Experimental Design for Testing at Soundspace

This SOP outlines the steps for designing and conducting experiments at Soundspace to ensure effective data collection, hypothesis testing, and result analysis.

Introduction

Purpose

To establish a systematic process for conducting experiments at Soundspace, ensuring effective data collection, hypothesis testing, and result analysis.

Scope

This SOP is applicable to all departments interacting with customers, markets, or products at Soundspace.

Definitions

• Experiment: A scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact.

• Hypothesis: A proposed explanation for a phenomenon, formulated for testing and investigation.

• Control Group: A group in an experiment where the independent variable being tested is not applied, hence serves as a benchmark to measure how the other tested subjects do.

• Confounding Variables: Variables that the researcher failed to control, or eliminate, damaging the internal validity of an experiment.

Procedure

Step 1: Make an Observation

Identify a phenomenon or pattern in your data that is worth investigating. This could be a trend, an anomaly, or a gap in your current understanding.

Step 2: Empathize and Define

Understand the context of the problem and its effects on various stakeholders. Define the problem in concrete terms, focusing on the root cause of the phenomenon you're investigating.

Step 3: Ideate a Hypothesis

Formulate multiple hypotheses that could explain your observation. Ensure your hypotheses are clear, testable, and make specific assertions that you can prove or disprove. Group your hypotheses into categories and see where your tendencies are gravitating in types of explanations. Take these categories and make new hypotheses. Repeat until you are down to one to three hypotheses to test.

Step 4: Design an Experiment

Design an experiment to test your hypotheses. The experiment should involve a control group and an experimental group, with only one variable being manipulated. The more variables you add, the more control groups you need to account for. However, you can account for multiple manipulations of the same variable with a single control. Ensure you have enough trials to run statistics on your results.

Step 5: Check for Confounding Variables

Identify potential confounding variables that could distort your results. Plan to control these variables during your experiment to ensure the validity of your results.

Step 6: Prototype your Experiment

Test your experiment design to ensure it will provide the data necessary to test your hypotheses. Make necessary adjustments based on this validation process.

Step 7: Carry out the Experiments

Execute the experiment, taking care to minimize errors and maximize data collection. Be diligent in your data collection as one small error could invalidate your data.

Step 8: Analyze

Analyze the results of your experiment using appropriate statistical tests. Based on the results, accept or reject your hypotheses. Use the data to refine your hypotheses and design a new experiment if necessary.

Monitoring and Reporting

Regularly monitor the progress of the experiment and track key performance indicators (KPIs). Provide periodic reports to leadership regarding the experiment’s performance and any new opportunities.

Documentation and Compliance

Ensure all communication, proposals, and agreements are documented. Comply with organizational policies and legal regulations regarding experiments.