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Creating Figures

Creating Figures. Figure 9. Daily patterns of full stomachs (%) of herring and sprat sampled during the 1997 survey. Standard errors (bars) were not available for sprat. From Cardinale et al . (2003). When to use figures vs. tables vs. text?.

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Creating Figures

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  1. Creating Figures • Figure 9. Daily patterns of full stomachs (%) of herring and sprat sampled during the 1997 survey. Standard errors (bars) were not available for sprat. • From Cardinale et al. (2003)

  2. When to use figures vs. tables vs. text? t (time) - 150', T (temperature) = 32C; t = 0', T = 25C; t = 6',T = 29C; t = 3', T= 27C; t=12’, T = 32C; t = 9',T = 31C temperature (C) time (min) 32  150 27 3 31 9 29 6 25 0 32 12 example from Gopen and Swan 1990

  3. When to use figures vs. tables vs. text? t (time) - 150', T (temperature) = 32C; t = 0', T = 25C; t = 6',T = 29C; t = 3', T= 27C; t=12’, T = 32C; t = 9',T = 31C temperature (C) time (min) 25 0 27 3 29 6 31 9 32 12 32  150

  4. When to use figures vs. tables vs. text? t (time) - 150', T (temperature) = 32C; t = 0', T = 25C; t = 6',T = 29C; t = 3', T= 27C; t=12’, T = 32C; t = 9',T = 31C time (min) temperature (C) 0 25 3 27 6 29 9 31 12 32 150 32 

  5. When to use figures vs. tables vs. text? t (time) - 150', T (temperature) = 32C; t = 0', T = 25C; t = 6',T = 29C; t = 3', T= 27C; t=12’, T = 32C; t = 9',T = 31C time (min) temperature (C) 0 25 3 27 6 29 9 31 12 32 150 32 

  6. When to use figures vs. tables? • General rules of thumb: • < 4 numbers, state them in the text • Tables are used to report data,figures are used to look at relationships and patterns

  7. When to use figures vs. tables? • Figures - present complex data patterns, when visual is more intuitive than numbers, many data points • Easy to describe in text; figure not necessary • More difficult to describe in text; figure is instructive • 10˚ C • 4˚ C • Cod growth rate • (mm/yr) • Cod growth rate • (mm/yr) • South • North • South • North • Tables – convey essential info that does not fit into text easily (e.g., lat/lon of multiple sites, model parameters), data of interest to others (e.g., model coefficients)

  8. Numbering – tables and figures each numbered in order of citation in text (each start at Table 1 and Figure 1)

  9. The purpose of figures • To present your data in an informative summary • To visualize your data – look for relationships, trends, outliers • To maximize information transfer and minimize ‘clutter’

  10. Minimize wasted space (e.g., origin does not need to be zero) • All elements on graph should convey information (e.g., avoid grid lines)

  11. Creating figures (bad vs good) • Fish Growth • Outside frame, border around graph • No legend for data points, red-green color blindness • Gridlines present, axes lines are grey • Fonts are too small, inappropriate decimal places • No units on axes labels • Figure title • Take-home lesson – Excel does not provide a good graph format, you have to do it yourself • MUCH BETTER!

  12. Effective captions are important for figures and tables • Provide context • Allow figure/table to stand on its own • Complete sentences • NO titles on figures! • Figure - weight of fish of different ages • Figure 1. Mass-at-age of walleye captured between 2002 and 2003 from lakes with stunted- and trophy-sized individuals. Why aren’t the dots connected with a line?

  13. Basic Rules • Independent variable (the one you control) is the x-axis; dependent (or response) variable is the y-axis • The type of data determines the type of graph, e.g.: • Time-series – usually a line graph • Two independent variables – x-y (scatterplot) • Percentages – pie-chart • Categorical independent variable – bar chart

  14. Basic Rules • Graphs do not have titles (except in talks) – they have a heading, below the graph

  15. Basic Rules • Graphs do not have titles (except in talks) – they have a heading, below the graph • Label the axes. Put units of measure on the axes (yrs, mm, percentage, etc.)

  16. Line or bar graph?

  17. Teixeira and Cortes 2006

  18. Pie charts compare components of a whole sample Madenjian et al. 2006

  19. Two independent variables – x-y plot

  20. Addition of years next to each data point aided in data interpretation (years that did not fit the curve were El Nino events that changed the stock-recruit dynamic of the pollock) • Bering Sea pollock • B. A. Megrey and V. G. Wespestad

  21. Comparison of treatments (dependent vs. independent variables)

  22. Creating Tables • Table 1. The size range and sample size of each fish species (with prey in stomachs) used in the 2005 (lakewide) and 2006 (western Lake Superior; WLS) selectivity analysis. “na” = not available. • From Isaac et al. (2012) • 24/10

  23. Creating Tables • Table 1. The size range and sample size of smelt with prey in stomachs used in the 2005 (lakewide) and 2006 (western Lake Superior; WLS) selectivity analysis. • These data do not justify a table. • From Isaac et al. (2012) • 25/10

  24. Creating tables • Bluegill • 142 • 14 • 29 • Yellow perch • 203 • 29 • 37 • Smallmouth bass • Juveniles • 157 • 19 • 31 • Adults • 423 • 339 • 18 • Northern pike • Juveniles • 278 • 21 • 14 • Adults • 613 • 638 • 8 • # fish • Mean • length • Mean • mass • Species/life-stage

  25. Creating tables • Bounded by thicker borders on top and bottom • Bluegill • 142 (± 42.3) • 14 (± 2.7) • 29 • Yellow perch • 203 (± 52.9) • 29 (± 3.6) • 37 • Smallmouth bass • Thinner border to set column headers apart from data • Juveniles • 157 (± 22.7) • 19 (± 1.2) • 31 • Adults • 423 (± 62.1) • 339 (± 32.5) • 18 • Northern pike • Juveniles • 278 (± 48.2) • 21 (± 3.3) • 14 • Adults • 613 (± 77.3) • 638 (± 62.7) • 8 • Mean • length (mm) • Mean • mass (g) • Species/life-stage • n • 27/10

  26. Creating tables • Clearly labeled column headers, with units, “n” is universal for “sample size” • Bounded by thicker borders on top and bottom • Bluegill • 142 (± 42.3) • 14 (± 2.7) • 29 • Yellow perch • 203 (± 52.9) • 29 (± 3.6) • 37 • Smallmouth bass • Thinner border to set column headers apart from data • Juveniles • 157 (± 22.7) • 19 (± 1.2) • 31 • Adults • 423 (± 62.1) • 339 (± 32.5) • 18 • Northern pike • Juveniles • 278 (± 48.2) • 21 (± 3.3) • 14 • Adults • 613 (± 77.3) • 638 (± 62.7) • 8 • Mean • length (mm) • Mean • mass (g) • Species/life-stage • n • Measure of variance, when appropriate • No borders separating columns or rows of data • 28/10

  27. Creating tables • Bluegill • 142 (± 42.3) • 14 (± 2.7) • 29 • Yellow perch • 203 (± 52.9) • 29 (± 3.6) • 37 • Smallmouth bass • Juveniles • 157 (± 22.7) • 19 (± 1.2) • 31 • Adults • 423 (± 62.1) • 339 (± 32.5) • 18 • Northern pike • All numbers are right-aligned in columns • Juveniles • 278 (± 48.2) • 21 (± 3.3) • 14 • Adults • 613 (± 77.3) • 638 (± 62.7) • 8 • Mean • length (mm) • Mean • mass (g) • Species/life-stage • n • 29/10

  28. Creating tables • Table 1. Mean lengths and mass of four fish species sampled in Lost Lake in 2015. Standard deviations are shown in parentheses. • Caption that identifies the types of data in the table, with time and place where they were collected. • Bluegill • 142 (± 42.3) • 14 (± 2.7) • 29 • Yellow perch • 203 (± 52.9) • 29 (± 3.6) • 37 • Smallmouth bass • Juveniles • 157 (± 22.7) • 19 (± 1.2) • 31 • Adults • 423 (± 62.1) • 339 (± 32.5) • 18 • Northern pike • Juveniles • 278 (± 48.2) • 21 (± 3.3) • 14 • Adults • 613 (± 77.3) • 638 (± 62.7) • 8 • Mean • length (mm) • Mean • mass (g) • Species/life-stage • n

  29. Use of multiple underlines to link and clarify headings • Table 1. The size range and sample size of each fish species (with prey in stomachs) used in the 2005 (lakewide) and 2006 (western Lake Superior; WLS) selectivity analysis. “na” = not available. • From Isaac et al. (2012)

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