R Dataset / Package datasets / JohnsonJohnson
Attachment | Size |
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dataset-35863.csv | 1 KB |
Documentation |
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On this Picostat.com statistics page, you will find information about the JohnsonJohnson data set which pertains to Quarterly Earnings per Johnson & Johnson Share. The JohnsonJohnson data set is found in the datasets R package. Try to load the JohnsonJohnson data set in R by issuing the following command at the console data("JohnsonJohnson"). This may load the data into a variable called JohnsonJohnson. If R says the JohnsonJohnson data set is not found, you can try installing the package by issuing this command install.packages("datasets") and then attempt to reload the data with library("datasets") followed by data("JohnsonJohnson"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing JohnsonJohnson at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the JohnsonJohnson R data set. The size of this file is about 1,027 bytes. Quarterly Earnings per Johnson & Johnson ShareDescriptionQuarterly earnings (dollars) per Johnson & Johnson share 1960–80. UsageJohnsonJohnson FormatA quarterly time series SourceShumway, R. H. and Stoffer, D. S. (2000) Time Series Analysis and its Applications. Second Edition. Springer. Example 1.1. Examplesrequire(stats); require(graphics) JJ <- log10(JohnsonJohnson) plot(JJ) ## This example gives a possible-non-convergence warning on some ## platforms, but does seem to converge on x86 Linux and Windows. (fit <- StructTS(JJ, type = "BSM")) tsdiag(fit) sm <- tsSmooth(fit) plot(cbind(JJ, sm[, 1], sm[, 3]-0.5), plot.type = "single", col = c("black", "green", "blue")) abline(h = -0.5, col = "grey60")monthplot(fit) -- Dataset imported from https://www.r-project.org. |
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R Output | Date |
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Picostat Output - Boxplot | Jun 27, 2020 |
Picostat Output - Boxplot | Jun 27, 2020 |
Picostat Output - Boxplot | Jun 27, 2020 |
Picostat Output - Numerical Summaries | Apr 29, 2020 |
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