Master GCSE Biology

MS1:

- A control variable is a factor that is kept the same in all groups except the group being tested. (1)

- It ensures that only the independent variable is tested, eliminating other variables that could affect the results. (1)

MS2:

- Using aseptic technique helps to prevent contamination of the experiment, ensuring reliable results. (1)

- It eliminates microorganisms that could affect the growth or behavior of the microorganisms being studied. (1)

MS3:

- Benedict's reagent (1)

MS4:

- Independent variable: Light intensity (1)

- Dependent variable: Rate of photosynthesis (1)

- Control variables: Temperature, CO2 concentration, leaf size (1)

MS5:

- An anomaly is an unusual or unexpected result that does not fit the general pattern of data. (1)

- It can affect the reliability of data by introducing uncertainty or misleading patterns. (1)

MS6:

- Calibrate the microscope using a graticule or scale. (1)

- Measure the diameter of the cell in micrometers (µm) using the calibrated microscope. (1)

MS7:

- Stage 1: Prepare plant tissue (e.g., potato) and soak it in distilled water to remove cell contents. (1)

- Stage 2: Cut strips of tissue and place them in solutions of different concentrations. (1)

- Stage 3: Measure the change in mass or length of the tissue strips over time. (1)

- Stage 4: Plot a graph to show the relationship between the concentration of the solution and the change in mass/length of the tissue. (1)

MS8:

- Biuret reagent (1)

MS9:

- The control group provides a baseline against which the results of the experimental group can be compared. (1)

- It ensures that any observed differences between the experimental and control groups are due to the chemical fertilizer, rather than other factors such as temperature or light. (1)

MS10:

- Accuracy refers to how close a measurement is to the true value. (1)

- Precision refers to the consistency of measurements with each other. (1)

- Both accuracy and precision are important for validity, as inaccurate or imprecise data can lead to misleading conclusions. (1)