Answer:
The requirements are missing, so I looked for similar questions. You should make any necessary adjusting entries on the accounting equation. Since there is not enough room here, I used an excel spreadsheet.
Answer:
The correct answer is Inductive reasoning.
Explanation:
Inductive reasoning is a form of reasoning in which the truth of the premises supports the conclusion, but does not guarantee it. A classic example of inductive reasoning is:
- All the crows observed so far have been black
- Therefore, all crows are black
In principle, it could be that the next crow observed is not black. In contrast to deductive reasoning, inductive reasoning has the advantage of being expansive, that is, the conclusion contains more information than is contained in the premises. Given its expansive nature, inductive reasoning is very useful and frequent in science and in everyday life. However, given its fallible nature, its justification is problematic. When are we justified in making an inductive inference, and concluding, for example, that all crows are black from a limited sample of them? What distinguishes a good inductive argument from a bad one? These and other related problems give rise to the problem of induction, whose validity and importance has continued for centuries.
Answer:
Mary has increased her data literacy skills that now allow her to access, interpret, summarize, and communicate data more effectively.
Explanation:
Data analysis is the process by which data is transformed in such a way that useful information can be extracted from it. Data analysis is a key skill that is needed in most business nowadays, for example; financial data can be very crucial in the planning, budgeting and execution of projects. The process of data analysis has been automated to take raw data and produce a result that can be readily consumed easily by humans in the form of charts and graphs. From this end result, conclusions can be drawn by data experts on what the results mean.
Experts in data analysis are therefor needed to adequately access, interpret, summarize and communicate data more effectively. These are skills that need to be learned for better overall quality of the data presentation. In general, the principals are referred to as data literacy skills. Data literacy can be defined as the ability of an individual to extract useful information from raw data.
Answer:
Go in for a traditional shirt-jeans outfit and pair it with black formal shoes. A plaid shirt, pair of blue jeans and black dress shoes is how you'll want to rock it! Get that macho look right by wearing a leather jacket over a formal shirt and jeans. Your shoes will complement the jacket perfectly.
Explanation:
