Thoroughly revised and updated, it is designed to let teachers and students easily find the topics they need, both in the classroom and for self-study. The book consists of five parts: The Writing Process Elements of Writing Language Issues Vocabulary for Writing Writing Models The first part explains and practises every stage of essay writing, from choosing the best sources, reading and note-making, through to referencing and proofreading. The four remaining parts, organised alphabetically, can be taught in conjunction with the first part or used on a remedial basis.
Interpreting graphs The majority of graphs published in scientific journals relate two variables. Although many other kinds of graphs exist, knowing how to fully interpret a two-variable graph can not only help anyone decipher the vast majority of graphs in the scientific literature but also offers a starting point for examining more complex graphs.
As an example, imagine trying to identify any long-term trends in the data table that follows of atmospheric carbon dioxide concentrations taken over several years at Mauna Loa Table 1; click on the excerpt below to see the complete data table. This is a small portion of a data table containing atmospheric carbon dioxide concentrations measured at Mauna Loa - click on it to see the full table.
The variables are straightforward — time in months in the top row of the table, years in the far left column of the table, and carbon dioxide CO2 concentrations within the individual table cells.
Yet, it is challenging for most people to make sense of that much numerical information. You would have to look carefully at the entire table to see any trends. But if we take the exact same data and plot it on a graph, this is what it looks like Figure 2: Reading a graph involves the following steps: The x-axis shows the variable of time in units of years, and the y-axis shows the range of the variable of CO2 concentration in units of parts per million ppm.
The dots are individual measurements of concentrations — the numbers shown in Table 1. Thus, the graph is showing us the change in atmospheric CO2 concentrations over time. Describing the data and trends: The line connects consecutive measurements, making it easier to see both the short- and long-term trends within the data.
On the graph, it is easy to see that the concentration of atmospheric CO2 steadily rose over time, from a low of about ppm in to a current level of about ppm.
Within that long-term trend, it's also easy to see that there are short-term, annual cycles of about 5 ppm. On the graph, scientists can derive additional information from the numerical data, such as how fast CO2 concentration is rising.
This rate can be determined by calculating the slope of the long-term trend in the numerical data, and seeing this rate on a graph makes it easily apparent. While a keen observer may have been able to pick out of the table the increase in CO2 concentrations over the five decades provided, it would be difficult for even a highly trained scientist to note the yearly cycling in atmospheric CO2 in the numerical data — a feature elegantly demonstrated in the sawtooth pattern of the line.
Putting data into a visual format is one step in data analysis and interpretationand well-designed graphs can help scientists interpret their data. Interpretation involves explaining why there is a long-term rise in atmospheric CO2 concentrations on top of an annual fluctuation, thus moving beyond the graph itself to put the data into context.
Seeing the regular and repeating cycle of about 5 ppm, scientists realized that this fluctuation must be related to natural changes on the planet due to seasonal plant activity.
Visual representation of these data also helped scientists to realize that the increase in CO2 concentrations over the five decades shown occurs in parallel with the industrial revolution and thus are almost certainly related to the growing number of human activities that release CO2 IPCC, It is important to note that neither one of these trends the long-term rise or the annual cycling nor the interpretation can be seen in a single measurement or data point.
That's one reason why you almost never hear scientists use the singular of the word data — datum. Imagine just one point on a graph.
You could draw a trend line going through it in any direction. Rigorous scientific practice requires multiple data points to make a clear interpretation, and a graph can be critical not only in showing the data themselves, but in demonstrating on how much data a scientist is basing his or her interpretation.
We just followed a short, logical process to extract a lot of information from this graph. Although an infinite variety of data can appear in graphical form, this same procedure can apply when reading any kind of graph.
What does the title say? What variable is represented on the x-axis? What is on the y-axis? What are the units of measurement? What do the symbols and colors mean? What is the numerical range of the data?
What kinds of patterns can you see in the distribution of the data as they are plotted? How do the patterns you see in the graph relate to other things you know? The same questions apply whether you are looking at a graph of two variables or something more complex. Because creating graphs is a form of data analysis and interpretationit is important to scrutinize a scientist's graphs as much as his or her written interpretation.
Comprehension Checkpoint Graphs are important because they a. Error and uncertainty estimation in visual data Graphs and other visual representations of scientific information also commonly contain another key element of scientific data analysis — a measure of the uncertainty or error within measurements see our Uncertainty, Error, and Confidence module.
For example, the graph in Figure 3 presents mean measurements of mercury emissions from soil at various times over the course of a single day. The error bars on each vertical bar provide the standard deviation of each measurement.Digestive System Diagram – The digestive system of a human consists of the following anatomy parts: stomach, intestines, bladder, rectum, anus, liver, colon, and other organs.
High quality printable digestive system . Get this from a library! Visuals: writing about graphs, tables and diagrams. [Gabi Duigu] -- Useful vocabulary and practical exercises for writing about visuals, with examples, models, and explanatory answers in the Answer Key.
Suitable for self-study, building vocabulary, and developing. Science Diagrams, available in both printable and projectable formats, serve as instructional tools that help students read and interpret visual devices, an important skill in STEM fields.
Many of the diagrams are enhanced visual teaching tools based on the diagrams found within Science A-Z resources, while others are only found in this collection.
Home / Figures and Charts. Figures and Charts They may be graphs, diagrams, photos, drawings, or maps. The Writing Center, University of North Carolina at Chapel Hill. If you enjoy using our handouts, we appreciate contributions of acknowledgement.
View All Tips & Tools. The Writing Center. Presenting statistical information – Graphs Introduction A graph is a visual representation of data that can present complex Apply a numbering system to the titles of all graphs so they can then be easily referenced in a summary list or in the appendices of the report.
. Several studies, journal guidelines, and discourses on scientific writing affirm the critical role that tables, figures, and graphs (or display items) play in enhancing the quality of manuscripts.