Unit 1: Introduction to Data Science - Practice Quiz

ECAP792 60 Questions
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1 What is a primary reason for learning data science?

Why learn data science? Easy
A. To eliminate the need for databases
B. To replace all computer hardware
C. To extract useful insights from data
D. To avoid making business decisions

2 What does the data analytics life cycle describe?

Life cycle of data analytics Easy
A. The history of programming languages
B. The stages of an analytics project
C. The schedule of network maintenance
D. The physical lifespan of a computer

3 What is a key activity during data discovery?

Data discovery Easy
A. Deploying a finished model
B. Understanding available data sources
C. Publishing the final report
D. Replacing missing values

4 Which task is commonly performed during data preparation?

Data preparation Easy
A. Defining business objectives
B. Presenting final conclusions
C. Cleaning incorrect data values
D. Deploying models to users

5 What is selected during model planning?

Model planning Easy
A. Company hiring policies
B. Suitable analytical methods
C. Presentation color themes
D. Final deployment servers

6 What happens during model building?

Model building Easy
A. Business goals are first identified
B. Analytical models are trained
C. Final results are presented
D. Data sources are initially located

7 What is the main purpose of communicating results?

Communicate results Easy
A. To collect additional raw data
B. To train every possible model
C. To explain findings to stakeholders
D. To repair damaged computer systems

8 What does operationalization usually involve?

Operationalization Easy
A. Listing possible data sources
B. Cleaning the initial dataset
C. Selecting a research question
D. Deploying a model for use

9 Which is a recognized type of data analysis?

Type of data analysis Easy
A. Electrical analysis
B. Structural analysis
C. Mechanical analysis
D. Predictive analysis

10 Which question does descriptive analysis primarily answer?

Descriptive analysis Easy
A. What should happen?
B. What will happen?
C. What happened?
D. Why did it happen?

11 Which question does diagnostic analysis primarily answer?

Diagnostic analysis Easy
A. What will happen later?
B. What should happen next?
C. What is happening now?
D. Why did it happen?

12 What is the purpose of predictive analysis?

Predictive analysis Easy
A. To explain only known causes
B. To summarize only past records
C. To recommend a specific action
D. To estimate future outcomes

13 Which question does prescriptive analysis primarily answer?

Prescriptive analysis Easy
A. Why did it happen?
B. What may happen next?
C. What happened before?
D. What should be done?

14 Which list contains the four common types of data analytics?

Types of data analytics Easy
A. Numeric, textual, visual, audible
B. Raw, cleaned, coded, deployed
C. Local, remote, public, private
D. Descriptive, diagnostic, predictive, prescriptive

15 How are missing values usually handled in an analytics project?

Data preparation Easy
A. During result communication
B. During operational deployment
C. During data preparation
D. During business discovery

16 Which stage commonly follows communicating the results in the data analytics life cycle?

Life cycle of data analytics Easy
A. Data preparation
B. Model planning
C. Operationalization
D. Data discovery

17 Which tool is especially useful for communicating analytical findings?

Communicate results Easy
A. An unrelated database table
B. An undocumented code file
C. A clear data visualization
D. An unorganized data dump

18 Which item should be clarified during data discovery?

Data discovery Easy
A. The completed model parameters
B. The final presentation design
C. The final model deployment date
D. The business problem to solve

19 Why is a model tested after it is trained?

Model building Easy
A. To identify every data source
B. To design the final presentation
C. To replace the project objective
D. To evaluate model performance

20 How can data science support an organization?

Why learn data science? Easy
A. By avoiding the use of evidence
B. By guaranteeing every prediction
C. By removing all uncertainty
D. By improving data-driven decisions

21 An online retailer wants to increase repeat purchases using its transaction and browsing data. Which data science application best supports this goal?

Why learn data science? Medium
A. Replacing all customer support agents
B. Increasing every product price equally
C. Building personalized product recommendations
D. Storing transactions without analyzing them

22 A team has defined its business problem and identified relevant data sources. What should it generally do next in the data analytics life cycle?

Life cycle of data analytics Medium
A. Publish conclusions to all stakeholders
B. Remove monitoring from the workflow
C. Deploy the final model immediately
D. Prepare and clean the collected data

23 During data discovery, a hospital team finds that patient identifiers differ across two databases. What is the most appropriate initial response?

Data discovery Medium
A. Assume the identifiers refer to different patients
B. Document the inconsistency and assess matching rules
C. Train a model using only record order
D. Delete all records from one database

24 A dataset contains missing ages, and the analyst plans to evaluate a predictive model on a test set. Which approach best avoids data leakage?

Data preparation Medium
A. Replace every missing age with zero
B. Estimate replacements from the complete dataset
C. Estimate replacements from training data only
D. Remove the age column after testing

25 A bank wants to predict whether each loan applicant will default within one year. Which modeling task should be planned?

Model planning Medium
A. Time-series decomposition
B. Binary classification
C. Customer clustering
D. Association rule mining

26 Only 2% of transactions in a dataset are fraudulent. Which evaluation measure is generally more informative than accuracy for model planning?

Model planning Medium
A. Total record count
B. Number of input columns
C. Average transaction date
D. Precision and recall

27 A model performs very well on training data but poorly on validation data. Which action is most likely to improve its generalization?

Model building Medium
A. Add the validation labels as features
B. Evaluate it on training data again
C. Reduce complexity or add regularization
D. Remove all validation observations

28 An analyst must explain a sales forecasting model to regional managers. Which presentation is most effective?

Communicate results Medium
A. A complete listing of model parameters
B. A derivation of each optimization equation
C. A raw export of every sales record
D. A forecast chart with uncertainty and actions

29 A deployed demand model becomes less accurate after customer behavior changes. Which operational practice would detect this problem?

Operationalization Medium
A. Archiving the original project proposal
B. Increasing the size of presentation slides
C. Monitoring prediction error and data drift
D. Renaming fields in the training dataset

30 Website conversions fell last month. An analyst compares traffic sources, page errors, and device categories to determine the cause. What type of analysis is this?

Type of data analysis Medium
A. Diagnostic analysis
B. Descriptive analysis
C. Predictive analysis
D. Prescriptive analysis

31 A manager asks for a summary of last quarter's revenue by region and product category. Which output best addresses the request?

Descriptive analysis Medium
A. A model of customer churn causes
B. A grouped revenue dashboard
C. A next-quarter demand forecast
D. An optimized delivery schedule

32 A factory's defect rate increased from 3% to 7%. Which method is most suitable for investigating the increase?

Diagnostic analysis Medium
A. Optimize prices for defective products
B. Compare defects across machines and shifts
C. Forecast defects for the next five years
D. Report only the overall defect count

33 A telecommunications company uses past customer behavior to estimate which subscribers may cancel next month. What is the primary output?

Predictive analysis Medium
A. A churn probability for each subscriber
B. A summary of last month's cancellations
C. A reason for every previous cancellation
D. A retention offer assigned under constraints

34 A delivery company has predicted tomorrow's package volumes. It must now assign trucks while minimizing cost and meeting capacity limits. Which approach is appropriate?

Prescriptive analysis Medium
A. Unconstrained demand forecasting
B. Constrained route optimization
C. Historical volume summarization
D. Delivery-delay root-cause analysis

35 Which sequence correctly progresses from understanding past performance to recommending a future action?

Types of data analytics Medium
A. Predictive, prescriptive, descriptive, diagnostic
B. Diagnostic, descriptive, prescriptive, predictive
C. Descriptive, diagnostic, predictive, prescriptive
D. Prescriptive, predictive, diagnostic, descriptive

36 A customer dataset has a nominal feature called payment_method with values such as card, cash, and transfer. Which transformation is suitable for many machine-learning models?

Data preparation Medium
A. Delete all rows containing payment methods
B. Sort categories alphabetically as measurements
C. Replace categories with their frequencies only
D. Create one-hot encoded indicator columns

37 During model building, a team discovers that inconsistent measurement units are reducing accuracy. What should the team do?

Life cycle of data analytics Medium
A. Skip directly to production deployment
B. Change the business objective after deployment
C. Hide the issue in the final presentation
D. Return to data preparation and standardize units

38 An analyst tunes several models using the validation set. How should the analyst obtain a less biased estimate of the selected model's final performance?

Model building Medium
A. Retrain and score it on identical rows
B. Report its best validation score only
C. Evaluate it once on an untouched test set
D. Select the model using the test labels

39 A model estimates that a marketing campaign will increase conversion by 4%, with a wide confidence interval. How should this be communicated?

Communicate results Medium
A. Replace the estimate with model accuracy
B. Report the estimate together with its uncertainty
C. Present the 4% estimate as guaranteed
D. Remove the interval to simplify the result

40 A company plans to deploy a new recommendation model gradually. Which strategy best reduces operational risk?

Operationalization Medium
A. Use a limited rollout with monitoring and rollback
B. Evaluate only the model's training accuracy
C. Disable performance logging during the deployment
D. Replace the existing model for every user immediately

41 A retailer has accurate demand forecasts but still experiences frequent stockouts and excessive holding costs. Which capability most strongly explains why learning data science remains valuable beyond producing predictions?

Why learn data science? Hard
A. Replacing all managerial judgment with automated rules
B. Converting forecasts into constrained inventory decisions
C. Increasing the number of variables in each forecast
D. Summarizing historical sales in additional dashboards

42 During model validation, a team discovers that its strongest predictor is recorded only after the outcome occurs. What is the most appropriate life-cycle response?

Life cycle of data analytics Hard
A. Continue building and reduce the predictor's coefficient
B. Operationalize the model with more frequent retraining
C. Return to discovery and preparation to redefine usable data
D. Proceed to communication with a leakage disclaimer

43 A hospital wants to predict readmission at the instant a patient is discharged. Which discovery finding should cause the greatest concern about a candidate variable?

Data discovery Hard
A. It is strongly correlated with the discharge diagnosis
B. It has different missing rates across hospital wards
C. It contains hundreds of clinically meaningful categories
D. It is finalized two days after patient discharge

44 A numerical feature has missing values, and the dataset will be evaluated with five-fold cross-validation. Which preparation procedure avoids validation leakage?

Data preparation Hard
A. Estimate each imputation value from that fold's validation partition
B. Estimate each imputation value from that fold's training partition
C. Remove missing rows before assigning cross-validation folds
D. Estimate one imputation value from the complete labeled dataset

45 A model will predict equipment failures from daily sensor readings, and performance must reflect predictions on future machines and future dates. Which validation design is most defensible?

Model planning Hard
A. Forward-chaining splits with machines kept across one side only
B. Leave-one-feature-out validation ordered by sensor importance
C. Bootstrap samples drawn independently from all machine-days
D. Random row-level folds stratified by the failure outcome

46 Only 0.2% of transactions are fraudulent, investigators can review 500 alerts daily, and false negatives are costly. Which primary evaluation design best matches deployment?

Model planning Hard
A. Specificity among transactions below the median score
B. Recall among the 500 highest-scored daily transactions
C. Mean squared error over all predicted probabilities
D. Overall accuracy at a probability threshold of 0.5

47 After tuning 200 hyperparameter configurations against the same validation set, a team reports the best validation score as its expected production performance. What is the best corrective action?

Model building Hard
A. Retrain the selected configuration using the validation labels only
B. Evaluate the selected configuration once on an untouched test set
C. Average the validation scores of all configurations that were tried
D. Choose the simplest configuration regardless of measured performance

48 Each regional branch shows a higher conversion rate under campaign B than campaign A, yet the company-wide conversion rate is lower under B. What should an analyst communicate first?

Communicate results Hard
A. The aggregate reversal may result from different regional mixes
B. The company-wide result invalidates every regional conversion rate
C. The reversal demonstrates that the collected observations are erroneous
D. The regional comparisons prove that campaign B caused improvement

49 A credit model's input distributions remain stable, but default rates increase and predicted probabilities become systematically too low. Which monitoring conclusion is best supported?

Operationalization Hard
A. The model has improved because observed positive outcomes increased
B. The relationship or outcome baseline has drifted despite stable inputs
C. Only data-schema drift can explain the probability underestimation
D. No drift exists because the feature distributions have remained stable

50 An analyst first quantifies last quarter's churn, then investigates its drivers, forecasts next quarter's churn, and finally allocates retention offers under a fixed budget. Which sequence correctly classifies the analyses?

Type of data analysis Hard
A. Predictive, diagnostic, descriptive, prescriptive
B. Diagnostic, descriptive, prescriptive, predictive
C. Descriptive, predictive, diagnostic, prescriptive
D. Descriptive, diagnostic, predictive, prescriptive

51 Department X has 20 employees with an average salary of , while department Y has 80 employees with an average salary of . What is the correct company-wide average salary?

Descriptive analysis Hard
A.
B.
C.
D.

52 Sales fell immediately after a website redesign. A diagnostic analysis finds that mobile traffic also shifted toward a lower-converting country during the same week. Which conclusion is most defensible?

Diagnostic analysis Hard
A. The redesign caused the decline because it occurred before the decline
B. The redesign's causal effect remains unidentified without controlling confounding
C. The geographic shift caused the decline because conversion was lower there
D. Both factors can be ignored if total traffic volume remained unchanged

53 Two binary classifiers have equal ROC-AUC, but model P is well calibrated and model Q is not. Decisions use predicted probabilities to calculate expected monetary loss. Which statement is correct?

Predictive analysis Hard
A. Model Q is preferable because poor calibration increases score separation
B. Model P is preferable because probability accuracy affects expected loss
C. Calibration is irrelevant whenever both models rank cases equally well
D. The models are equivalent because ROC-AUC determines all decision costs

54 A delivery optimizer minimizes expected travel time but repeatedly assigns routes that exceed driver-hour regulations. What is the most appropriate correction?

Prescriptive analysis Hard
A. Increase the prediction accuracy of every travel-time estimate
B. Add driver-hour limits as explicit optimization constraints
C. Replace the objective with the historical mean travel time
D. Report the infeasible routes with wider confidence intervals

55 A factory dashboard reports failure counts, a root-cause model links failures to overheating, a forecast estimates tomorrow's failures, and an optimizer schedules maintenance. Which component can recommend an action while directly considering resource constraints?

Types of data analytics Hard
A. The maintenance scheduling optimizer
B. The next-day failure forecast
C. The overheating root-cause model
D. The historical failure dashboard

56 After deployment, users consistently override a model because one recommended action is operationally impossible. Which response best reflects an iterative analytics life cycle?

Life cycle of data analytics Hard
A. Retrain the unchanged model more often using the original objective
B. Suppress override logs so adoption metrics reflect model recommendations
C. Revisit discovery and planning to encode the missing operational constraint
D. Improve visual styling while preserving the same recommendation logic

57 A categorical feature receives previously unseen values after deployment. Which training-time design most robustly prevents scoring failures without using future data?

Data preparation Hard
A. Map unseen values to the most predictive target category observed
B. Discard every training row containing an infrequent category
C. Fit the encoder again on each production batch before prediction
D. Reserve an unknown category and define deterministic encoding behavior

58 For a calibrated binary classifier, a false positive costs and a false negative costs , with zero cost for correct decisions. At what probability threshold should a case be classified as positive?

Model planning Hard
A.
B.
C.
D.

59 A forecast gives next month's revenue as million with a 95% prediction interval of million. Which statement communicates the result most appropriately?

Communicate results Hard
A. Revenue has a 95% probability of equaling exactly million
B. Ninety-five percent of historical monthly revenues lie in that interval
C. The true mean revenue must lie between and million
D. Revenue is forecast at million, with substantial outcome uncertainty

60 A new fraud model performs better offline, but labels arrive after 60 days and a faulty release could block legitimate customers. Which rollout strategy best controls operational risk?

Operationalization Hard
A. Disable monitoring because outcome labels cannot arrive immediately
B. Replace the current model globally once the offline metric improves
C. Use a limited canary rollout with guardrails and rollback capability
D. Run only a shadow deployment until every delayed label is available