1.2 Data Collection and Analysis

• Qualitative data measures amounts or numbers.

  False
• Basic statistical measures include averages, standard deviations, and correlations
• There are three main methods for collecting data: observation, experimentation, and surveys
• Observation involves watching and recording information about the subject of study
• Quantitative data analysis involves using statistical methods to calculate averages, standard deviations, and correlations
• The choice of data analysis method depends on the type of data and the research question.

  True
• There are three main methods for collecting data: observation, experimentation, and surveys
• What type of data describes characteristics or qualities, such as the taste of fruit?

  Qualitative
• Quantitative data analysis involves using statistical methods to analyze numerical data.


  True
• What is a table primarily used for in data presentation?

  Displaying numerical values
• What is the median in a data set?

  The middle value
• Standard deviation measures how much individual data points vary from the mean
• The mode is the value that appears most frequently in a data set.


  True
• The mean is always better than the median for skewed data.

  False
• Researchers can make informed decisions by drawing well-reasoned conclusions from data.


  True
• Data collection is the process of gathering information through observation, experimentation, or surveys
• What are examples of data presentation techniques?

  Tables and graphs
• Match the type of data with its description:

  Qualitative ↔️ Describes characteristics or qualities

  Quantitative ↔️ Measures amounts or numbers
• What is qualitative data used to describe?

  Characteristics or qualities
• Match the type of data with its example:

  Quantitative ↔️ Height of plants

  Qualitative ↔️ Color of flowers
• What does qualitative data analysis identify in descriptive data?

  Patterns and themes
• Match the type of data with its description:

  Qualitative ↔️ Describes characteristics

  Quantitative ↔️ Measures amounts or numbers
• What type of data is numerical and measurable, such as the height of plants?

  Quantitative
• Data analysis is the process of examining and interpreting data to draw conclusions
• What are two common techniques for presenting data after analysis?

  Tables and graphs
• The mean is the average value, calculated by adding all data points and dividing by the total number of data points
• The range is the difference between the highest and lowest values in a data set.


  True
• The median represents the central value
• Standard deviation measures how much the data points vary from the mean
• Steps involved in interpreting data and drawing conclusions

  1️⃣ Identify patterns

  2️⃣ Recognize relationships

  3️⃣ Evaluate significance

  4️⃣ Answer the question

  5️⃣ Test the hypothesis
• Match the type of data with its description:

  Qualitative Data ↔️ Describes characteristics or qualities

  Quantitative Data ↔️ Measures amounts or numbers
• Observation involves watching and recording information about the subject of study
• What is an example of quantitative data?

  Height of plants
• What is the process of examining and interpreting data called?

  Data analysis
• Quantitative data analysis involves analyzing numerical data using statistical methods
• Order the steps involved in data analysis and presentation:

  1️⃣ Collect data

  2️⃣ Analyze data

  3️⃣ Choose presentation technique

  4️⃣ Interpret findings
• Standard deviation measures how much data points vary from the mean
• After evaluating significance, the next step in interpreting data is to answer the original research question
• Effective data management ensures data accuracy and accessibility
• Steps in the data analysis process

  1️⃣ Examine the data

  2️⃣ Interpret the data

  3️⃣ Draw conclusions

  4️⃣ Make informed decisions