Scientific Method It is a process that is used to find answers to questions about the world around us.

There are several versions of the scientific method but all have the same basic steps.

Scientific Method 1. Observation 2. Hypothesis 3. Test with an experiment 4. Analyze results or data 5. Draw conclusion 6. Communicate results If hypothesis is false or partially true. Must restate hypothesis

1. Observation Ask a question A phenomena unexplained occurrence that happens in the natural world leading you to a question. -based on observations and information gained through previous research or knowledge. -must be defined, measureable

Practice Observing What are 3 things you can observe in the picture? Example: I observe grass and trees on the mountain tops

2. Hypothesis What do you think will happen? Speculative guess that has yet to be tested. A prediction is an assumption one makes based off what they have observed. Stated in a If Then statement. Must be testable. Always ask yourself. Is this testable?

Practice forming a hypothesis Using one of your observations + predictions forms a testable hypothesis. Example: If there is more than 20 inches of rain a year then an additional 20 feet of grass and trees will cover the mountain tops.

Practice Predicting Predict 3 things that might happen in the picture. Example: I predict the grass and trees will expand to the other mountain tops if they get enough rain.

Hypothesis Vs. Theory A hypothesis attempts to answer questions by putting forth a plausible explanation that has yet to be rigorously tested. A theory, on the other hand, has already undergone extensive testing by various scientists and is generally accepted as being an accurate explanation of an observation but not proven. (example: Big Bang Theory)

3. Test with a experiment How will you test your hypothesis. Develop a procedure for experimentation Test with variables Independent variable- what you control Dependent variable- what will be measured. What the investigator thinks will be affected during the experiment Controlled – unrelated factors, possibly affecting the experiment must be kept constant.

Practice identifying the independent and dependent variable in a hypothesis Example: If there is more than 20 inches of rain then an additional 20 feet of grass and trees will cover the mountain tops. Identify the independent variable. Identify the dependent variable. Identify a control. If there is more than 20 inches of rain Then an additional 20 feet of mountain tops will be covered with grass and trees. It is being measured cover a portion of the mountain that gets no rain.

Other factors to consider when testing an experiment. Need multiple samples Combine data from multiple trials Peer review (Can someone else follow your procedures and get same results.

4. Analyze results/Data Data can be qualitative or quantitative Qualitative-Deals with descriptions. Observed but not measured. Qualitative → Quality Quantitative-Deals with numbers,can be measured. Quantitative → Quantity  Some friendly red ants 12 red ants Using the illustration practice identifying qualitative and quantitative

Practice quantitative vs. qualitative Quantitative-list three Qualitative-list three (example the picture is 10in x 14in I guessed) (example the picture has blues, greens, and brown colors)

Analyze results and Data 3 Types of graphs Bar graph-useful in comparing information gathered by counting Pie graph-Shows a fixed quantity. Is broken down into parts. Also show a percent(%) that will equal 100. 3. Line graph-Show a relationship between variables over time (independent vs. dependent)

Graphing Practice 1. Identify the 3 graphs as pie, line, or bar. 2 Graphing Practice 1. Identify the 3 graphs as pie, line, or bar. 2. Identify the independent and dependent variable on the line and bar graphs. 3. What percentage of Americans enjoy romance movies? 4. What can you infer from the line graph?

Why Analyze results/Data To see if the result of the experiment support or refute the hypothesis. What can you infer (inference) from the data DRY dependent responsive y-axis MIX manipulative independent x-axis M I L E S D R Y MIX

Inference What do you think the picture or graph is based on using your observations and what you already know. -My observation: a lot of green grass and trees. -What I already know: trees and grass require water to grow and stay green. Example: I infer that this area gets an abundance of rain because of the bright green vegetation

5. Draw conclusions Did the data support the hypothesis? M I L E S Did the data support the hypothesis? If there is more than 20 inches of rain then an additional 10 miles of grass and trees will cover the mountain tops. If yes move forward If no must re-construct hypothesis. D R Y MIX Does the graph support my hypothesis? YES

6. Communicate Results Presented in the form of a lab report. Summarizes experiment and results. Share your results with others

Lab Report Template                                          Title: * a brief, concise, yet descriptive title Statement of the Problem: * What question(s) are you trying to answer? * Include any preliminary observations or background information about the subject Hypothesis: * Write a possible solution for the problem. * Make sure this possible solution is a complete sentence. * Make sure the statement is testable. Materials: * Make a list of ALL items used in the lab. Procedure: * Write a paragraph (complete sentences) which explains what you did in the lab. * Your procedure should be written so that anyone else could repeat the experiment. Results (Data): * This section should include any data tables, observations, or additional notes you make during the lab. * You may attach a separate sheet(s) if necessary. * All tables, graphs and charts should be labeled appropriately Conclusions: * Accept or reject your hypothesis. * EXPLAIN why you accepted or rejected your hypothesis using data from the lab. * Include a summary of the data - averages, highest, lowest..etc to help the reader understand your results * List one thing you learned and describe how it applies to a real-life situation. *Discuss possible errors that could have occurred in the collection of the data (experimental errors)