One of the biggest concerns in science is that scientists themselves may influence the outcomes of experiments.Scientists have come up with all sorts of strategies to try to get rid of this problem.
   But gathering the data and running an experiment is not the only part of the process that can go wrong.The methods chosen to analyse the data can also influence results.This point was dramatically demonstrated by two recent papers published in a journal called Surgery.Despite being based on the same data set，they drew opposite conclusions about whether using a particular piece of kit（成套設(shè)備） during appendix removal surgery reduced or increased the chances of infection.
   A new paper，from a large team of researchers headed by Martin Schweinsberg，a psychologist at the European School of Management and Technology，in Berlin，helps cast some light on why.Dr Schweinsberg gathered 49 different researchers by advertising his project on social media.Each was handed a copy of a data set consisting of 3.9 m words of text from nearly 8，000 comments made on Edge.jye.ai，an online forum for chatty intellectuals.
   In the end，37 analyses were regarded sufficiently detailed to include.As it turned out，no two analysts employed exactly the same method，and none got the same result.The problem was not that any of the analyses was "wrong" in any objective sense.The differences occurred because researchers chose different definitions of what they were studying，and applied different techniques.
   Truth，in other words，can be a slippery customer，even for simple-sounding questions.What to do？One conclusion is that experimental design is critically important.Dr Schweinsberg hopes that platforms such as Data Explained can help solve the problem as well as revealing it，by allowing scientists to specify exactly how they chose to perform their analysis，allowing those decisions to be reviewed by others.It is probably not practical，he admits，to check and re-check every result.But if many different analytical approaches point in the same direction，then scientists can be confident that their conclusion is the right one.

（1）Why did the two papers get different results？

D

D

A．Some analyses were conducted in a new way.
B．Some experimental techniques were unreliable.
C．Various data were adopted randomly and indirectly.
D．Different methods were applied in the data analysis.
（2）Which is TRUE according to Paragraphs 3 and 4？

B

B

A．2 analyses were considered not good enough.
B．37 researchers were found to get different results.
C．49 researchers were gathered to discuss an issue.
D．37 analyses were regarded to use the same method.
（3）What does the underlined part "a slippery customer" refer to？

B

B

A．A person who is extremely critical.
B．Someone who can't be trusted.
C．A person who is willing to speak frankly.
D．Someone who can raise questions skillfully.
（4）What can be learned from the whole passage？

C

C

A．Different results come from the same experimental design.
B．The more data are collected，the more truthful the results will be.
C．Data don't lie，but they can lead scientists to opposite conclusions.
D．The outcomes of experiments come from the cooperation of scientists.