1. The Star of the Science Project
DATA
The Star of the Science Project

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

3. 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.

4. 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

5. 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

6. 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.

7. 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.

8. 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.

9. 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.

10. 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

11. 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

12. 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.