ANS: No, since a histogram cannot detect non-stationarity.
ANS: A time series plot of force versus time. It can tell her when the process begins becoming non-stationary, and therefore help in quickly dientifying problems.
ANS: Location: mode, 500, which is at the center of the highest bars, or the median, 565.5, above which and below which lies half the data. Spread: IQR, 837.5-358.5=479, the spread of the middle half of the data.
ANS: The lower adjacent value is 48, which is the smallest data value greater than . The upper adjacent value is 1547, which is the largest data value less than . The rest of the five number summary consists of Q1=358.5, Q2=565.5 and Q3=837.5. The boxplot is in Figure 2.
ANS: The mode, 500, which is at the center of the highest bars. These are the bars containing the greatest number of observations.
ANS: No. Treatments were not assigned to experimental units.
ANS: Outcome: death or not within 30 days.
ANS: Because researchers were not allowed to control assignment of treatment to patients, or to control or randomize with respect to nuisance variables, the results can only suggest an association, not establish cause-effect.
ANS: I would design a controlled experiment in which treatments (right heart catheterization or alternative procedures) were assigned to patients by the researchers. Blocking could involve factors such as hospital, surgeon, severity of patient illness, patient age, patient gender, etc., and would be used to reduce variation in the responses due to those factors. Randomization would be used for whatever was not blocked to remove unsuspected sources of bias. For example, within blocks, treatments would be assigned to patients at random.