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BIDA 630 DATA ANALYTICS QUESTIONS AND CORRECT ANSWERS | LATEST UPDATE

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Identify whether the task required is supervised or unsupervised learning: Deciding whether to issue a loan to an applicant based on demographic and financial data (with reference to a database of similar data on prior customers). - Supervised - Unsupervised -:- Supervised This is supervised learning, because the database includes whether the loan was approved or not. Identify whether the task required is supervised or unsupervised learning: Printing of custom discount coupons at the conclusion of a grocery store checkout based on what you just bought and what others have bought previously. 2 | P a g e | G r a d e A + | 2 0 2 4 / 2 0 2 5 2 0 2 4 /2025 | © copyright | This work may not be copied for profit gain | Excel! - Supervised - Unsupervised -:- Unsupervised This is unsupervised learning, if we assume that we do not know what will be purchased in the future. The test data are used to build models, or to further tweak the model or improve its fit. - True - False -:- False The test data are not used to build models, or to further tweak the model or improve its fit. (If the test data were used for these purposes, they would play a role in building or selecting the best model, and would no longer provide an unbiased assessment of the chosen model's performance with completely new data.) 3 | P a g e | G r a d e A + | 2 0 2 4 / 2 0 2 5 2 0 2 4 /2025 | © copyright | This work may not be copied for profit gain | Excel! _____________ of data is used to assess the performance of each supervised learning model so that we can compare models and pick the best one. - The test partition - The validation partition -:- Validation The validation partition is used to assess the performance of each supervised learning model so that we can compare models and pick the best one. In some algorithms (e.g., classification and regression trees, k-nearest neighbors) the validation partition may be used in automated fashion to tune and improve the model. This means that the validation data are actually used to help build the model. When a model is fit to training data, zero error with those data is not necessarily good. This special case is called ______. - Overestimating - Good fit 4 | P a g e | G r a d e A + | 2 0 2 4 / 2 0 2 5 2 0 2 4 /2025 | © copyright | This work may not be copied for profit gain | Excel! - Overfitting -:- Overfitting Overfitting occurs when the model captures not only the generalizeable pattern in the data, but also the error. When we split the data into training and validation sets, we assume that the same pattern (if there is a pattern) exists in both, and that they differ only in the error that they contain. An absurd and false model may fit perfectly (on training data set) if the model has enough complexity. Therefore, we may get zero error for such a model using the training dataset. Such a model, however, is not likely to give useful results on the validation data set. Bar charts are useful for comparing a single statistic (e.g. average, count, percentage) across groups. The height of the bar represents the value of statistic, and different bars correspond to different groups. - True - False -:- True 5 | P a g e | G r a d e A + | 2 0 2 4 / 2 0 2 5 2 0 2 4 /2025 | © copyright | This work may not be copied for profit gain | Excel! Which of the following are the most popular visualization tools in JMP_Pro? (3 correct answers) - Distribution - Fit Y by X - Graph Builder - Data visualizer - Graph wizard -:- - Distribution - Fit Y by X - Graph Builder Scatter plots play important role in prediction. Next step can be developing a model. Scatter plots provide information about relationships (linear or non-linear) between variables. The variables in scatter plot ________. - can be nominal

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BIDA 630
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2024 /2025 | © copyright | This work may not be copied for profit gain | Excel!




BIDA 630 DATA ANALYTICS
QUESTIONS AND CORRECT ANSWERS |
LATEST UPDATE
Identify whether the task required is supervised or unsupervised learning: Deciding whether

to issue a loan to an applicant based on demographic and financial data (with reference to a

database of similar data on prior customers).




- Supervised


- Unsupervised


✓ -:- Supervised




This is supervised learning, because the database includes whether the loan was approved or

not.




Identify whether the task required is supervised or unsupervised learning: Printing of custom

discount coupons at the conclusion of a grocery store checkout based on what you just

bought and what others have bought previously.




1|P a g e | G r a d e A + | 2 0 2 0 2 5

,2024 /2025 | © copyright | This work may not be copied for profit gain | Excel!




- Supervised


- Unsupervised


✓ -:- Unsupervised




This is unsupervised learning, if we assume that we do not know what will be purchased in

the future.




The test data are used to build models, or to further tweak the model or improve its fit.




- True


- False


✓ -:- False




The test data are not used to build models, or to further tweak the model or improve its fit.

(If the test data were used for these purposes, they would play a role in building or selecting

the best model, and would no longer provide an unbiased assessment of the chosen model's

performance with completely new data.)




2|P a g e | G r a d e A + | 2 0 2 0 2 5

, 2024 /2025 | © copyright | This work may not be copied for profit gain | Excel!




_____________ of data is used to assess the performance of each supervised learning

model so that we can compare models and pick the best one.




- The test partition


- The validation partition


✓ -:- Validation




The validation partition is used to assess the performance of each supervised learning model

so that we can compare models and pick the best one. In some algorithms (e.g.,

classification and regression trees, k-nearest neighbors) the validation partition may be used

in automated fashion to tune and improve the model. This means that the validation data

are actually used to help build the model.




When a model is fit to training data, zero error with those data is not necessarily good. This

special case is called ______.




- Overestimating


- Good fit


3|P a g e | G r a d e A + | 2 0 2 0 2 5

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