Question

One objective of data mining is the discovering of patterns in data that can lead to reasonable predictions.

a) True
b) False

Answer 1

True, data mining aims to discover patterns for prediction. 'Suggestion' is closest in meaning to hypothesis. Scientific theories do not become laws over time, and data contradicting a hypothesis is still useful, as is non-experimental investigation.

Step-by-step explanation:

One of the central objectives of data mining is indeed the discovery of patterns within large sets of data to enable reasonable predictions about future trends or behaviours, making the answer to the first question True. When it comes to scientific inquiry, a hypothesis serves as a tentative explanation or prediction that can be tested through research and experimentation. The word that is closest in meaning to hypothesis from the given options is d. suggestion.

The Scientific Method

The scientific method follows a structured approach where a hypothesis is made, then tested through various means such as experiments or observational studies. An example of the normal functioning of the scientific method would be:

1. Observing a natural phenomenon.
2. Formulating a hypothesis to explain it.
3. Conducting experiments to test the hypothesis.
4. Analyzing the results and drawing a conclusion.

The statement 'When a theory has been known for a long time, it becomes a law' is False. Scientific laws and theories serve different purposes; a law describes a consistent observation, whereas a theory provides the explanatory framework for those observations.

Data that does not support a hypothesis is still incredibly useful, as it can lead scientists to revise their hypothesis or explore new directions, so the answer is False for the question about the usefulness of data that does not support a hypothesis. Likewise, experimentation is a critical method of investigation in science, but it is not the only valid type, so this statement is also False.

Political scientists, like those in other fields, can make better predictions when they have b. lots of data, among other factors. Having ample data allows for more robust analysis and potentially more accurate predictions