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be performed to find the answer. Something is changed in order to be tested. Measurable A question is not testable if: Too broad • The answer could be found with a simple Google Search ● Opinion You try Q) What type of bear is best? Reason: Too broad Make it testable: How does the amount of honey a bear eats affect how high up a tree it can climb? Something changed: the amount of honey Something measured: how high up a tree it climbs What are we changing or measuring Does changing the height of the ramp affect the speed of a car going down the ramp? What are we changing? The speed. What are we measuring? The height of the ramp. Testable Questions Format Plug it into the format: "What is the effect of •Amount of sunlight Amount of water • Soil type Cause/Change Amount of fertilizer Independent Variable and Dependent Variable Independent Variable: What the scientist changes The cause of an effect 3 What is Hypothesis? Independent variable (cause) (Cause) F Independent Variable because Practice Writing Hypotheses on Dependent Variable: (Effect) Dependent Variable Height of plant • Speed of growth • Color of leaves Effect/Measure A prediction that answers your testable question! A thoughtful or educated guess that answers the testable question. NEVER written in the form of a question Does NOT have to be "correct" Format for Hypothesis If then ? Dependent variable (based on observations / research) (Effect) What the scientist measure ↳ The effect of changing the Indentation Variable TQ: What is the effect of amount of sugar eaten on the time it takes to run a lap? Hypothesis: If the amount of sugar eaten increases, then the amount of time it takes to run a lap will decrease because slow down your brain. Hypotheses vs. Theory Aummmmm A Definition Based on... Purpose Constants Hypothesis Prediction on an observed phenomenon Prediction, suggestion Same type of plant Same type of soil Same type of fertilizer Same amount of water The ONLY thing changing (IV) is the amount of sunlight Experimental and Control group You try ALI Explanation for a set of verified, proven hypotheses Present a possibility and encourages Explain why a large set of further experimentation Theory Evidence, verification, repeated testing, wide scientific consensus something that scientist makes sure is the same throughout the experiment • Besides the independent variable, all other materials need to remain unchanged or constant For example: Within an experiment, there are TWO groups 1. Experimental group (does receive the independent variable) 2. Control group (does NOT receive the independent variable) observations are consistently made Dependent Variable = Responding Variable = Y axis ~ Manipulated Variable = Independent Variable = X axis Observations vs. Inferences Importance of Control Groups: AUT • Allows you to be sure that any change in the dependent variable is due to the independent variable you are manipulating / testing We want to test the effect of sunlight on plant height. 1. Identify the independent variable- sunlight 2. Identify the dependent variable- plant height 3. Identify the control group (does NOT receive IV)- no sunlight 4. Identify the experimental group (does receive IV)- sunlight 4Observation: When you use one or more of your senses to gather information Inference: When you make explanations for the things you observe You try Observations: You see that your cup fell off the kitchen table and broke. Inference: Who do you think did it? The cat knock the cup down. Inferences vs. Hypothesis Inference: Conclusion based on what you observe Hypothesis: Prediction about something tat hasn't happened yet. TAILS Acronym • Title-includes both variables "DRY MIX" Dependent/Responding Variable on) axis Manipulated Independent Variable on X axis • Axis-IV on X-axis and DV on Y-axis Interval-The interval is appropriate for the scale Label-Both axes are labeled • Scale-Min and max values are appropriate O Bar Graph vs. Line Graph • Bar Graph: used for comparing data Line Graph: used to show change over LTIME Time is the IV What is CER? • CER, as you may have guessed, stands for claim, evidence and reasoning. • These are the three main parts of a good scientific conclusion. You've already been using CER in another part of the scientific method. CER Acronym - Claim 6000 5000 4000 3000- 2000 2014 has to have numbers ↳ Evidence directly supports your claim of truth. In science we draw our evidence from two main sources. ↳ Data ↳ Observations Number of supplies 10 9 7 KI 6 Simple Line Plot 2015 2016 Year 2017 Bar Graph School supplies students use I Pencil Scale Pen Sharpner Eraser Types of School supplies 2018 Claims are statements that state something as the truth. This something is reasonable and is based on the data and observations that you've collected in ↳your experiment. -Evidence Reasoning Reasoning ties your claim your claim and evidence together. -With Reasoning: Foxes are faster when hunting squirrels than rabbits. The color gray produced speeds of 20 mph while white only produced speeds of 10 mph. The squirrels used in this experiment were gray and the rabbits were white. When chasing these animals in a controlled environment, trained foxes were measured at a higher speed (20 mph) when they were "hunting" a squirrel. However, when "hunting" a rabbit, their speed was reduced by half, down to 10 mph. ↳ Without reasoning, you're just making claims and putting evidence. -Without Reasoning: Foxes are faster when hunting squirrels than rabbits. The color gray produced speeds of 20 mph while white only produced speeds of 10 mph. For example: Claim: The plants that were given more hours of sunlight did not grow as tall as those given less sunlight. • Evidence: The plant exposed to only 1 hour of sunlight grew the tallest at 10cm. The plants exposed to 2 hours of sunlight grew 8cm, and the plant exposed to 3 hours of sunlight only grew 5cm. • Reasoning: This shows how this type of plant thrives in low light. When exposed to too much sunlight, it's water dried up and it was unable to perform photosynthesis. Plant Growth (cm.) Temperature (°C) 5 10 15 Hours in Sunlight 20 25 Heart Rate (beats/min) 108 Conclusion 152 200 260 300 1 10 Heart Rate (beats/min) As the temperature increases, the heart rate in Daphnia increases 300 275 250 225 200 175 150 125 100 75 50 25 0 8 2 8 Title 5 10 15 20 Temperature (°C) 25 3 5 Scoring Guide • 1 point for marking an appropriate scale on the axis labeled "temperature" • 1 point for marking an appropriate scale on the axis labeled "Heart Rate" • 1 point for plotting the data correctly, surrounding each point with a small circle and connecting the points • 1 point for identifying a valid conclusion