Galaxy Color – Design and Conduct Your Own Investigation
NGSS Connections
Supports PE HS-ESS1-2 : Earth’s Place in the Universe
Supports DCI ESS1.A: The Universe and Its Stars, PS4.A Wave Properties, PS4.B: Electromagnetic Radiation
Engages in SEP 1:Asking questions, 3:Planning and carrying out investigations, 4:Analyzing and interpreting data,5:Using mathematics and computational thinking, 6:Constructing explanations, 7:Engaging in argument from evidence and CCC 1:Patterns, 6:Structure and function: The motion and make up of stars and galaxies provide evidence for the Big Bang theory
You are ready to design your own investigation when you have made an observation of galaxy color in relationship to shape. Your expedition can begin with the simple question, “Is my observation true?” For example, the initial observation that most Sb type galaxies are ___ (color) sets up an investigation to find more Sb type galaxies and count how many match your observation.
Let’s get started. Begin with the work you did adding color to the Hubble diagram and continue through the steps outlined below. Instructions that step you through the research investigation process appear below and the student journals (links above) provide guidance for applying them to your own work.
1. A Good Question
You have already made observations about the phenomena of galaxy colors and formulated some questions about what you observed. This is where scientific investigations begin. Good questions drive investigations that help scientists develop models, explanations and theories; but in order to do that, the questions must be answerable and empirical.
Answerable: Sometimes previously unanswerable questions like “How far away is the nearest galaxy?” become answerable with improvements in technology. Often big questions like “What is dark matter?” are answered by a body of knowledge that develops over decades of focused questioning. Your question needs to be focused enough to be answerable with the available data and tools.
Empirical: Scientific questions that lead to investigations and experiments can be explored using evidence that is measurable and repeatable. A theory can be logical and widely accepted, but until it can be investigated using repeatable measurements, it is not empirical. Measurements can be as straightforward as a count or require complex equipment such as a spectrograph. A measurement that is calculated using other measurements is valid as long as the method is agreed upon. For example, a mathematical average is a calculation that is well-established and agreed upon.
2. Know Your Subject, Know Your Data
Typically, researchers spend large amounts of time getting to know the subject they are investigating. The goal of background research is to know the topic inside and out before designing the methods of the experiment. Although we are shortening this process in Expedition – Galaxy Colors, we need to reflect on what we already know about our subject and clearly identify the data needed for our investigation.
Everyone participating in this Expedition is asking a question related to galaxy shape and color. Begin by recording what you know about the concept of color in astronomy and about galaxy shapes. Your instructor may ask you to check outside resources. Discussing this step with others is important in uncovering mistakes and recalling information.
Next, think about the question your have written and list the data you need to answer that question. Find out where those data are located. In addition, identify the type of data you are collecting. If you are taking a measurement directly or recording a measurement that has been recorded in SkyServer, you are using quantitative data. If the data are descriptions of a characteristic for which there is no numeric measurement, the data are qualitative.
3. Write a Hypothesis and Identify the Variables
You should feel confident enough in your background knowledge and previous observations to form a possible answer to your research question. If your answer is plausible and able to be tested using data and procedures that can be repeated by others, then you have a hypothesis.
In the case of this expedition, it is most likely that you are writing a hypothesis that predicts a connection between two variables, galaxy shape and color. A variable is some feature or characteristic in an experiment that changes. Traditionally we think about one variable as being changed or manipulated by the researcher as the independent variable, and any other characteristic measured in order to assess a response as the dependent variable.
For the type investigation we are doing here, there is nothing the astronomer can do to change the stars or galaxies she is observing. Although computer modeling can be used to simulate phenomena and conduct investigations that do identify independent and dependent variables, that is not the case when working with information from a large database. We are, however, able to predict a relationship between two measurements. We will refer to these characteristics, collectively, as variables.
Your draft hypothesis should reference any variables you plan to measure and make a prediction. Your hypothesis is likely to follow one of the these examples:
- If galaxy color is related to galaxy shape then [make a prediction].
- More than [percent or numeric measure] of galaxies are classified as [Hubble Galaxy Type] are [color].
- The more spiral arms a galaxy has, [make a prediction].
4. Describe Your Procedures
Remember, good investigations are repeatable. Not only do your measurements need to be accessible to other scientists, but the steps you take to acquire and analyze your data must be described well. In this section report on:
- how you plan to gather data
- ow you are going to organize and analyze the results (Are you going to create graphs? What statistics or calculations will you use?)
- The criteria you will use when you are finished to decide if your hypothesis is supported by the data or not
The last point listed above may be the only one that is not obvious. It is essential that you consider BEFORE you conduct your experiment or investigation how you will decide if the data support the hypothesis or not. Notice, we do not use the words “true or false.” A scientific hypothesis is a tentative explanation that experimental findings either support or do not support. Only through repeated investigations over time do these statements gain wide acceptance. So, think about the procedures and statistics you plan to use and make a decision in advance about what results would support your hypothesis.
If you do not have experience with probability and statistics, you will not have as many tools available to you to complete this last step. In this case you can create a simple statement describing your criteria. Below is an example that uses percentages:
- My hypothesis is supported by my results if greater than [percentage] of elliptical galaxies are [color].
A note about tests of statistical significance
You may decide that you want to apply specific statistical tests to your data that allow you to report, in standardized ways, the level of confidence you have that your data are grouped or distributed in particular ways. Some of these include analysis of variance, chi square, and correlation testing. If you are familiar with these measures or your instructor requires them as part of your research design, you should document that you are gathering and handling your data collection in ways that allow you confidently complete these tests.
5. Follow Your Plan, Gather Your Data
Believe it or not, the difficult work is finished. If you have worked carefully and thoroughly to this point, you should be able to follow through with your plan. If you are working with others on similar projects, it could be helpful to have someone verify your work early to confirm that everything is going as planned. Clearly recording data and maintaining back-up copies is important. Good luck.
6. Conclusions – Interpret Your Results
Review your data, graphs and notes. The following questions will help you draw conclusions from your results:
- Do any patterns appear in my data? What appears to be true when I review my work?
- Do my two variables appear to be related? Describe the relationship as best you can with words or statistics.
- Is my hypothesis supported by the data?
This is also the time to report on any surprises. Did anything new reveal itself? Record any new questions that arose as a result of your investigation.
7. Discussion
This stage is when you pause to consider the investigation as a whole. Think about any factors that make you less confident in your results, things you would do differently the next time. New questions may have become obvious. Take time to consider these aspects now.
- Is there anything about your data or procedures that makes you less confident of your results
- Can you see any areas of your research design, data collection or analysis you would modify the next time?
- What new questions presented themselves as a result of your work?
8. Report, Share Findings, and Receive Feedback
he only way for others to learn about new information and new methods is to share results. It is also one of the ways scientists receive feedback and insights from others working in their area of study but with whom they may not have frequent contact. Organizing and presenting it in such a way that others can use it is the purpose of scientific communication. Sharing results is an essential part of the research process