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BIDA 630 Data Analytics exam with complete solutions 2024_2025. $11.49   Add to cart

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BIDA 630 Data Analytics exam with complete solutions 2024_2025.

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  • Course
  • BIDA 630
  • Institution
  • BIDA 630

BIDA 630 Data Analytics exam with complete solutions 2024_2025.

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  • September 15, 2024
  • 12
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • BIDA 630
  • BIDA 630
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BIDA 630 Data Analytics exam with
complete solutions 2024/2025




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 - ANSWER- 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.

- Supervised
- Unsupervised - ANSWER- 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 - ANSWER- 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.)

, _____________ 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 - ANSWER- 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
- Overfitting - ANSWER- 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 - ANSWER- True

Which of the following are the most popular visualization tools in JMP_Pro? (3 correct
answers)

- Distribution
- Fit Y by X
- Graph Builder

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