Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as a. approximation. b. overfitting. c. postulating. d. hypothesizing.

Over fitting  

Explanation:

Over fitting is the situation where the model is well fitted with the current data but not fitted for sample data or not able to predict the sample data. This has happened when it is over-relied on the sample pattern and the trends that are going on in trends. The model is only applicable for new sample lonely. The model does not have access to this type of anomalous.

For example the housing data. Many times the model is so flexible and highly liked by the over fitted data.

the old way of life was represented by superstition, an angry god, and absolute submission to authority. the thinkers of the age of reason ushered in a new way of thinking. this new way championed the accomplishments of humankind. individuals did not have to accept despair. science and reason could bring happiness and progress. kings did not rule by divine right. they had an obligation to their subjects. europeans pondered the implications for nearly a century. americans put them into practice first.

answer; knowledge,reason,and judgement;