The phrase "in simple situations" is correct and usable in written English.
It is typically used as a prepositional phrase to describe the specific context or circumstances in which something occurs. Example: In simple situations, using basic math skills can come in handy for everyday tasks like budgeting and calculating tip at a restaurant.
We show how the new test corresponds to familiar tests in simple situations for independent, exchangeable, paired, and clustered data.
For many functions it is easy to estimate the OBDD size but asymptotically optimal bounds are only known in simple situations.
In particular, it figures as part of a conception of rationality whose dictates provide intuitively sensible guidance not only in simple situations but also in challenging dynamic choice situations.
In other words, the method is robust in simple situations and with the use of a single array; however, it generally fails when distributed arrays are used, and when early reflections and head orientation issues are to be addressed.
Mantel-Haenszel estimates are easy to obtain in simple situations such as the ones dealt with in this work (one exposure and one confounder).
In simple situations where there is a single acoustical stimulus (e.g., tone) with unknown ITD, theoretical arguments show that a summation code is optimal at low frequencies (Harper and McAlpine, 2004).
In simpler situations, you can usually just use the return rate on a savings account, stock investment, etc. that you might put your money in instead of making the investment you're analyzing.
In the one approach (often proposed in the literature) the finite-dimensional model leads to an ill-posed problem even in very simple situations.
However, all three have the same basic drawback: it is difficult for a software program to take into account all the complex situations that can arise when dividing one's estate, even in seemingly simple situations.
It also shows that, except in such simple situations, no polynomial-time algorithm can produce a theory whose error is even close to (i.e., within a particular polynomial factor of) optimal.
It then considers the computational complexity of finding this best theory, and proves that, unless P = NP, no polynomial-time algorithm can identify this optimal revision, even given the exact distribution of queries, except in certain simple situations.
