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Comparative Analysis of Biscuit Types and Vital Statistics through Graphical Representation

This report presents graphical displays of line graphs comparing multiple biscuit types based on depth. Cumulative graphs are utilized for comparing different distributions, illustrating the characteristics of various corn and biscuit types (Type I, Type II in red, yellow, gray, and Type III). Additionally, vital statistics such as birth rates and life expectancy are included, revealing trends in countries like China, India, the United States, Indonesia, and Brazil. The analysis employs scatterplots and bubble plots to further investigate the relationships among relevant variables and enhance data interpretation.

sarah-mcknight
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Comparative Analysis of Biscuit Types and Vital Statistics through Graphical Representation

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  1. Graphical Display 2 Pictures of Data

  2. Line Graphs • At least two variables, x is often time or depth while the other(s) are plotted for comparison • Cumulative graphs allow comparison of two or more distributions (Quantile comparison plot)

  3. > Nelson Depth Corrugated Biscuit Type_IType_II_RedType_II_YellowType_II_GrayType_III 1 1 57 10 2 24 23 34 5 2 2 116 17 2 64 90 76 6 3 3 27 2 10 68 18 48 3 4 4 28 4 6 52 20 21 0 5 5 60 15 2 128 55 85 0 6 6 75 21 8 192 53 52 1 7 7 53 10 40 91 20 15 0 8 8 56 2 118 45 1 5 0 9 9 93 1 107 3 0 0 0 10 10 84 1 69 0 0 0 0 > NelsonPct <- data.frame(Nelson[,1:2], prop.table(as.matrix(Nelson[,3:8]),1)*100) > NelsonPct Depth Corrugated Biscuit Type_IType_II_RedType_II_YellowType_II_GrayType_III 1 1 57 10.2040816 2.0408163 24.489796 23.4693878 34.693878 5.1020408 2 2 116 6.6666667 0.7843137 25.098039 35.2941176 29.803922 2.3529412 3 3 27 1.3422819 6.7114094 45.637584 12.0805369 32.214765 2.0134228 4 4 28 3.8834951 5.8252427 50.485437 19.4174757 20.388350 0.0000000 5 5 60 5.2631579 0.7017544 44.912281 19.2982456 29.824561 0.0000000 6 6 75 6.4220183 2.4464832 58.715596 16.2079511 15.902141 0.3058104 7 7 53 5.6818182 22.7272727 51.704545 11.3636364 8.522727 0.0000000 8 8 56 1.1695906 69.0058480 26.315789 0.5847953 2.923977 0.0000000 9 9 93 0.9009009 96.3963964 2.702703 0.0000000 0.000000 0.0000000 10 10 84 1.4285714 98.5714286 0.000000 0.0000000 0.000000 0.0000000

  4. # Vital Stats - Crude Birth Rate, Crude Death Rate, Expectancy of # Life at Birth", Infant Mortality, and Total Fertility # Rate from 2000 to 2010 top5 <- c("China", "India", "United States", "Indonesia", "Brazil") Top5<-VitalStats[VitalStats$Country %in% top5, c(substr(colnames(VitalStats), 1, 3) %in% c("IMR", "Cou"))] rownames(Top5) <- Top5$Country Top5$Country <- NULL Top5IMR <- t(Top5) Year <- as.numeric(substr(rownames(Top5IMR), 4, 7)) Top5IMR <- data.frame(Year, Top5IMR) rownames(Top5IMR) <- 1:9 Top5IMR Year United.States Brazil China India Indonesia 1 2000 7.0 35.2 30.3 54.9 40.9 2 2001 7.0 34.0 28.9 51.5 39.5 3 2002 6.9 32.9 27.7 48.2 38.2 4 2003 6.8 31.7 26.4 45.2 36.9 5 2004 6.6 30.7 25.3 42.4 36.4 6 2005 6.5 29.6 24.2 39.7 34.5 7 2006 6.4 28.6 23.1 37.1 33.3 8 2007 6.4 27.6 22.1 34.6 32.1 9 2010 6.2 24.9 19.4 28.1 28.9

  5. Quantile comparison plot

  6. Scatterplot – XY Plot • Two interval/ratio variables • Smoothed and regression lines, linear and non-linear relationships • Compare groups (ellipses) • Label points (outliers) • Scatterplot matrix to compare more than two variables

  7. Scatterplot • Numerous options. Turn off all options on the menus, but select “Plot by groups” and select Name • Insert three options into the command: • legend.coords=“topleft” • ellipse=TRUE • levels=.95

  8. ScatterplotMatix • This gives you a visual display of a correlation matrix between three or more variables • Default puts a kernel density plot in the diagonal with a rug showing the data points • For values: by(DartPoints[,6:8], DartPoints$Name, rcorr.adjust)

  9. > library(Rcmdr) > by(DartPoints[,6:8], DartPoints$Name, rcorr.adjust) DartPoints$Name: Darl Length Width Thick Length 1.00 0.59 0.64 Width 0.59 1.00 0.49 Thick 0.64 0.49 1.00 n= 27 P Length Width Thick Length 0.0013 0.0003 Width 0.0013 0.0095 Thick 0.0003 0.0095 Adjusted p-values (Holm's method) Length Width Thick Length 0.0026 0.0009 Width 0.0026 0.0095 Thick 0.0009 0.0095

  10. ------------------------------------------------------------ DartPoints$Name: Pedernales Length Width Thick Length 1.00 0.40 0.52 Width 0.40 1.00 0.15 Thick 0.52 0.15 1.00 n= 28 P Length Width Thick Length 0.0365 0.0042 Width 0.0365 0.4611 Thick 0.0042 0.4611 Adjusted p-values (Holm's method) Length Width Thick Length 0.0731 0.0126 Width 0.0731 0.4611 Thick 0.0126 0.4611

  11. 3D Scatterplots • Three interval/ratio variables and a possible grouping variable • Often difficult to interpret • Experiment with rotation and view angle • Consider dropping pins to the floor • scatter3d (car) • scatterplot3d (scatterplot3d)

  12. with(DartPoints, scatterplot3d(Length, Width, Thick))

  13. with(DartPoints, scatterplot3d(Length, Width, Thick, type="h"))

  14. Bubble Plot • Bubble plots are scatterplots in which the size of the symbol reflects a third dimension • with(DartPoints, symbols(Length, Width, circles=Thick, inches=1/6, fg="blue", bg="blue")) • ? symbols for more details on the variety of plots possible

  15. > with(DartPoints, symbols(Length, Width, circles=Thick, inches=1/6, fg="blue", bg="blue")) > symbols(c(26, 26), c(35, 33), circles=c(4, 12), inches=1/6, fg="blue", bg="blue", add=TRUE) > text(c(28, 28), c(35, 33), c("Thickness = 4 mm", "Thickness = 12 mm"), pos=4) Create the plot Add circles of min and max size to upper left Add text labels

  16. Publication Quality • In Windows, you can generally save a graph in several formats or place it in the clipboard • For control over resolution and size, plot to a device • Use ?Devices to get the ones available

  17. E.g. Postscript • postscript(file="graph.ps") • plot(rnorm(25), rnorm(25)) • dev.off()

  18. E.g. tif • tiff(file="graph.tif", width=1500, height=1500, res=300, compression="lzw") • plot(rnorm(25), rnorm(25), las=1) • dev.off()

  19. Cairo • Package Cairo gives you access to additional graphic formats including svg as well as some options that are not available in the standard graphics devices.

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