# The Star of the Science Project

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The Star of the Science Project
DATA The Star of the Science Project

Types of Scientific Inquiry
Demonstrations Simple Inquiry Comparative Studies Descriptive Studies Controlled Experiments Models

The Hypothesis If you write the hypothesis correctly, then knowing what to measure will be easy! Basic format- If _______, then ______ will ________ The third blank should use terms like increase, decrease or stay the same. EXAMPLE HYPOTHESES If I add fertilizer to the soil, then the tomato plants will grow tall. If I add salt to water, then it will take longer to freeze. If I use reclaimed water, then the grass will be healthier.

Variables Manipulated Variable Also known as independent variable
It is the IF part of the hypothesis Plotted on the X- axis Responding Variable Also known as the dependent variable It is the THEN part of the hypothesis Plotted on the Y-axis

Types of Data Quantitative Data Measurements
Units should be from the Metric System Plotted on a line graph Qualitative Data Observations Use a Rubric May require an “operational definition” Plotted on a bar graph

The More; The Better Data that is
A valid experiment is one in which the data collected is either from a large sample size or has many repeated trials. The experimental design usually determines which is more feasible to accomplish in the time span of a school science project. Collect both quantitative data and qualitative data during an experiment- data not collected- is data lost forever. All original data is collected in the log book.

Quantitative Data-Hypothesis #1
If I add fertilizer to the soil, then the tomato plants will grow tall. Manipulated Variable- fertilizer Responding Variable- height of the tomato plants Tool used- meter stick; units Meters SAMPLE SIZE should be considered in this situation. A controlled experiment would have the amount of fertilizer used in each group varied with the control group receiving no fertilizer.

Quantitative and Qualitative Hypothesis #2
If I add salt to water, then it will take longer to freeze. Manipulated Variable- salt Responding Variable- length of time No salt used in the control group Tool used- timer; units Minutes/Seconds Problem encountered- What constitutes ‘Freeze’? Solved by developing what is called an OPERATIONAL DEFINTION. Example- Frozen is when the toothpick in the water can no longer be moved. Number of trials might be more appropriate in this experiment.

Qualitative -Hypothesis #3
If I use reclaimed water, then the grass will be healthier. Manipulated Variable- reclaimed water Responding Variable- the health of the grass Problem encountered- what constitutes healthy grass? Begin with an operational definition: Healthy grass is deep green and thick. However- what if what I think is deep green is not what others think. Solution is to use a rubric such as a Likert scale. On a scale of 1-5 rate the greeness of the grass; On a scale of 1-5 rate the thickness of the grass. If descriptive study format is used then the reclaimed water might be compared to tap water. A large sample size for both groups would make the experiment more valid. Using many people to rate the samples would make the results more reliable.

Format on Exhibit Data tables should always be included with a graph
When plotting more than one trial on a line graph be sure to include a key Be sure to label both axes and give the graph a title Units should be included in labels

Analyze Data Graphs show the relationship between the variables.
Relationships can be direct as in “as one increases the other increases” or as “one decreases the other decreases” Relationships can be indirect as in “as one increases the other decreases” Some graphs may show no relationship between the variables Consider mean, median or mode as ways to make the data more manageable- best fit lines might be more appropriate than connect the dot lines

CONCLUSION Refer back to the hypothesis to determine if the data supported the hypothesis, or not. Don’t “prove” anything and also don’t throw out an experiment just because ‘nothing’ happened- the fact that nothing happened is data. Discuss the data in the conclusion and include an inference that explains why such an outcome occurred.

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