Data+ Analysis Quiz: Data Mining & Analysis Skills

1. In data preparation, what does normalization accomplish?

Scales numeric data to a standard range, typically 0-1

Removes all categorical variables

Sorts data in ascending order

Eliminates all text fields

2. True or False: Descriptive statistics summarize data characteristics, while inferential statistics draw conclusions about populations.

True

False

3. What is the primary benefit of data aggregation?

Combining data from multiple sources to provide summary insights

Increasing the total number of records

Converting numeric data to categorical

Removing all duplicate entries

4. Which data source provides structured, organized information in tables or databases?

Unstructured data

Semi-structured data

Structured data

Raw data

5. In statistical analysis, what does p-value indicate?

The probability that an observed result occurred by chance

The number of data points in the sample

The average value of all observations

The range of data values

6. What is the purpose of feature engineering in data analysis?

Removing all features from the dataset

Creating new variables that better represent underlying patterns

Converting all data to text format

Deleting records with missing values

7. Which technique is used to identify patterns in categorical data?

Regression analysis

Cross-tabulation

Standard deviation calculation

Correlation coefficient

8. True or False: Missing data should always be removed from a dataset before analysis.

True

False

9. What does a histogram display in data visualization?

The relationship between three variables

The distribution of a single continuous variable across intervals

Categorical data in pie-slice format

Time-series data only

10. Which of the following is a characteristic of big data?

Small file sizes and low processing requirements

Large volume, high velocity, and variety of data types

Exclusively numeric information

Data that never changes over time

11. Which of the following best describes data mining?

Extracting patterns and insights from large datasets using statistical and computational methods

Manually sorting data into alphabetical order

Deleting irrelevant information from a database

Creating backup copies of raw data files

12. What is the purpose of exploratory data analysis (EDA)?

To delete all missing values without examination

To understand data structure, patterns, and relationships before formal modeling

To immediately apply machine learning algorithms

To convert all data to a single format

13. Which data quality dimension refers to the accuracy and completeness of data?

Consistency

Integrity

Validity

Timeliness

14. True or False: A correlation of -1.0 indicates a perfect positive relationship between variables.

True

False

15. What is correlation in data analysis?

The strength and direction of a linear relationship between two variables

The process of removing outliers

Organizing data in chronological order

The total number of data points in a dataset

16. Which statistical measure represents the spread of data around the mean?

Median

Mode

Standard deviation

Range

17. In data analysis, what is sampling used for?

Selecting a subset of data to represent the entire population

Removing duplicate records from a dataset

Converting categorical data to numeric format

Creating multiple copies of the same data

18. What does outlier detection help identify in a dataset?

The average value of all records

Unusual or anomalous data points that deviate significantly from the norm

The most frequently occurring value

The range between minimum and maximum values

19. Which visualization type is most appropriate for showing the relationship between two continuous variables?

Pie chart

Bar chart

Scatter plot

Heat map

20. What is the primary goal of data cleaning in the analysis process?

Removing all numeric values

Identifying and correcting errors, inconsistencies, and missing values

Converting all data to text format

Reducing the total number of records

Data+ Analysis Quiz: Can You Find the Insight?

1. In data preparation, what does normalization accomplish?

2.

What first name or nickname would you like us to use?

2. True or False: Descriptive statistics summarize data characteristics, while inferential statistics draw conclusions about populations.

3. What is the primary benefit of data aggregation?

4. Which data source provides structured, organized information in tables or databases?

5. In statistical analysis, what does p-value indicate?

6. What is the purpose of feature engineering in data analysis?

7. Which technique is used to identify patterns in categorical data?

8. True or False: Missing data should always be removed from a dataset before analysis.

9. What does a histogram display in data visualization?

10. Which of the following is a characteristic of big data?

11. Which of the following best describes data mining?

12. What is the purpose of exploratory data analysis (EDA)?

13. Which data quality dimension refers to the accuracy and completeness of data?

14. True or False: A correlation of -1.0 indicates a perfect positive relationship between variables.

15. What is correlation in data analysis?

16. Which statistical measure represents the spread of data around the mean?

17. In data analysis, what is sampling used for?

18. What does outlier detection help identify in a dataset?

19. Which visualization type is most appropriate for showing the relationship between two continuous variables?

20. What is the primary goal of data cleaning in the analysis process?