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