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Transcript of DATA The Star of the Science Project. Types of Scientific Inquiry Demonstrations Simple Inquiry...
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 tomeasure will be easy!
Basic format- If _______, then ______ will ________The third blank should use terms like increase, decrease or staythe 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 VariableAlso known as
independent variable It is the IF part of the
hypothesisPlotted on the X- axis
Responding VariableAlso known as the
dependent variable It is the THEN part of
the hypothesisPlotted on the Y-axis
Types of Data
Quantitative DataMeasurementsUnits should be from
the Metric SystemPlotted on a line
graph
Qualitative DataObservationsUse a RubricMay require an
“operational definition”
Plotted on a bar graph
The More; The BetterData 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- fertilizerResponding Variable- height of the tomato plantsTool 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 QualitativeHypothesis #2
If I add salt to water, then it will take longer to freeze.Manipulated Variable- saltResponding Variable- length of timeNo salt used in the control groupTool 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 waterResponding Variable- the health of the grassProblem 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.