2.3 Extracting Information from Data

• Match the data type with its description and example:

  Numbers ↔️ Numerical values used in calculations ||| 123, 3.14

  Text ↔️ Strings of characters for names or addresses ||| "Hello World"

  Booleans ↔️ True/false values ||| True, False

  Arrays ↔️ Collections of items of the same type ||| [1, 2, 3, 4]
• Match the data type with its example:

  Numbers ↔️ 123, 3.14

  Text ↔️ "Hello World"

  Booleans ↔️ True, False

  Arrays ↔️ [1, 2, 3, 4]
• Descriptive statistics provide a high-level overview of the data
• Data cleaning ensures data is accurate and consistent
• Primary data is collected directly by the user or organization
• Active data collection involves users or researchers directly gathering data
• What are the main measures of central tendency in descriptive statistics?

  Mean, median, mode
• Inferential statistics provide a high-level overview of the data.

  False
• Match the data cleaning technique with its description:

  Handling Missing Values ↔️ Replacing empty fields

  Standardizing Data ↔️ Converting data to a common format

  Removing Duplicates ↔️ Eliminating identical records
• What is the purpose of scatter plots in data visualization?

  Identifying correlations
• Which chart type is best for visualizing trends over time?

  Line chart
• What does the term "data" refer to in computer science?

  Facts, values, or information
• What is an example of an active data collection method?

  Interviews or measurements
• The choice of data source and collection method depends on specific needs and constraints
• What is an example of a passive data collection method?

  Sensor data
• Match the statistic type with its description:

  Descriptive Statistics ↔️ Summarize main features of data ||| Mean, median, standard deviation

  Inferential Statistics ↔️ Draw conclusions about a population ||| Hypothesis testing
• Order the following data cleaning techniques:

  1️⃣ Handling Missing Values

  2️⃣ Standardizing Data

  3️⃣ Removing Duplicates
• What are the two main types of data sources?

  Primary and secondary
• What are the two main methods for data collection?

  Active and passive
• Order the steps in the descriptive statistics process:

  1️⃣ Summarize data

  2️⃣ Calculate central tendency

  3️⃣ Measure spread
• Inferential statistics allow you to draw conclusions about a population
• What is the primary goal of data cleaning?

  Ensure accuracy and consistency
• What is the primary use of charts in data visualization?

  Comparing values and trends
• Order the steps in identifying key insights from data:

  1️⃣ Aggregate data

  2️⃣ Filter data

  3️⃣ Compare data

  4️⃣ Segment data
• Data collected directly by the user or organization is called primary
• Passive data collection requires direct user involvement.

  False
• Data can come from two main sources
• Primary data sources offer more control compared to secondary data sources.


  True
• Inferential statistics are used to summarize the main features of a dataset.

  False
• Primary data sources provide more control and customization
• Secondary data is collected by others and made available.


  True
• Passive data collection occurs without direct user involvement.


  True
• Data visualization helps identify trends, outliers, and relationships
• Histograms display the frequency distribution of data.


  True
• The choice of visualization method depends on the insights you want to communicate