Multiple Choice Questions: There could be more than one correct answer-choose all that apply

Describe Questions: Please describe briefly – no more than 500 words
1) Data Mining is:
A. Most applicable in large datasets
B. Discovering patterns and hidden trends in the data
C. Retrospective analyses of data
D. For providing accurate models and correct predictions
2) (T/F) Data Mining requires a good understanding of statistics and computer sciences
3) Data Mining relies on:
A. Cleaned and Curated data
B. Unstructured data
C. Computational efficiency of the algorithm
D. Training data
E. Non-experimental (Observational) data

4) The model selection process depends on several criteria including:
A. Hypothesis to be proved or disproved
B. Type of data available
C. Underlying methods such as association, etc.
D. All of the above

5) (T/F) Association mining typically requires you to identify strong rules for measures of minimum support and threshold.

6) Interestingness of patterns in a dataset can be determined by these methods

A. Correlation
B. Association Rules
C. Classification
D. Lift & Chi Square Test

7) (T/F) R2 is a measure of the explanatory power of the independent variables

8) (T/F) Model fit refers to how well the variables correlate with one another in a model

9) Sensitivity and Specificity are two values useful in:
A. Receiver Operating Characteristic curve
B. Sigmoid curve
C. Logit curve
D. Sinusoidal curve
E. None of the above

10) (T/F): Its best to compare and contrast model by using measures of information criteria AIC/BIC for individual and hybrid models.

11) Statistical inference refers to:
A. Predicting the outcome of a model run
B. Probability of an event occurrence
C. Measuring dependent variable and any error terms to arrive at a solution
D. None of the above

12) (T/F) Sample and Population in Statistics refers to how clean the dataset is before data modeling

13) The following technique is useful for a single descriptive measure of income by age

A. Variance
B. Central Tendency
C. Outliers
D. All of the above

14) (T/F) Probability theory is useful in statistics for improving upon ‘random guess’ related to events occurring

15) Probability of joint occurrence refers to:
A. Two independent events
B. Co-occurring events
C. Conditionally independent events
D. Multiplying the probabilities of individual events

16) In the article: Advanced Scout – Data Mining and Knowledge Discovery in NBA Data
Describe the purpose of creating the data mining software (application) i.e. what value add does it bring?

17) In the article: Advanced Scout – Data Mining and Knowledge Discovery in NBA Data
Describe the 4 general steps used in the application as part of data mining – including possible data structure for the application to read the data from.

18) A few applications of Text Mining & NLP (Natural Language Processing) are:
A. Web reviews and ratings
B. Medic

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