# Data Analysis MCQs

## Multiple Choice Questions on Data Analysis

**1. Which of the following is not a form of data analysis?**

- Descriptive analysis
- Inferential analysis
- Predictive analysis
- Observational analysis

**Answer: D)** Observational analysis

**2. What comes first in the process of data analysis?**

- Collecting data
- Cleaning data
- Analyzing data
- Visualizing data

**Answer: A)** Collecting data

**3. Which of the following is not a method for displaying data?**

- Bar chart
- Scatter plot
- Box plot
- Random forest

**Answer: D)** Random forest

**4. What is the purpose of descriptive analysis?**

- To make predictions about future data
- To describe and summarise data
- To evaluate data-related hypotheses
- To identify outliers in data

**Answer: B)** To describe and summarise data

**5. What does inferential analysis aim to accomplish?**

- To summarize and describe data
- To make predictions about future data
- To test hypotheses about data
- To identify outliers in data

**Answer: C)** To test hypotheses about data

**6. What distinguishes correlation from causation?**

- In contrast to causation, which is a direct connection between two variables, correlation is a statistical relationship between two variables.
- In contrast to causation, which is a statistical link between two variables, correlation is a direct relationship between two variables.
- While causation does not entail correlation, correlation indicates causation.
- The terms "correlation" and "cause" are interchangeable.

**Answer: A)** In contrast to causation, which is a direct connection between two variables, correlation is a statistical relationship between two variables.

**7. Which of the following is not a sampling method?**

- Random sampling
- Stratified sampling
- Convenience sampling
- Correlation sampling

**Answer: D)** Correlation sampling

**8. What is the purpose of predictive analysis?**

- To summarize and describe data
- To forecast data for the future
- To test hypotheses about data
- To identify outliers in data

**Answer: B)** To forecast data for the future

**9. Which of the following is an algorithm for supervised learning?**

- K-means clustering
- Principal component analysis
- Decision tree
- Apriori algorithm

**Answer: C)** Decision tree

**10. Which of the following describes a dispersion measure?**

- Mode
- Median
- Variance
- Mean

**Answer: C)** Variance

**11. What is the purpose of exploratory data analysis?**

- To make predictions about future data
- To summarize and describe data
- To evaluate data-related hypotheses
- To spot trends and connections in data

**Answer: D)** To spot trends and connections in data

**12. What kind of analysis does not fall within the category of regression?**

- Straight-line regression
- A number of linear regressions
- Logistic regression
- Hierarchical regression

**Answer: D)** Hierarchical regression

**13. What distinguishes a parameter from a statistic?**

- A statistic is a characteristic of a sample, whereas a parameter is a feature of a population.
- A statistic is a characteristic of the population, whereas a parameter is a characteristic of a sample.
- A statistic is a measure of dispersion, whereas a parameter measures central tendency.
- A parameter is the same as a statistic.

**Answer: A)** A statistic is a characteristic of a sample, whereas a parameter is a feature of a population.

**14. What accomplishes cluster analysis?**

- To forecast data for the future
- To summarize and describe data
- To group similar observations together
- To identify relationships between variables

**Answer: C)** To group similar observations together

**15. Which of the following is the kind of algorithm for unsupervised learning?**

- Linear regression
- Naive Bayes
- K-means clustering
- Support vector machines

**Answer: C)** K-means clustering

**16. What is the purpose of time series analysis?**

- To make predictions about future data
- To summarize and describe data
- To evaluate data-related hypotheses
- Finding connections between different factors

**Answer: A)** To make predictions about future data

**17. Which of the following is not a kind of data transformation?**

- Standardization
- Normalization
- Aggregation
- Correlation

**Answer: D)** Correlation

**18. What is the purpose of data mining?**

- To make predictions about future data
- To summarize and describe data
- To identify patterns and relationships in data
- To test hypotheses about data

**Answer: C)** To identify patterns and relationships in data

**19. Which of the following is a measure of association between two categorical variables?**

- Pearson's coefficient of correlation
- Coefficient of correlation with Spearman's rank
- Chi-squared test
- T-test

**Answer: C)** Chi-squared test

**20. What is the purpose of factor analysis?**

- To compile related observations
- To spot trends and connections in data
- Minimising the amount of data in a dataset that has variables
- To make predictions about future data

**Answer: C)** Minimising the amount of data in a dataset that has variables

**21. Which one of the following describes a data bias?**

- Sampling bias
- Descriptive bias
- Predictive bias
- Inferential bias

**Answer: A)** Sampling bias

**22. What distinguishes a population from a sample?**

- A population is a subset of a sample, whereas a sample is a subset of a population.
- A population is a collection of all possible observations, whereas a sample is a subset of the population.
- A population is a collection of all possible samples, whereas a sample is a collection of all possible observations.
- A population and a sample are the same thing.

**Answer: B)** A population is a collection of all possible observations, whereas a sample is a subset of the population.

**23. Which of the following is data imputation method?**

- Mean imputation
- Median imputation
- Mode imputation
- All of the above

**Answer: D)** All of the above

**24. What does cross-validation provide as a means of?**

- To gauge model effectiveness using fresh data
- To identify outliers in data
- To group similar observations together
- To visualize relationships between variables

**Answer: A)** To gauge model effectiveness using fresh data

**25. What kind of data distribution is not one of the following?**

- Skewed distribution
- Bimodal distribution
- Multimodal distribution
- Hierarchical distribution

**Answer: D)** Hierarchical distribution

**26. What is the purpose of data cleaning?**

- To make predictions about future data
- To summarize and describe data
- To test hypotheses about data
- To correct errors and inconsistencies in data

**Answer: D)** To correct errors and inconsistencies in data

**27. Which of the following is a type of sampling error?**

- Measurement error
- Non-response error
- Sampling bias
- Sampling variance

**Answer: D)** Sampling variance

**28. What is the purpose of text mining?**

- To compile related observations
- To find correlations and patterns in text data
- To reduce the number of variables in a text dataset
- To make predictions about future text data

**Answer: B)** To find correlations and patterns in text data

**29. Which of the following is a measure of central tendency?**

- Variance
- Standard deviation
- Mean
- Skewness

**Answer: C)** Mean

**30. Which of the following is a kind of data visualisation?**

- Scatter plot
- Box plot
- Bar chart
- All of the above

**Answer: D)** All of the above

**31. What is the purpose of hypothesis testing?**

- To make predictions about future data
- To summarize and describe data
- To test whether a sample statistic differs significantly from a population parameter
- To spot trends and connections in data

**Answer: C)** To test whether a sample statistic differs significantly from a population parameter

**32. Which of the following is a type of time series analysis?**

- Autoregressive integrated moving average (ARIMA)
- Principal component analysis (PCA)
- Decision tree analysis
- K-nearest neighbors (KNN)

**Answer: A)** Autoregressive integrated moving average (ARIMA)

**33. What is the purpose of data normalization?**

- Minimising the amount of data in a dataset that has variables
- Converting data to a common scale
- Combining comparable observations to find patterns and
- Connections in data

**Answer: B)** Converting data to a common scale

**34. Which of the following options does not fall within the category of data mining?**

- Association rule mining
- Clustering
- Neural networks
- Linear regression

**Answer: D)** Linear regression

**35. What is the purpose of data wrangling?**

- To make predictions about future data
- To summarize and describe data
- Data transformation and cleaning
- To spot trends and connections in data

**Answer: C)** Data transformation and cleaning

**36. Which of the following is a type of data feature selection?**

- Recursive feature elimination
- Principal component analysis
- Lasso regression
- All of the above

**Answer: D)** All of the above

**37. What is the purpose of correlation analysis?**

- To spot trends and connections in data
- To group similar observations together
- To test hypotheses about data
- To make predictions about future data

**Answer: A)** To spot trends and connections in data

**38. Which of the following is a kind of data interpolation?**

- Linear interpolation
- Quadratic interpolation
- Cubic interpolation
- All of the above

**Answer: D)** All of the above

**39. What does data sampling accomplish?**

- Minimising the amount of data in a dataset that has variables
- To transform and clean data
- To select a subset of observations from a population
- To spot trends and connections in data

**Answer: C)** To select a subset of observations from a population

**40. Which of the following is a type of data clustering?**

- K-means clustering
- Decision tree analysis
- Neural networks
- Linear regression

**Answer: A)** K-means clustering

**41. What does data preparation serve?**

- To make predictions about future data
- To summarize and describe data
- Data transformation and cleaning
- To spot trends and connections in data

**Answer: C)** Data transformation and cleaning

**42. Which of the following is a type of data outlier detection?**

- Z-score method
- Interquartile range (IQR) method
- Cook's distance method
- All of the above

**Answer: D)** All of the above

**43. What function does data visualisation serve?**

- To summarize and describe data
- To test hypotheses about data
- To identify patterns and relationships in data
- To transform and clean data

**Answer: C)** To identify patterns and relationships in data

**44. What kind of reasoning is based on statistics?**

- Regression analysis
- Hypothesis testing
- Cluster analysis
- Time series analysis

**Answer: B)** Hypothesis testing

**45. What is the purpose of data imputation?**

- Minimising the amount of data in a dataset that has variables
- Data transformation and cleaning
- Calculating the missing values in a dataset
- To spot trends and connections in data

**Answer: C)** Calculating the missing values in a dataset

**46. Which of the following is a type of dimensionality reduction technique?**

- Principal component analysis
- Linear regression
- Decision tree analysis
- K-nearest neighbours

**Answer: A)** Principal component analysis

**47. What is the purpose of data feature extraction?**

- To forecast data for the future
- To spot trends and connections in data
- Data transformation and cleaning
- Minimising the amount of data in a dataset that has variables

**Answer: D)** Minimising the amount of data in a dataset that has variables

**48. What is the purpose of data rescaling?**

- To group similar observations together
- To transform data to a standard scale
- To select a subset of observations from a population
- To spot trends and connections in data

**Answer: B)** To transform data to a standard scale

**49. Which of the following is a type of data transformation?**

- Log transformation
- Exponential transformation
- Square root transformation
- All of the above

**Answer: D)** All of the above

**50. What is the purpose of data standardization?**

- Minimising the amount of data in a dataset that has variables
- To transform and clean data
- To transform data to a standard scale
- To spot trends and connections in data

**Answer: C)** To transform data to a standard scale

**51. Which of the following is a type of data validation?**

- Hypothesis testing
- Cross-validation
- Principal component analysis
- K-means clustering

**Answer: B)** Cross-validation

**52. What is the purpose of data augmentation?**

- To make predictions about future data
- To summarize and describe data
- In order to expand a dataset
- To spot trends and connections in data

**Answer: C)** In order to expand a dataset

**53. What kind of data fusion is which of the following?**

- Feature extraction
- Feature selection
- Data integration
- Data cleaning

**Answer: C)** Data integration

**54. What is the purpose of data privacy?**

- To guarantee the data is correct
- To safeguard private data in a dataset
- To identify patterns and relationships in data
- To transform and clean data

**Answer: B)** To safeguard private data in a dataset

**55. Which of the following is a type of data smoothing?**

- Interpolation
- Extrapolation
- Moving average
- Outlier detection

**Answer: C)** Moving average

**56. What is the purpose of data enrichment?**

- Minimising the amount of data in a dataset that has variables
- To transform and clean data
- To enhance a dataset with additional information
- To spot trends and connections in data

**Answer: C)** To enhance a dataset with additional information

**57. Which of the following is a type of data governance?**

- Data privacy
- Data analysis
- Data modelling
- Data quality management

**Answer: D)** Data quality management

**58. What is the purpose of data profiling?**

- To describe and summarise data
- To spot trends and connections in data
- To transform and clean data
- To test hypotheses about data

**Answer: A)** To summarize and describe data

**59. Which of the following is a type of data reduction?**

- Principal component analysis
- Linear regression
- Decision tree analysis
- K-nearest neighbours

**Answer: A)** Principal component analysis

**60. What is the purpose of data aggregation?**

- Data transformation and cleaning
- To spot trends and connections in data
- To group similar observations together
- To make predictions about future data

**Answer: C) To group similar observations together**

**61. Which of the following is a type of data linkage?**

- Data validation
- Data integration
- Data cleaning
- Data transformation

**Answer: B)** Data integration

**62. What is the purpose of data partitioning?**

- Data transformation and cleaning
- To spot trends and connections in data
- The act of dividing a dataset into training and test sets
- To reduce the number of variables in a dataset

**Answer: C)** The act of dividing a dataset into training and test sets

**63. What is the purpose of data normalization?**

- Data transformation and cleaning
- Minimising the amount of data in a dataset that has variables
- Converting data to a common scale
- To spot trends and connections in data

Answer: C) Converting data to a common scale

**64. What is the purpose of data classification?**

- To spot trends and connections in data
- To make predictions about future data
- To transform and clean data
- Minimising the amount of data in a dataset that has variables

Answer: B) To make predictions about future data