3.1 Data Handling

• Qualitative data describes numerical values that can be measured or counted.

  False
• What is an example of qualitative data?

  Hair color
• Match the data type with its characteristic:

  Qualitative Data ↔️ Non-numerical information

  Quantitative Data ↔️ Numerical information
• To create a frequency distribution, you must first determine the class intervals
• The class interval 150-154 cm has a frequency of 5 in the given example.


  True
• What are some methods for collecting quantitative data?

  Structured surveys, experiments
• Organizing data using tabulation involves arranging it in rows and columns.

  True
• Quantitative data is numerical information that can be measured or counted.


  True
• Qualitative methods focus on understanding characteristics and experiences, while quantitative methods measure numerical values and statistics.


  True
• What does tabulation involve in data organization?

  Arranging data in rows and columns
• Steps to create a frequency distribution:

  1️⃣ Determine class intervals: Decide on a reasonable range and class width

  2️⃣ Tally frequencies: Count how many data points fall into each class

  3️⃣ Create a table: List the class intervals and their corresponding frequencies
• Frequency distributions are used to organize and summarize data by grouping it into classes or intervals
• Bar charts are used to display categorical data, such as demographic groups.


  True
• Pie charts are used to show the proportional sizes of different categories within a whole.


  True
• Match the type of chart with its purpose:

  Bar Chart ↔️ Compare magnitudes

  Pie Chart ↔️ Show proportions
• The mode is the value that appears most frequently in the dataset
• Quantitative data measures numerical values
• What are the two main types of data?

  Qualitative and quantitative
• Qualitative data analysis is numerical and statistical.

  False
• Organizing data into rows and columns is called tabulation
• What is the purpose of a frequency distribution?

  Organize and summarize data
• Pie charts display the proportional sizes of categories in a whole
• What are the three measures of central tendency?

  Mean, median, mode
• The mode is the value that appears most frequently in a dataset
• The standard deviation measures how much data points deviate from the mean
• What type of data do pictograms effectively visualize?

  Categorical data
• The x-axis in a line graph typically represents the time period.


  True
• Match the graph type with its characteristic:

  Pictograms ↔️ Use symbols or icons

  Line Graphs ↔️ Show trends over time
• Line graphs are effective for visualizing quantitative data.
• Match the type of graph with its purpose:

  Pictograms ↔️ Compare magnitudes

  Line Graphs ↔️ Show trends over time
• Pictograms are useful for visualizing and comparing categorical data.
• Match the strength of the graph with its type:

  Pictograms ↔️ Intuitive, easy to understand

  Line Graphs ↔️ Effective for identifying patterns
• Line graphs may be less intuitive for some audiences.


  True
• Steps to interpret data and draw meaningful conclusions:

  1️⃣ Review the data

  2️⃣ Identify patterns

  3️⃣ Analyze findings

  4️⃣ Draw conclusions
• Line graphs are useful for identifying trends over time.
• Interpreting data allows you to make informed inferences about the underlying data.


  True
• What are the two main types of data?

  Qualitative and quantitative
• Quantitative data is numerical information that can be measured or counted
• What is an example of quantitative data?

  Height
• Steps to create a frequency distribution

  1️⃣ Determine class intervals

  2️⃣ Tally frequencies

  3️⃣ Create a table