When you analyze data from your investigation, you are trying to understand what your results mean. One way is to look for patterns. Are the numbers increasing or decreasing? Were all your trials very similar, or did they vary widely? A graph is a great way to help reveal these patterns. For example, a line graph that slopes upward shows a steady increase. Once you find patterns in the data, you interpret what those patterns mean. Look at the graph below. It shows atmospheric carbon dioxide concentrations (blue dotted line) and average global temperatures (red line). The pattern is that both began to increase at a fast rate from about 1900. The interpretation of the pattern answers the question: What does this pattern mean? If you know that carbon dioxide is a greenhouse gas, you might interpret the graph to mean that there is a connection between carbon dioxide concentration in the atmosphere and the average temperature of the planet. Atmospheric carbon dioxide concentrations are the blue dotted line and average global temperatures are the red line on the graph. Source: PDQ Digital Media Solutions Ltd/Pearson Education Ltd The vertical axis on the left is labeled CO2 (ppm) and ranges from 230 to 390 in increments of 20. The vertical axis on the right is labeled temperature (degree C) and ranges from 13.5 to 14.5 in increments of 0.2. The horizontal axis is labeled year and lists dates from 1000 to 2000 in 100-year increments. The line for CO2 starts from 280 in the year 1000 and remains nearly parallel to the horizontal axis until the year 1800 where it starts sloping upward. The line with a high growth rate reaches a point beyond 370 by the year 2000. The line for temperature starts from 13.82 in the year 1000 and moves as a rising and falling curves from left to right, fluctuating between 13.6 and 14.0 until 1900. The line then slopes upward with a high growth rate and reaches a point near 14.5 by 2000. The values used in the description are approximate. You may recall that a claim is a statement, and evidence supports a claim. When you analyze data, your claim is the statement of what you conclude from the patterns in the data. The data itself is your evidence. When you write an analysis, you state your conclusion and explain how the evidence supports itThe bar graph shows how many lichens were found on twigs at different distances from an industrial site. Lichens are very sensitive to air pollution and will not grow when there are high levels of air pollution. Numbers of lichens found at different distances from an industrial site. Source: Oxford Designers & Illustrators Ltd/Pearson Education Ltd The vertical axis is labeled number of lichens and ranges from 0 to 30 in increments of 5. The horizontal axis is labeled distance (km) and ranges from 0 (industrial area) to 16 (countryside) in increments of 2. The data is as follows. 8 to 10, 4. 10 to 12, 12. 12 to 14, 17. 14 to 16, 23. The values used in the description are approximate. Question 1 What pattern is shown in the graph for the relationship between distance from an industrial site and number of lichens? Reveal Answer Question 2 Could this evidence support a conclusion that the industrial site produces air pollution? Explain your answer.How well did your simulation reflect a situation you might find in nature? How well did you draw conclusions from the data you collected? What was the most challenging part of creating your own simulation? What was most interesting or surprising about your simulation? What are some other ways you could have completed this simulation? Explain.
3 answers
The graph shows a pattern where the number of lichens found increases as the distance from the industrial site increases. It is a downward sloping pattern.
Answer to Question 2:
Yes, this evidence could support a conclusion that the industrial site produces air pollution. Lichens are very sensitive to air pollution, and their absence or low numbers can indicate high levels of pollution in the area. As the distance from the industrial site increases, the number of lichens found increases, suggesting that there is less air pollution farther away from the site.