Developing a Hypothesis for an Investigation

  • Understand that a hypothesis is an educated guess about the relationship between two or more variables
  • Know that a good hypothesis is testable and measurable
  • Be able to frame the hypothesis as an if-then statement
  • Remember to develop a hypothesis related to your own investigations

Selection of Appropriate Equipment, Techniques, and Standard Procedures

  • Understand the importance of selecting appropriate equipment and techniques
  • Know the standard procedures for the operation of equipment
  • Recognize the need for controls in an experiment to ensure validity

Health and Safety Associated with The Investigation

  • Know the importance of a comprehensive risk assessment
  • Remember the need for the use of appropriate personal protective equipment (PPE)
  • Understand the standard safety protocols when conducting an investigation

Variables in The Investigation

  • Know the difference between dependent, independent, and controlled variables
  • Understand the importance of controlling variables to ensure a fair test

Method for Data Collection and Analysis

  • Recognize the need for accurate and precise data collection
  • Understand different methods of data analysis, such as statistical analysis or graphical representation

Collection of Quantitative/Qualitative Data

  • Understand the difference between quantitative data (numerical data) and qualitative data (descriptive data)
  • Know how to collect both types of data appropriately

Processing Data

  • Know the importance of organizing and coding collected data for processing
  • Understand the use of statistical tools for analyzing and interpreting data

Interpretation/Analysis of Data

  • Know how to interpret the data visually (through graphs and charts)
  • Understand the importance of analyzing data to form conclusions


  • Understand the importance of evaluating the method used and the data obtained
  • Know how to repeat measurements and take average values to improve accuracy
  • Be able to recognize anomalies and outliers in data collection and processing, and to draw relevant conclusions
  • Remember to discuss possible improvements or future work based on the results obtained