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Data Analysis Foundations with Python

Quiz for Part IV: Exploratory Data Analysis (EDA)

Questions of Quiz for Part IV: Exploratory Data Analysis (EDA)

1. What is Exploratory Data Analysis (EDA)? 

a) A statistical technique to make predictions
b) An initial process to summarize the main characteristics of the data
c) The process of deploying machine learning models into production
d) The act of gathering data

2. In Univariate Analysis, how many variables are typically analyzed at a time?

a) Two
b) Three
c) One
d) Many

3. Which of the following is commonly used for Bivariate Analysis?

a) Scatter Plot
b) Heatmap
c) Pair Plot
d) Line Chart

4. What does Multivariate Analysis involve?

a) Analyzing a single variable
b) Analyzing two variables
c) Analyzing more than two variables
d) None of the above

5. What is Data Cleaning?

a) Modifying data for better visualization
b) Removing or imputing missing values, handling outliers, and so on
c) Extracting features from existing data
d) Transforming data into another format

6. What is Feature Engineering?

a) The process of selecting only the most important variables
b) The act of creating new features from the existing ones to improve a model’s performance
c) The process of deleting redundant features
d) Both a and c

7. Which of the following is a Data Transformation technique?

a) Normalization
b) Label Encoding
c) One-Hot Encoding
d) All of the above

8. What does a Heatmap represent in Multivariate Analysis?

a) Correlations between two variables
b) Correlations among multiple variables
c) Distributions of a single variable
d) None of the above

9. Why is Descriptive Statistics important in EDA?

a) It helps in understanding the data distribution
b) It assists in identifying outliers
c) It aids in making inferences about the data
d) All of the above

10. Which of the following can be considered a preprocessing step?

a) Data cleaning
b) Feature engineering
c) Data transformation
d) All of the above

Questions of Quiz for Part IV: Exploratory Data Analysis (EDA)

1. What is Exploratory Data Analysis (EDA)? 

a) A statistical technique to make predictions
b) An initial process to summarize the main characteristics of the data
c) The process of deploying machine learning models into production
d) The act of gathering data

2. In Univariate Analysis, how many variables are typically analyzed at a time?

a) Two
b) Three
c) One
d) Many

3. Which of the following is commonly used for Bivariate Analysis?

a) Scatter Plot
b) Heatmap
c) Pair Plot
d) Line Chart

4. What does Multivariate Analysis involve?

a) Analyzing a single variable
b) Analyzing two variables
c) Analyzing more than two variables
d) None of the above

5. What is Data Cleaning?

a) Modifying data for better visualization
b) Removing or imputing missing values, handling outliers, and so on
c) Extracting features from existing data
d) Transforming data into another format

6. What is Feature Engineering?

a) The process of selecting only the most important variables
b) The act of creating new features from the existing ones to improve a model’s performance
c) The process of deleting redundant features
d) Both a and c

7. Which of the following is a Data Transformation technique?

a) Normalization
b) Label Encoding
c) One-Hot Encoding
d) All of the above

8. What does a Heatmap represent in Multivariate Analysis?

a) Correlations between two variables
b) Correlations among multiple variables
c) Distributions of a single variable
d) None of the above

9. Why is Descriptive Statistics important in EDA?

a) It helps in understanding the data distribution
b) It assists in identifying outliers
c) It aids in making inferences about the data
d) All of the above

10. Which of the following can be considered a preprocessing step?

a) Data cleaning
b) Feature engineering
c) Data transformation
d) All of the above

Questions of Quiz for Part IV: Exploratory Data Analysis (EDA)

1. What is Exploratory Data Analysis (EDA)? 

a) A statistical technique to make predictions
b) An initial process to summarize the main characteristics of the data
c) The process of deploying machine learning models into production
d) The act of gathering data

2. In Univariate Analysis, how many variables are typically analyzed at a time?

a) Two
b) Three
c) One
d) Many

3. Which of the following is commonly used for Bivariate Analysis?

a) Scatter Plot
b) Heatmap
c) Pair Plot
d) Line Chart

4. What does Multivariate Analysis involve?

a) Analyzing a single variable
b) Analyzing two variables
c) Analyzing more than two variables
d) None of the above

5. What is Data Cleaning?

a) Modifying data for better visualization
b) Removing or imputing missing values, handling outliers, and so on
c) Extracting features from existing data
d) Transforming data into another format

6. What is Feature Engineering?

a) The process of selecting only the most important variables
b) The act of creating new features from the existing ones to improve a model’s performance
c) The process of deleting redundant features
d) Both a and c

7. Which of the following is a Data Transformation technique?

a) Normalization
b) Label Encoding
c) One-Hot Encoding
d) All of the above

8. What does a Heatmap represent in Multivariate Analysis?

a) Correlations between two variables
b) Correlations among multiple variables
c) Distributions of a single variable
d) None of the above

9. Why is Descriptive Statistics important in EDA?

a) It helps in understanding the data distribution
b) It assists in identifying outliers
c) It aids in making inferences about the data
d) All of the above

10. Which of the following can be considered a preprocessing step?

a) Data cleaning
b) Feature engineering
c) Data transformation
d) All of the above

Questions of Quiz for Part IV: Exploratory Data Analysis (EDA)

1. What is Exploratory Data Analysis (EDA)? 

a) A statistical technique to make predictions
b) An initial process to summarize the main characteristics of the data
c) The process of deploying machine learning models into production
d) The act of gathering data

2. In Univariate Analysis, how many variables are typically analyzed at a time?

a) Two
b) Three
c) One
d) Many

3. Which of the following is commonly used for Bivariate Analysis?

a) Scatter Plot
b) Heatmap
c) Pair Plot
d) Line Chart

4. What does Multivariate Analysis involve?

a) Analyzing a single variable
b) Analyzing two variables
c) Analyzing more than two variables
d) None of the above

5. What is Data Cleaning?

a) Modifying data for better visualization
b) Removing or imputing missing values, handling outliers, and so on
c) Extracting features from existing data
d) Transforming data into another format

6. What is Feature Engineering?

a) The process of selecting only the most important variables
b) The act of creating new features from the existing ones to improve a model’s performance
c) The process of deleting redundant features
d) Both a and c

7. Which of the following is a Data Transformation technique?

a) Normalization
b) Label Encoding
c) One-Hot Encoding
d) All of the above

8. What does a Heatmap represent in Multivariate Analysis?

a) Correlations between two variables
b) Correlations among multiple variables
c) Distributions of a single variable
d) None of the above

9. Why is Descriptive Statistics important in EDA?

a) It helps in understanding the data distribution
b) It assists in identifying outliers
c) It aids in making inferences about the data
d) All of the above

10. Which of the following can be considered a preprocessing step?

a) Data cleaning
b) Feature engineering
c) Data transformation
d) All of the above