The phrase "a challenging term" is correct and usable in written English.
It can be used when referring to a word or phrase that is difficult to understand or requires significant effort to grasp.
Example: "The professor introduced a challenging term that left many students puzzled during the lecture."
Alternatives: "a difficult term" or "a complex term".
Making several good R datasets available is a necessary condition for completing a challenging term project.
But it is even more clear that at the primary level, this could be a challenging term.
However, for a challenging term project, such as replicating the so-called MAX trading strategy suggested by Bali et al. (2011), it is not feasible to ask students to generate (CRSP 2018 -related R datasets themselves.
This paper explains seven critical factors for designing and teaching a programming course: strong motivation, a good textbook, hands-on learning environment, being data intensive, a challenging term project, multiple supporting R datasets, and an easy way to upload such R datasets.
The Table 3 below shows a few challenging term projects.
Obama is looking at some sort of foreign policy legacy after what has been a very challenging term.
To put a finer point on this challenging term, what is it, from the standpoint of respective adherents, that sets apart the Torah, Quran, Bible, Bhagavad Gita, Guru Granth Sahib, or any other text in which one senses the sacred, from the countless other writings in the human canon of narrative?
Asked about the timing of the hirings, Mr. Bloomberg said it was important to recruit skilled managers for a challenging third term: "If there's any group that I wouldn't want to cut in tough times, it's those that can guide people and incent people and excite people to do more with less".
Whenever possible, it is a good idea to use (CRSP 2018) to finish many challenging term projects.
To help a potential instructor design and teach such a course, this brief paper summarizes the numerous determinants into seven unique and significant ones: strong motivation, good textbook, hands-on environment, being data intensive, challenging term project, making supporting R datasets available, and an easy way to upload those R datasets quickly.
