Data Entropy — Learn free

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Questions 1–10 of 10

1. In which domain is the term Entropy normally used when applied to data?
Question 1A. Network SecurityB. Data ScienceC. Data WarehousingD. Database AdministrationE. Project Management
2. What does High Entropy mean in a dataset?
Question 2A. The data has been fully validatedB. All values are identicalC. The data is ready for reportingD. More surprises and more unexpected values, which are considered more informativeE. Fewer surprises and less informative values
3. What does Low Entropy mean in a dataset?
Question 3A. Fewer surprises and fewer unexpected values, which are considered less informativeB. More unexpected values that are highly informativeC. The data contains many errorsD. The data cannot be storedE. Every value has a probability of zero
4. By what other name is Entropy described?
Question 4A. Perfect Order of valuesB. Average Deviation of valuesC. Central Tendency of valuesD. Normal Distribution of valuesE. Extreme Disorder of values
5. In the plus-and-minus illustration of Entropy from I Am Datapedia!, where is Entropy at its lowest?
Question 5A. In the circles where the mix of pluses and minuses cannot be determinedB. In every circle equallyC. At the starting point where all the signs are MINUSD. Only in the second circleE. Wherever the values are hidden
6. How is probability treated when analysing results in terms of Entropy?
Question 6A. The higher the probability, the more informative the outcomeB. The lower the probability, the better the outcomeC. Probability is ignored entirelyD. Only probabilities above 50% are consideredE. Probability is only used for structured data
7. In the context of Entropy, what counts as informative information?
Question 7A. Information that has been verified by an auditorB. Information that is repeated in every recordC. Information that comes from a trusted sourceD. Information stored in a data dictionaryE. Something that was not already known
8. Which of the following is NOT true of how Entropy is used in Data Science?
Question 8A. Surprises are avoided at all costsB. Finding unexpected outcomes is the aimC. Results are analysed based on a probability ratioD. It helps Data Scientists try to predict unknown valuesE. More unexpected values are considered more informative
9. What is the situation for a Data Scientist when Entropy in a dataset is at its lowest?
Question 9A. The data must be discardedB. The model will produce the most surprisesC. The data is at its most informativeD. No surprises are expected, so there is not much to predictE. The probability of every value is unknown
10. What do Data Scientists use the concept of Entropy for?
Question 10A. Compressing datasets before storageB. Designing database schemasC. Finding unknown values and trying to predict themD. Assigning user access rightsE. Scheduling batch jobs