Evaluation
Evaluation
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
Evaluation
- 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