List of unsolved problems in statistics

Inference and testing

• How to detect and correct for systematic errors, especially in sciences where random errors are large.
• The Graybill–Deal estimator is often used to estimate the common mean of two normal populations with unknown and possibly unequal variances. Though this estimator is generally unbiased, its admissibility remains to be shown.
• Meta-analysis: Though independent p-values can be combined using Fisher's method, techniques are still being developed to handle the case of dependent p-values.
• Behrens–Fisher problem: Yuri Linnik showed in 1966 that there is no uniformly most powerful test for the difference of two means when the variances are unknown and possibly unequal. That is, there is no exact test that is also the most powerful for all values of the variances. Though there are many approximate solutions, the problem continues to attract attention as one of the classic problems in statistics.
• Multiple comparisons: There are various ways to adjust p-values to compensate for the simultaneous or sequential testing of hypothesis. Of particular interest is how to simultaneously control the overall error rate, preserve statistical power, and incorporate the dependence between tests into the adjustment. These issues are especially relevant when the number of simultaneous tests can be very large, as is increasingly the case in the analysis of data from DNA microarrays.
• Bayesian statistics: A list of open problems in Bayesian statistics has been proposed.

  Experimental design

• As the theory of Latin squares is a cornerstone in the design of experiments, solving the problems in Latin squares could have immediate applicability to experimental design.

  Problems of a more philosophical nature

• Sampling of species problem: How is a probability updated when there is unanticipated new data?
• Doomsday argument: How valid is the probabilistic argument that claims to predict the future lifetime of the human race given only an estimate of the total number of humans born so far?
• Exchange paradox: Issues arise within the subjectivistic interpretation of probability theory; more specifically within Bayesian decision theory. This is still an open problem among the subjectivists as no consensus has been reached yet. Examples include:
• * The two envelopes problem
• * The necktie paradox
• Sunrise problem: What is the probability that the sun will rise tomorrow? Very different answers arise depending on the methods used and assumptions made.