Scientific Investigation (Scientific Method) Steps: 1. Identify a testable question 2. Research information about the topic 3. State the hypothesis as a predicted answer to the question. It should state the possible outcome of the investigation. (guess) 4. Design an experiment to test the hypothesis, controlling all variables except the independent variable. ● Plan for independent and dependent variables ● Plan for factors that should be held constant (controlled variables) ● List the materials needed to conduct the experiment ● List the procedures to be followed. ● Plan for recording, organizing and analyzing data. 5. Conduct the experiment and record data (observation) in tables, graphs, or charts. Analyze the data in the tables, graphs, or charts to figure out what the data means (describe the relationship between the variables) 6. Compare the results to the hypothesis and write a conclusion that will support or not support the hypothesis based on the recorded data. 7. Communicate the results to others (presentation). →Step 1: Identify a Testable Question Generating Testable Questions Testable questions are those that ● Test one independent (manipulated) variable ● Include a dependent (responding) variable ● Include the relationship between the two variables ● Can be answered through scientific investigation and data collection →Step 2: Research Background Information Collect knowledge needed to know about the subject of the experiment. This is used to develop a hypothesis or possibly refine your question. →Step 3: State the Hypothesis The prediction that you make about the relationship between the variables in your testable question is your hypothesis. ● A hypothesis can be stated positively or negatively. ● States the the relationship between the two variables ● A hypothesis can be stated as a cause-and-effect statement. ● If…...then…. →Step 4: Design an Experiment/Method of Experimentation If there is only one independent variable, then there is only one factor that can affect the results of an experiment. This helps us know what actually caused the change. ● List all factors that could possibly affect the results of your test. ● Choose one factor to be the independent variable. ● Independent or Manipulated Variable is the variable that changes. ● What is the results or the effect of your experiment, dependent variable. ● Dependent or Responding Variable is what the scientist is keeping track of, or observe/measure during the experiment, their results. ● Decide how you are going to control all the other factors on the list. Constant/Controlled Variables are the factors that will be kept the same in your investigation. ● You may decide to have a control group in your experiment. You will treat this set-up or group like the experimental group except you will not apply the independent variable. Your comparison group. →Step 5: Conduct Experiment and Record Data Observation and Inference You should collect data throughout any controlled scientific investigation. Data includes both scientific observation and inferences. You make scientific observation by carefully identifying and describing properties using your five senses or scientific tools. Scientific observation can be classified as quantitative or qualitative. ● Quantitative observations are observations that use NUMBERS (amounts) or measurement (including the unit label) or observations that make relative comparisons, such as more than, all, less than, few , or none. ● Qualitative observations are observations that are made using only the senses and refer to specific properties. Organizing Data A data table organizes data collected in an experiment so that it can be read easily. ● Plan your data table before the investigation starts ● Think about the kind and number of items needed to be included and the units to use ● Organize your data tables in columns and rows. The columns should have headings that shows the quantity and unit of the data in that column ● List the independent variable in the column on the left side ● List the dependent variable in the column on the right side Constructing graphs ● Identify the independent variable and the dependent variable from the data. ● The independent variable is written on the x-axis ● The dependent variable is written on the y-axis ● DRY MIX Dependent Manipulated Responding Independent Y-axis X-axis ● Include appropriate units of measurement for each variable ● Look at the range of data to determine the intervals or increments of the x-axis and y-axis. The increments do not need to be the same but need to be consistent. ● Plot the data on the graph as matched pairs. ● Write an appropriate title for the graph. →Step 6: Analyze Data and Write your conclusion Validating Results of Experiments Scientist are careful to report true or valid, results and conclusions. To insure this, they conduct repeated trials to determine patterns in their data. They must replicate (reproduce) the results of their testing to verify their conclusions. The more data that is collected through replication, the more reliable the results. When gathering data during an experiment: ● Gather data more than once under the SAME conditions. ● Repetition ensures that the experiment is valid. ● Each set of repeated data is called trial. Analyzing Data and Drawing Conclusion ● Interpret and analyze the data you collected from your investigation. ● A valid conclusion is a summary of the findings of an experiment. It is based on scientific observation, inferences, and collected data that states the relationship between the independent and dependent variables. ● When you make a conclusion statement, it should say whether the collected data supports the hypothesis or does not support the hypothesis (not that the hypothesis was right or wrong). →Step 7: Communicate Results Communicating Data Diagrams identify specific parts or how they work, a sequence of events, or how things are alike and different. Graphs compare data. Graphs show not only information but also the relationships between the data. Different types of graphs show different types of information. ● Bar graph are often used for qualitative observations. The lengths of the bars on a bar graph represent and compare data. A numerical scale determines the lengths of the bars. ● Circle graphs show percentages of a whole. The entire circle is equal to 100% of the data. ● Line graphs are a good way to show quantitative data collected over time. ● Line graphs can also show how quantitative data changes the relationship between manipulated (changing) variable and responding (resulting) variable. The lines on a line graph changes at a glance.
