We measure the direct CP violation asymmetry, A_CP, in B to X_s gamma and the isospin difference of the asymmetry, Delta A_CP, using 429 fb^-1 of data collected at Upsilon(4S) resonance with the BaBar detector at the PEP-II asymmetric-energy e+e- sto
rage rings operating at the SLAC National Accelerator Laboratory. B mesons are reconstructed from 10 charged B final states and 6 neutral B final states. We find A_CP = +(1.7 +- 1.9 +- 1.0)%, which is in agreement with the Standard Model prediction and provides an improvement on the world average. Moreover, we report the first measurement of the difference between A_CP for charged and neutral decay modes, Delta A_CP = +(5.0 +- 3.9 +- 1.5)%. Using the value of Delta A_CP, we also provide 68% and 90% confidence intervals on the imaginary part of the ratio of the Wilson coefficients corresponding to the chromo-magnetic dipole and the electromagnetic dipole transitions.
The BaBar collaboration has an extensive program of studying hadronic cross sections in low-energy e+e- collisions, accessible via initial-state radiation. Our measurements allow significant improvements in the precision of the predicted value of the
muon anomalous magnetic moment. These improvements are necessary for illuminating the current ~3.6 sigma difference between the predicted and the experimental values. We have published results on a number of processes with two to six hadrons in the final state. We report here the results of recent studies with final states that constitute the main contribution to the hadronic cross section in the energy region between 1 and 3 GeV, as e+e- to K+K-, pi+pi-, and e+e- to 4 hadrons.
Combining measurements which have theoretical uncertainties is a delicate matter, due to an unclear statistical basis. We present an algorithm based on the notion that a theoretical uncertainty represents an estimate of bias.
Several approaches to testing the hypothesis that two histograms are drawn from the same distribution are investigated. We note that single-sample continuous distribution tests may be adapted to this two-sample grouped data situation. The difficulty
of not having a fully-specified null hypothesis is an important consideration in the general case, and care is required in estimating probabilities with ``toy Monte Carlo simulations. The performance of several common tests is compared; no single test performs best in all situations.
