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In this study, the comparison was not performed by randomly selecting a sample of men and then assigning some to a low iron level treatment and the others to a high iron level treatment The researchers just tracked the subjects over time Recall from 1 that this type of study is called an observational study It is dif cult to identify causality in observational studies, because the observed statistically signi cant difference in response between the two groups may be due to some other underlying factor (or group of factors) that was not equalized by randomization and not due to the treatments For example, the difference in heart attack risk could be attributable to the difference in iron levels, or to other underlying factors that form a reasonable explanation for the observed results such as cholesterol levels or hypertension.

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The dif culty of establishing causality from observational studies is also seen in the smoking and health controversy Numerous studies show that the incidence of lung cancer and other respiratory disorders is higher among smokers than nonsmokers However, establishing.

cause and effect here has proven enormously dif cult. Many individuals had decided to smoke long before the start of the research studies, and many factors other than smoking could have a role in contracting lung cancer.

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The 100(1 )% con dence interval on the difference in two means 1 2 when the variances are known can be found directly from results given previously in this section. Recall that X11, X12, p , X1n1 is a random sample of n1 observations from the rst population and X21, X22, p , X2n2 is a random sample of n2 observations from the second population. The difference in sample means X1 X2 is a point estimator of 1 2, and Z X1 B n1 X2 1

1 2 2 22

has a standard normal distribution if the two populations are normal or is approximately standard normal if the conditions of the central limit theorem apply, respectively. This implies that P1 z 2 Z z 2 2 1 , or P X1

where h is the MD5 hash function. In other words, the hash value is not just the output of this function, since there is a final transformation and the message is padded. Next, we consider the final transformation; for details on the padding, see Section 5.3. Define f(Iv, = ( Q ~ o , Q62, Q61) + IV, nil) Q63, where (Qfjg,Q 6 2 , Q 6 1 , &so) = MD50 ..63(IV,M ) and the addition is computed modulo 2'32,per 32-bit word. Then f is the MD5 compression function. If we hash a message M = (Mo,M I ) consisting of two 512-bit blocks, we have

1 2 2

If x1 and x2 are the means of independent random samples of sizes n1 and n2 from 2 2 two independent normal populations with known variances 1 and 2, respectively, a 100(1 )% con dence interval for 1 2 is x1 where z

Selecting Flash Control from the Shooting menu opens another menu of ve options that affect the performance of the G11 s onboard ash. If you have attached an external Speedlite to the camera s hot shoe, selecting Flash Control displays a similar menu affecting the ash accessory s performance. All Canon PowerShot cameras have two moving curtains in the shutter mechanism. The front curtain opens the shutter, and the rear curtain closes it. The normal operation of the shutter and ash causes the ash to re immediately when the front curtain opens. This is 1st-curtain sync, and it s ne for most general ash applications. But let s say your subject is moving, and you re panning the camera using a slow shutter speed to pick up some ambient light. Flash photography in this mode produces motion trails in front of the object you re tracking to make it look like it s moving backward. The trick is to get the ash to re right before the shutter closes, thereby showing the motion trails behind the object, and this is exactly what 2ndcurtain sync does. You can set this feature either on the G11 or on the Speedlite, but note that the Speedlite takes precedence over the camera s settings.

h ( M ) = f ( f ( I Vb,f o ) , Ml).

(10-7)

The con dence level 1 is exact when the populations are normal. For nonnormal populations, the con dence level is approximately valid for large sample sizes.

EXAMPLE 10-4

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