Science• Systematic knowledge of the physical or material

world gained through observation and experimentation.

Observation• Consists of receiving knowledge of the outside world through our

senses, or recording information using scientific tools and instruments.

• Example:Once dropping the M&M into the water, the color of the M&M spread into the water in the shape of a circle around the M&M. The circle continued to get larger the longer the M&M sat in the water. The M&M itself turned white.

Questions can be divided into two categories: Causal and Existence.

 • Scientists ask causal questions when trying to

understand the world.• Causal Questions are Testable.

Causal Questions are Testable• Testable questions begin with: How, What, If, Does

and I Wonder. • These questions can be addressed through scientific

experiments. • Examples:– What color M&M dissolves fastest in water?– Does temperature of the water change the

dissolving rate of an M&M?

Testable Questions…

• ask about objects, organisms, and events in the natural world.

• can be answered through investigations that involve experiments, observations, or surveys.

• are answered by collecting and analyzing evidence that is measurable.

• relate to scientific ideas rather than personal preference or moral values.

• do not relate to the supernatural or to non-measurable phenomena.

Existence Questions – not usually testable

• Usually begin with “Why” and generally require recall of factual information.

• Examples:–  Why does the candy coating on an M&M

dissolve?– Why does hot water cause the M&M to dissolve

faster?

Hypothesis• A tentative explanation for an observation,

phenomenon, or scientific problem that can be tested by further investigation.

• Example:The brown M&M will dissolve faster than the other colors because brown is a mixture of all the other colors so it has more color and will therefore dissolve faster.

Variables• factors or elements that are likely to vary or

change. • A typical study has an independent variable

and a dependent variable.

What’s the difference?

• The independent (or manipulated) variable is something that the experimenter purposely changes or varies over the course of the investigation.

• The dependent (or responding) variable is the one that is observed and likely changes in response to the independent variable.

• So… in our M&M experiment where we were trying to answer the testable question, “Do some M&M colors dissolve faster than others?” what was the independent variable (what did we purposefully change)?

• What was the dependent variable (what did we observe or measure)?

Identifying variables in an experiment:

• For example, a student might change the position of a plane’s wing to see how it affects the average speed of a model plane.

• What would be the independent variable?• Dependent variable?

Independent Variable:The wing position because the student purposely changes its location

Dependent Variable:The average speed since the average speed would depend on the location of the wing and it’s what’s being observed or measured

• In an experiment, one variable is changed (independent) and a second variable is measured in response (dependent).

To summarize variables…

Controlling Variables• When conducting an experiment, all other variables

must be kept the same throughout the investigation; they should be controlled. The variables that are not changed are called controlled variables.

• Example:– When we tested “Does water temperature affect the dissolving

speed of M&Ms?” we kept everything else the same (color of M&M, amount of water, type of dish, not stirring or disturbing either place…) except the water temperature.

Control Group

• Group separated from the rest of the experiment where the independent variable being tested cannot influence the results.

• Using a control group enables us to study the impact of the independent variable.

• Example:– The control group in our M&M experiment “Does

temperature of water change the dissolving speed?” our control group was the M&M we placed in room temperature water.

Data• Data are your recorded observations and

measurements taken during an experiment.• Data tables are usually used to organize data.• Data can be qualitative (descriptive) or

quantitative (numerical)

Color of M&M Time for color ring to reach “finish line”

Blue 90 seconds

Green  85 seconds

Brown 91 seconds

In general, data tables should have the following format:

Independent Variable (What you modify)

Dependent Variable (What you Measure) Average of the Trials

Trial 1 Trial 2 Trial 3

Color of M&M Time for color to reach “finish line” Average of the Trials

Trial 1 Trial 2 Trial 3

Blue 90s 91s 89s 90.0s

Green 90 90 89 89.7s

Brown 87 90 92 89.7s

So, for our M&M experiment it would look like:

Technology is often used in science to help measure & collect data.

• What technology could we have used in our M&M experiment that would have given us more accurate data?

Why & how to graph data• Graphs represent data in a visual, easy to read manner,

which helps us to understand data more clearly• Independent variable should be placed along the bottom of

the x-axis. • Dependent variable should be placed on the side of the y-

axis.• Label the axes — don't forget to include the units of

measurement (grams, centimeters, liters, etc.). • If you have more than one set of data, show each series in a

different color or symbol and include a legend with clear labels.

 

Different Types of Graphs - Bar

• Bar Graph used when comparing different trials or different experimental groups. It also may be a good choice if your independent variable is not numerical.

Different Types of Graphs - line• Line Graph is a good way to look at how

something changes, usually over time or sometimes across space.

Different Types of Graphs - Pie• Pie Graph is the best way to show portions, or

parts of a whole. Using this pie graph, we can see just what portion of all the trash each particular type of trash represents.

Different Types of Graphs – Scatter Plot• Similar to line graphs • Show how much one variable is affected by another.

The relationship between two variables is called their correlation .

• The closer the data points come to making a straight line, the higher the correlation between the two variables, or the stronger the relationship.

Scatter Plot - continued

Best Fit Line - used with scatter plots

• Drawn through a scatter plot to find the direction of an association between two variables. This line of best fit can then be used to make predictions. • To draw a line of best fit, balance the number of points above the line with the number of points below the line• Is association positive or negative?• Is association weak or strong?•Use the line of best fit to predict the swimming pool attendance where the daily maximum temperature is:(i)  18 ºC          (ii)  30 ºC           (iii)  40 ºC

Inference• Inference is just a big word that means judgement. • If you infer that something has happened, you do not see,

hear, feel, smell, or taste the actual event. But from what you know, it makes sense to think that it has happened.

• You make inferences everyday. Most of the time you do so without thinking about it.

• Suppose you are sitting in your car stopped at a red signal light. You hear screeching tires, then a loud crash and breaking glass. You see nothing, but you infer that there has been a car accident.

• Example:– On your way to your next class after conducting the M&M

experiment, you notice red color on your hand and pencil. The M&M you tested was red. You infer that the red color from the M&M dissolved in the sweat and oils on your hand.

Conclusion• The answer to a testable question that is supported by

the evidence collected (data).• Example:

– No one color of M&M dissolves faster than the others. Six different groups tested the various colors and each group found a different color to dissolve faster. In order to be more sure of this conclusion, more trials would need to be conducted.

Reliability & Validity

• An experiment is considered reliable if other researchers are able to perform exactly the same experiment, under the same conditions and generate the same results. This will reinforce the findings and ensure that the wider scientific community will accept the conclusion. Multiple trials improve reliability.

• Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. Valid experiments control all the variables except the one being tested, precisely measure and record data, accurately display the data, develop a conclusion based on the data.