Scientific Method Observe Experiment Research Draw Conclusions Form a Hypothesis Test a hypothesis

Scientific Method

Observe Observation- the process of obtaining information by using your senses (sight, touch, taste, hearing, and smell) Science is all about observing our natural world and trying to figure out why things happen and learn to predict what things may happen in the future. Once an observation is made, the next step is to form a hypothesis. (The first scientific observations were made in China Thousands of years ago)

Hypothesis Hypothesis- an idea or explanation based on observations and research, must be able to be tested by performing experiments. Example: Houseplants given a large amount of sunlight will grow faster than plants given a smaller amount of sunlight.

Designing an Experiment Scientific experiments must be well documented so they can be reproduced and reviewed by peers most experiments test one independent variable Independent variable- a factor being deliberately manipulated Dependent variable- the factor that changes as a result of the manipulation. This is what will be measured This “depends” on the independent variable Control Group- a run in the experiment in which no manipulations are made to the independent variable, this will serve as the baseline to compare all other runs to. (normal level of sunlight) (in a controlled experiment) all other factors in an experiment should be identical to ensure that the changes of the dependent variable are due to the manipulation of the independent variable. Experimental Group- runs in the experiment in the independent variable has been manipulated (the more repetitions you have of any experimental group can make your findings more meaningful

Designing an Experiment Examples: Independent variable- The amount of sunlight the house plants receive Dependent variable- how the plants respond to the different amounts of sunlight Height, mass, etc Control group- run with natural amount of sunlight to compare the runs with more and less sunlight to All runs should have plants of the same species, the same amount of water, same kind of soil, etc. Experimental groups-runs with lights to increase the light, and runs with shades to decrease the amount of light

Measurements and Analysis To draw conclusions measurements from your experiment must be analyzed The “International System of Units”(SI) is used when taking measurements in a scientific experiment so the data can be analyzed by scientists all over the world These units are all based on units of 10- metric system

SI Units Length Mass Volume Time Temperature

SI Units Length (kg) kilograms Mass (L) liters Volume (s) seconds Time (K) kelvins Temperature (m) meters

Converting SI Abbreviation prefix value Scientific notation E exa 1,000,000,000,000,000,000 10^18 P peta 1,000,000,000,000,000 10^15 T tera 1,000,000,000,000 10^12 G giga 1,000,000,000 10^9 M mega 1,000,000 10^6 k kilo 1,000 10^3 h hecto 100 10^2 da deka 10 10^1 Unit (meter) N/A 1 10^0 d deci 0.1 10^-1 c centi 0.01 10^-2 m milli 0.001 10^-3 μ micro 0.000,001 10^-6 n nano 0.000,000,001 10^-9 p pico 0.000,000,000,001 f femto 0.000,000,000,000,001 10^-15 a atto 0.000,000,000,000,000,001 10^-18 Converting SI

Scientific Notation Science often deals with really small or really large numbers so in order to make them more manageable we use scientific notation Example: Earth’s distance to the sun is146,000,000km or 1.46x10^8km Length of a red blood cell is 0.000006m or 6x10^-6m

Graphs and charts Graphs and charts can be used to help visualize and interpret data Common graphs Pie chart Scatterplot Bar graphs

Pie Chart A circle divided into portions representing a whole This type of chart is good for showing percentage or proportion data

Scatter Plot/ Line Graph Good for showing data over time

Bar Graph Good for showing data over time or comparing categories of data

Accuracy vs. Precision Accuracy- how close a measurement is to the true value Precision- exactness of a measurement A measurement in millimeters is more precise than a measurement in centimeters.

Significant Figures Any digit that carries meaning in regards to the precision of your measurement 0.00700 0.052 370. 10.0 705.001 37,000

Significant Figures Any digit that carries meaning in regards to the precision of your measurement 0.00700 3 0.052 2 370. 3 10.0 3 705.001 6 37,000 2

Error Error- The amount of imprecision or variation in a set of measurements Percent error- how far off the measurement is from the accepted value PE=((accepted-experimental)/accepted)X100 Confidence interval- the percent of measurements in an experiment that fall within a range of measurements The average ear of corn in a field is 23cm and 90% of the ears are within 3cm of the average The average length of corn is 23cm+- 3cm with 90% confidence

Drawing Conclusions After many experiments a conclusion can be made If the results match what was suspected in your hypothesis, then it supports your hypothesis *does not prove If your results do not match your expectations then your hypothesis is not supported and further experiments can be ran and the hypothesis may be altered. It is not a failed experiment if your hypothesis is not supported

Models In nature it is nearly impossible to have a controlled experiment so models are used model- description, representation, or imitation of an object, system, process, or concept

Types of Models Physical Models- three dimensional models that can be touched Graphical models- two deminsional models such as charts and maps Conceptual models- model that represents how a system is organized or how it works Mathematical models- mathematical equations that represents the was a system or process works Computer models- computer programs that represent simple processes or complex systems where variables can be manipulated and the outcomes can be predicted.

Acceptance of Scientific Ideas Results of an experiment must pass a peer review (panel of experts of the field) to be published. Once findings have been replicated several times and not been contradicted they may become a theory Theory- explanation that is consistent with all existing tests and observations