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The Scientific Method Hands-On Labs, Inc. Version 42-0313-00-01

Read the entire exercise before you begin. Take time to organize the materials you will need and set aside a safe work space in which to complete the exercise.

Experiment Summary:

In this experiment, you will identify the importance of science and how it is a part of our daily lives. You will list and describe the steps of the scientific method, and define control groups, independent and dependent variables, and quantitative and qualitative data. You will also conduct research on topics associated with global climate change, develop hypotheses, and conduct experiments to test those hypotheses. Finally, you will use all of the knowledge gained throughout the lab to design your own experiment that demonstrates the importance of sea ice in regards to global temperatures.

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EXPERIMENT

Learning Objectives Upon completion of this laboratory, you will be able to:

● Relate science to your daily life.

● List and describe the steps of the scientific method.

● Describe controlled experiments and define conditions, independent and dependent variables, and controls.

● Differentiate between qualitative and quantitative data.

● Demonstrate the weight difference between dry air and carbon dioxide (CO2).

● Model the effects on temperature of normal and excess levels of greenhouse gases.

● Design your own experiment to model the effects of sea ice on water temperatures.

Time Allocation: 5 hours

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Materials Student Supplied Materials

Quantity Item Description 1 Baking soda 1 Bottle of vinegar 1 Box of matches or lighter 1 Candle 1 Clear plastic wrap 1 Coffee cup 2 Containers of equal size; Suggestions:

- Plastic containers - Milk cartons - Cardboard boxes - Glass dishes

1 Digital camera or smartphone 1 Dish soap 2 Large jars or glasses (with no bottleneck) 1 Measuring cup, 1 cup 1 Metal kitchen spoon 1 Pair of scissors 1 Pen or pencil 1 Reflective surface; Suggestions:

- Aluminum Foil - Mirror - Slab of metal

1 Roll of paper towels 1 Rubber band 1 Set of measuring spoons, 1 tablespoon and 1 teaspoon 2 Sheets of white paper 1 Source of heat; Suggestions:

- Direct sunlight - Heat lamp - Incandescent light (non-LED/energy saving light bulb)

1 Source of tap water 1 Stopwatch or timer 1 Tape, clear

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2 Thermometers, analog mercury filled* 1 White paper product:

- Construction paper - Card stock - Foam board - Poster board

*The recommended thermometers for performing this experiment are standard oral or anal analog thermometers that can be found at pet stores or drug stores. If you do not have access to two analog thermometers, one digital thermometer may replace one of the analog thermometers for Exercise 2. If you choose to do this, be certain to include this information in your Lab Report Assistant to account for variability in using two different materials. For Exercise 3, digital thermometers may be used if necessary.

To fully and accurately complete all lab exercises, you will need access to:

1. A computer to upload digital camera or smartphone images.

2. Basic photo editing software such as Microsoft® Word or PowerPoint®, to add labels, leader lines, or text to digital photos.

3. Subject-specific textbook or appropriate reference resources from lecture content or other suggested resources.

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Background What Has Science Done for You Lately?

The modern world would not be so advanced if it were not for technology, courtesy of science. Science is responsible for most modern conveniences such as electricity, raw material production, communication resources, and agricultural practices that supply food worldwide. Health care would not be what it is today without science. We would not have X-ray or MRI machines, prosthetics, medications or vaccinations, or knowledge that hand-washing reduces the spread of disease- causing microbes. Science is the foundation for most innovations. Science promoted the invention of cars in the 1800’s, and science continues to contribute to current transportation innovations such as improved gas mileage, reduced carbon emissions, and new discoveries regarding alternative fuels. Science also promotes the conservation of our planet through the preservation of millions of living species. See Figure 1.

Figure 1. A few developments made possible by science. ©Robert Adrian, Noyan Yimaz, jaroslavaV, Goran Bogicevic, Ekaterina Minaeva, Everett Historical, STUDIOMAX, Spotmatik Ltd, Andre w Mayovskyy, pixinoo,

Harvepino, aastock, Triff

Because of the role science plays in our everyday life, it shapes not only our personal decisions, but also policies and regulatory decisions made by the government. The creation of nutrition and warning labels, and the illegal dumping of hazardous waste are just a few protections developed because of science.

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The Scientific Method

Science is important in our daily lives, but how is science conducted? Scientists investigate and learn about the world either by an open-ended discovery process or by application of the scientific method.

The scientific method is a process used by scientists to acquire new knowledge or correct previous knowledge, solve a problem, or develop theories or explanations of natural phenomena. Scientists use the scientific method to collect and report information that is free of bias or opinion. The general process and the typical order of the steps are shown in Figure 2.

Figure 2. The scientific method. ©schab and janoon028

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The scientific method has seven steps:

1. Make an observation.

2. Ask a question and conduct background research on what is already known.

3. Formulate a hypothesis.

4. Test the hypothesis through experimentation.

5. Analyze data and draw conclusions.

6. Verify the conclusions through peer review.

7. Communicate the results.

The steps may vary, based on the scientist’s needs. For example, background information may be researched before conducting observations and asking questions. The steps of the scientific method are continuous and often lead to greater advancements in science through new observations and questions, all of which result in continued investigation. Often the results of discovery-based science are then used as the observations for a hypothesis-driven investigation.

Observations, Questions, and Research

Many research projects begin with simple observations. Observations should be objective and verifiable by other scientists. Clear observations lead to research questions. For example, an ecologist who observes a unique stand of trees in one area of the forest might ask, “Why is this unique tree species growing in this area?” The ecologist would then conduct research and collect background information about the tree species’ needs, such as how much nitrogen must be in the soil or how much water is needed for the tree to grow in an area. The ecologist might also look into how the tree reproduces and disperses seeds. Once information is collected, the scientist could begin to theorize about why the unique tree is growing in that particular location.

Formulating and Testing a Hypothesis

A hypothesis is a proposed explanation for a phenomenon and is a starting point for further investigation. A good hypothesis has the following characteristics:

● Is best stated as “if, then” to imply cause and effect

● Holds across space and time

● Is a tentative idea

● Agrees with available observations

● Is simple

● Most importantly, a good hypothesis is testable and potentially falsifiable. In fact, some of the most important scientific discoveries resulted from experiments in which the original hypothesis was NOT supported.

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Hypotheses can begin broad and after research is conducted new hypotheses can be formulated for a more detailed explanation or discovery. For example, a scientist might hypothesize that “if nitrogen is the primary nutrient for plants, then they will grow more rapidly with nitrogen fertilization than with phosphorus or potassium fertilization.” Once a hypothesis is formulated, the scientist designs a study to test the hypothesis.

Controlled experiments are commonly used to test hypotheses. A controlled experiment is a scientific investigation in which both the control group and experimental groups are kept under similar conditions apart from the variable being tested so that the effect or influence of the variable can be identified. A variable is one or more condition that is subject to change. There are two types of variables, independent and dependent. Independent variables are the variable being studied and manipulated during the experiment. As the scientist changes the independent variable, he/she makes observations. Dependent variables are the outcomes that are observed from the effect of the variable(s) on the study. The value of the dependent variable depends on how the independent variable is manipulated. A control group is not exposed to the variable(s) being tested. For many experiments, a control group is necessary to compare the results of the experiment.

Figure 3 shows an example of a controlled experiment regarding plant growth in relation to specific nutrients typically found in fertilizers. The independent variable, the factor being manipulated, is the type of nutrient (nitrogen, phosphorous, or potassium) in the fertilizer. The dependent variable, the outcome being observed, is the amount of plant growth, which could be the measurement of height in millimeters or centimeters. The plant that is not given any fertilizer is considered the control because it is not being exposed to any added nutrients. Conditions not differing between experimental and control groups include sunlight exposure, soil type, and water availability.

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Figure 3. Controlled experiment of plant growth versus the type of nutrient given to the plant. ©kak2s, DeiMosz, llibra

Experimental Design Example

Consider another example of an experiment; a scientist wants to determine if Drug X is effective for reducing blurred vision in patients with multiple sclerosis. The experimental design follows:

● Observation: The chemistry of Drug X is designed to target and improve vision in patients with multiple sclerosis.

● Question: What percent of patients that use Drug X experience reduced blurred vision?

● Hypothesis: If Drug X is effective, then it will reduce blurred vision in at least 30% of patients with multiple sclerosis.

● Independent variable: Drug dosage: amount (mg) of the drug consumed by each patient each day.

● Dependent variable: Percentage of patients with reduced blurred vision.

● Control group: Given a placebo (a sugar pill that does not contain the drug) in place of Drug X.

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Let’s assume that the drug is effective at reducing blurred vision in 30% of patients. In this case, it would be said that, “The hypothesis is supported.” One key aspect of all hypotheses is that they cannot be proven true. In this example, not all patients on earth with multiple sclerosis were included in the experiment. Therefore, science cannot prove that the drug is effective for all patients.

However, a hypothesis can be rejected or refuted based on the results. Let’s assume that the drug was only effective at reducing blurred vision in 20% of patients or that the control group also experienced a 30% reduction in blurred vision. In this case, it would be said that, “The hypothesis is rejected.” The scientist would ask new questions and refine the experimental design. Regardless if a hypothesis is supported or rejected the purpose of the experiment is fulfilled, in that we learn something new.

Analyzing the Data

Data collected from the experimental process must be analyzed before conclusions are made regarding the hypothesis. There are two types of data: quantitative data are numerical, and qualitative data are non-numerical. Recall the example with Drug X. An example of quantitative data would be the numeric scores that patients receive during formal vision tests. An example of qualitative data would be the patient’s opinion of whether their vision has improved. Analyzed data is typically illustrated as graphs, tables, and charts.

Independent variables are usually plotted on the horizontal axis (x-axis) and the dependent variable is plotted on the vertical axis (y-axis). Figure 4 shows a bar graph that describes data associated with Drug X from the earlier example. Notice that dosage amount (the independent, manipulated variable) is on the x-axis, and the percentage of reduced blurred vision (the dependent, outcome variable) is on the y-axis. Scientists would use this graph to show that vision test scores increased for more than 30% of patients at a 20 mg dose of Drug X.

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Figure 4. Example of a scientific figure for the effects that dosage of Drug X has on the percentage of patients with reduced blurred vision.

Statistical analysis is used to evaluate scientific data to determine if there is a significant difference between the control group and the experimental group. For example, if analysis of Drug X shows that 30% or more patients had a reduction in their blurred vision compared to patients in the control group that were given the placebo, then the hypothesis can be supported. For the purposes of this experimentation, you will not be asked to carry out a statistical analysis for the data you collect.

After a scientist analyzes the data they begin to draw conclusions based on the data and write a report on the findings of the experiment. This report includes the background research that was conducted, the experimental design, data results, and conclusions. The conclusions typically include an explanation about why the hypothesis was supported or refuted, a comparison of the investigation to other similar research, and ideas for future experimentation.

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Peer Reviewed Verification

For research to be reliable, it must be validated by a group of qualified peers. Most scientists send their findings to respected peer-reviewed journals for validation and publication, such as Nature, the journal pictured in Figure 5. The validation process is stringent and the report is reviewed by multiple topic area experts that provide recommendations for revisions. Then, the report may be accepted for publication in the journal. In addition to published papers, research findings are also shared via posters and live presentations. Presenting findings allows other scientists to verify results, develop new tests for existing hypotheses, and develop entirely new hypotheses of their own. Sharing the knowledge gained leads to solving other problems and facilitates the cycle of the scientific method.

Figure 5. A cover of “Nature - The International Weekly Journal of Science.” ©www.nature.com

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Large-Scale Investigations

The scientific method is used for many types of investigations beyond controlled experiments. Scientists often conduct large scale analyses, or meta analyses, that include data from multiple published investigations. Meta analyses can answer questions on a broader scale using validated data from other scientific experiments. Scientists regularly use complex computer models and extensive datasets to describe large-scale phenomena that cannot be captured with simple experimental designs. One example of using the scientific method for a large-scale analysis is monitoring climate change. Climatologists, ecologists, geologists, chemists, biologists, and other scientists are working together to compile data and protocols that can be used by other experts to continue cutting-edge research.

Climate change studies are difficult to reproduce since independent variables, such as the weather, cannot be controlled. For example, a scientist studying methane concentrations at a natural gas site in Colorado would have different results than a scientist conducting the same study at a site in Italy. However, the aggregation of data from multiple sites provides insight into climate change on an expansive, global scale rather than a smaller, regional scale. Climatologists have aggregated temperature data since the late 1800’s because climate must be measured over the course of decades and not yearly like the weather. See Figure 6.