Experimental Investigation Skills Flashcards
Identify and describe the difference between quantitative and qualitative data
Quantitative Data: Numerical data that can be measured and expressed in numbers (e.g., height, weight).
Qualitative Data: Descriptive data that cannot be measured numerically (e.g., colors, opinions).
Identify and describe the differences between discrete and continuous data
Discrete Data: Countable data with distinct values (e.g., number of students).
Continuous Data: Measurable data that can take any value within a range (e.g., temperature, height).
Data Tables
Describe relationships between graphed variables, including interpreting changes in gradient
Independent Variable: The variable changed in an experiment.
Dependent Variable: The variable measured or observed.
Create data tables that clearly show a title, column headings with units in brackets, raw data
Title: Clear and descriptive.
Column Headings: Include units in brackets (e.g., Height (cm), Weight (kg)).
Raw Data: Organized values in rows
Describe the differences between a column (bar) graph and line graph and understand when it is appropriate to use each type of graph
Bar Graph: Used for categorical data to compare different groups (e.g., population by city).
Line Graph: Used for continuous data to show trends over time (e.g., temperature changes).
what axis do the variables go on
The independent variable belongs on the x-axis (horizontal line) of the graph and the dependent variable belongs on the y-axis (vertical line).
Suggest factors that should be controlled (held steady) in an experiment
Control factors to ensure valid data: only one independent variable should be tested at a time: Temperature, humidity, light Conditions, time, concentration, volume, Sample Size,
Environmental Conditions.
Importance of Controlled Factors
Validity: Ensures that the experiment tests only the intended independent variable.
Reproducibility: Allows for the experiment to be repeated with the same conditions for reliable results.
Accuracy: Reduces the chance of confounding variables affecting the outcome.
Provide a relevant hypothesis, aim and conclusion for a given experiment
Hypothesis: A testable prediction.
Aim: The purpose of the experiment.
Conclusion: Mention if the hypothesis was correct, reference aim, summarise results and what they mean.
Understand and explain the difference between the science terms accuracy and precision
Accuracy: How close a measurement is to the true value.
Precision: How consistent repeated measurements are.
Understand the term random error, its effect on the precision of measurements, and the reason why scientists repeat trials and calculate averages
Variability in measurements due to unpredictable factors; leads to reduced precision. Scientists repeat trials to improve reliability.
Systematic error
Consistent error affecting accuracy; occurs from flawed instruments or methods.
SI Units
Distance: meters (m)
Time: seconds (s)
Mass: kilograms (kg)
Energy: joules (J)
Force: newtons (N)
