Understanding the Scientific Method

• Scientific method is a sequence of steps to test hypotheses and differentiate truth from myths, also used to validate information.
• The scientific method is a process for experimentation used to explore observations and answer questions.
• The scientific method is a systematic way of generating information based on keen observation, persistent experimentation, and intuitive inferences.
• Scientific method takes a systematic and orderly approach to gathering information, data, and solving problems.
• The scientific method involves observations, identifying the problem, gathering related information, formulating hypotheses, designing/performing experiments, and drawing conclusions.

Steps of the Scientific Method

• Observation identifies a problem, and poses a question. It includes: How, What, When, Who, Which, Why, or Where?
• Research involves investigating and collecting information related to a problem.
• Hypothesis is an educated guess about how things work and the factors that affect a problem.
• A hypothesis attempts to answer the question with a testable explanation and must allow you to then make a prediction
• The Null hypothesis (Ho) is written in negative terms.
• Alternative hypotheses (H1) are written in affirmative terms.
• Test involves designing an experiment and gathering the materials needed.
• Treatment should be identified as it is the variable manipulated to compare your baseline.
• Details that occur when one variable is manipulated are observed and recorded in testing.
• Repeating experiments ensures that the first results were not accidental.
• Analysis involves organizing and presenting data in tables or graphs.
• Visualizing results helps to understand what the data and findings imply.
• During analysis, measurements are collected, analyzed, and tested to see if they support your hypothesis.
• Conclusion involves drawing a conclusion based on your findings and interpretations of the data, if data analysis agrees with your hypothesis.
• A recommendation can be made for further study if the data supports the hypothesis.
• The difficulties encountered during the experiment should be shared, and how to address the differently in the future explained.
• An alternative solution to the problem can be recommended if the data refutes the hypothesis.
• When results do not match the hypothesis, avoid changing the hypothesis, try to determine why hypothesis and experimental results do not match.
• Consider future recommendations to future researchers to improve an investigation if results don't match hypothesis

Communicate Result

• Communicate results through a final report and/or a display board to complete the science activity.
• Scientist do this through publishing final reports in scientific journals, presenting on posters, or at scientific meetings.

Qualities of a good hypothesis

• A good hypothesis should be observable, meaning that it should contain an outcome that can be observed and recorded.
• A good hypothesis should also be measurable under conditions that are easily measured.
• A good hypothesis should also be testable by being subjected to experimentation.
• Hypotheses serve as calculated guesses to answer a scientific problem, so there is no such thing as a right or wrong hypothesis.

Data Collection

• A specific plan conducts the experiment/research and determines how to collect the data.
• When planning an experiment/research, consider questions such as:
  • How will I test my hypothesis?
  • What data do I need to collect?
  • How will I collect the data?
  • What materials do I need?
  • Is there a control needed to compare the data?
  • How will I plan my time?
  • How many samples and tests do I need?

Data Organization and Summarization

• Observations must be written down in both qualitative and quantitative forms.
• You should ask yourself:
• How will I organize and summarize the data?
• Will l use graphs, tables or charts?
• Can I see patterns or relationship in my data?

Independent, Dependent and Controlled Variables

• Independent variables are changed and manipulated or the cause.
• Dependent variables are the responding variable or the effect.
• Controlled variables are kept constant or treated the same.
• Independent variables are also known as "explanatory variables", "manipulated variables", or "controlled variables.".
• Dependent variables are are also termed as “measured variable," the "responding variable," or the "explained variable".
• The experimenter brings about change in the independent variables.
• Changes in the independent variables cause changes in the dependent variables.

Control and Experimental Groups

• CONTROL GROUP serves as the standard for comparison and has the same conditions as the other groups with no manipulation of the variable.
• EXPERIMENTAL GROUP is also known as a treatment group and receives the treatment to study it's effects.

Application of the Scientific Method

• Although scientists modify the scientific method when direct experimentation is not possible, they still discover cause and effect relationships.

History of the Scientific Method

• Sir Francis Bacon (1561-1626) is considered the father of the scientific method, but he was preceded by thinkers who formulated the ideas that inspired him.
• Aristotle pioneered scientific method in ancient Greece.

Scientific Theory

• A hypothesis turns into a theory when consistent results are obtained from a large number of repeated experiments.
• A theory is based on observations, research, and experimentation using factual evidence or data and explains an observed occurrence or phenomenon.

Observation vs Inference

• Qualitative observations use adjectives to describe what you observe.
• Quantitative observations use numbers to measure what you observe.
• Objective observations are based on facts that can be independently verified
• Subjective observations are based on personal opinions or interpretations.
• Inferences are interpretations or conclusions drawn from observations based on prior knowledge or logical reasoning.

Quantitative vs Qualitative Data

• Quantitative data is countable or measurable, relating to numbers, is factual, and gathered by measuring and counting things.
• Qualitative data is descriptive, using words and language to describe certain attributes, and is dynamic and subjective.