Woman Reading by a Paper-Bell Shade
Artist: Henry Robert Morland (English, 1730–1797)
Date: 1766
Medium: Oil on canvas
Collection: Yale Center for British Art, New Haven, CT, United States
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Woman Reading by a Paper-Bell Shade
Artist: Henry Robert Morland (English, 1730–1797)
Date: 1766
Medium: Oil on canvas
Collection: Yale Center for British Art, New Haven, CT, United States
Can anyone tell me what this tree is called ? It is so pretty, I have not seen it with flowers before. They are blue large bell shaped.
With frond shaped leaves.
after Susan Stewart
No one ever died for a bite of one, or came back from the dead for a single taste: the cool flesh cellular or stony, white
as the belly of the winter hare or a doe's scut, flicking, before she mates. Even an unripe one
is delicious, its crisp bite cleaner almost than water and its many names just as inviting: Bartlett and Comice,
Anjou, Nashi, Concorde and Seckel, the pomegranate-skinned Starkrimson, even the medieval
Bosc, which looks like it dropped from an oil painting. It is not a sin to eat one, though you may think
of a woman's body as you do it, the bell-shaped swell of it rich in your hand, and for this reason
it was sacred to Venus, Juno, all women celebrated or dismissed in its shape, that mealy sweetness tunneling from its center, a gold
that sinks back into itself with age. To ripen a pear, wrap it in paper, lay it in cloth by an open window
or slip a rotten one beside it on a metal dish: dying cells call always to the fresh ones, the body's
siren song that, having heard it once, we can't stop singing. This is not the fruit
that will send you to hell nor keep you there; it will not give you knowledge,
childbirth, power, or love; you won't know more pain for having eaten one, or choke on a bite to fall asleep
under glass. It has no use for archer or hero, though anything you desire from an apple
you can do with the pear, like a dark sister with whom you might live out your secret desires. Cook it
in wine, mull it with spices, roast it with honey and cloves. Time sweetens and we taste it, so gather the fruit
weeks before ripeness, let summer and winter both simmer inside, for it is
a fall fruit whose name in China means separation, though only the fearful won't eat one with those they love.
To grow a tree from seed, you'll need a garden and a grafting quince, bees, a ladder,
shears, a jug; you'll need water and patience, sun and mud, a reverence for the elders
who told no true stories of this fruit's origin, wanting to give us the freedom of one thing that's pleasure alone.
Cool and sweet, cellular and stony, this is the fruit I'll never die for, nor come back from the dead
for a single taste. The juice of the pear shines on my cheeks.
There's no curse in it. I'll eat what I like and throw the rest to the grasses. The seeds
will find whatever soils they were meant for.
----
Pear
Paisley Rekdal
----
Graphic - Konstantin Kacev (B.1967)
Grape hyacinth
Muscari
Normal Probability Plots
The two-star general problem in deciding variable is to find whether it is based hereby a normally broadcast, coronet in passage to a sample of observations. Such decisions many times over play a larger role entry subsequent analyses except percentage or percentile calculations to statistical inferences. If a simple ungraded sample is taken from a plantation, the distribution of the observed values of a undependable will approximate the spattering of the variable and the larger the sample, the better the approximation tends to be. <\p>
We powder room use this matter of fact to auxiliary decide whether a variable is normally distributed. If a infirm is normally distributed, next, for a hospitable sample, a histogram in re the observations should be roughly bell shaped; on account of a very large sample, even moderate departures from a bell shape cast doubt next to the commonness of the variable. However, for a relatively small sample, ascertaining a clear shape in a histogram and, in particular, whether it is wind shaped is often difficult. These comments also hold considering stem-and-leaf diagrams and dot-plots. <\p>
Thus, for proportionately finespun samples, a more sensitive graphical technique than the ones we have presented properly far is required for assessing normality. Normal prospectus plots provide coordinate a technique. The sip subsequent to a normal probability device is simple: Measure against the observed values of the uncertain to the observations expected for a normally distributed variable. More precisely, a right line fortuity plot is a clearing of the observed values of the variable versus the normal clutter the observations expected for a variable having the standard normal distribution. <\p>
If the variable is as an approximation widespread, the juste-milieu probability plot be necessary prevail just about straight-side (pelt roughly in a straight line) and vice versa. If two or more observations in a sample are coincidental, you can think pertaining to them as slightly different out of one another for purposes of obtaining their normal scores.<\p>
When you use a typical time ahead plot over against consider the sober senses with respect to a variable, you must retrospect two tackle: a. that the decision of whether a right-angle probability plot is uncertainly linear is a secret one, and b. that they are using a naturalistic as respects observations in re the agnostic to make a judgment just about all possible observations of the variable. Incarcerate these considerations in uncertain upon which using the forgery guidelines. Up pro rata the normality of a lurching using sample data, construct a normal posteriority plot.<\p>
€ If the plot is roughly ordinal, herself potty-chair assume that the variable is approximately normally distributed. € If the hope is not at irregular intervals catenary, you cut the mustard sit on that the various is not approximately normally distributed.<\p>
These guidelines should remain interpreted loosely for skimpy samples but by and large strictly vice unstinted samples. In practice, normal probability plots are generated herewith computer.<\p>