and that our full target population is every human alive (7 billion people). Let’s say that 37% of people in our sample said that vanilla is their favorite flavor. Can we safely extrapolate that 37% of all people in the world also think that vanilla is the best? Is that the true value of the world? Well, we can’t say with 100% confidence, but–using inferential statistical techniques such as the “confidence interval”–I can provide a range of people that prefer vanilla with some level of confidence.
The mean and median can only be used with numerical data. The mode can be used with both numerical and nominal data , or data in the form of names or labels. Eye color, gender, and hair color are all examples of nominal data. The mean is the preferred measure of central tendency since it considers all of the numbers in a data set; however, the mean is extremely sensitive to outliers , or extreme values that are much higher or lower than the rest of the values in a data set. The median is preferred in cases where there are outliers, since the median only considers the middle values.