R Dataset / Package DAAG / bomregions2011

How To Create a Barplot

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Description

Describes how to create a bar plot based on count data. For an example of count data, see the email50 curated data set which was taken from the Open Intro AHSS textbook (not affiliated). An example of count data in this dataset would be the spam column.

Usage

Select one (1) column to create its barplot and then click 'Submit'. If you do not choose count data, you may get unexpected results.

See Also

Students may also be interested in creating barplots for contingency tables.

For a stacked side-by-side barplot, see the other barplot app.

How To Create a Stacked Barplot

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Usage

Select 1 (one) column from a contingency table like the Gender and Politics or VADeaths curated datasets.

If you do not choose a contingency table, you may get unexpected results. You can import a dataset if you are logged-in.

Details

Shows the student how to create a single stacked bar plot based on a column in a contingency table.

See Also

For a basic barplot (single column) based on count data see the count data barplot app.

For a stacked side-by-side barplot see the other stacked barplot app for categorical data.

How To Create a Pie Chart

Webform

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The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
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Usage

Select 1 (one) column from a contingency table. If you don't have your own dataset, you can choose the Gender and Politics or VADeaths curated datasets. If a contingency table is not chosen, you may get unexpected results.

A contingency table has columns like a regular dataset, but the first row contains row names that categorize and "split-up" the dataset. An example of a contingency table would be something like this:

LIBERAL CONSERVATIVE
F 762 468
M 484 477

This contingency table is take from the Gender and Politics dataset. You can get a preview by selecting the dataset from the Curated Data dropdown above.

Details

This app shows the student how to create a pie chart from a contingency table by hand using a Quadstat dataset.

A pie chart shows proportions of a sample or population. Each piece of a pie chart corresponds to some subset of the sample or population. In this case, we will use the contingency table rows to subset the sample.

See Also

Students may also want to view the app for creating a pie chart from count data.

How To Compute the Mean

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Usage

Click "Submit" after selecting one column to see how to compute the arithmetic mean (average) of data (vectors).

Description

If all the values of a sample were plotted on a number line, the average would be the point in the middle that would balance the two sides.

The average is greatly influenced by outliers, meaning extreme points can pull the average to the left or right.

If we are referring to the average of population (all observations), the symbol for the average (arithmetic mean) is $\mu$.

If we are referring to the average of a sample (a subset of the population), the symbol for the average (arithmetic mean) is $\bar{x}$.

Computing the average

Suppose we have a sample consisting of $x_1, x_2, x_3,...,x_n$. This means we have $n$ observations. Then,

$$\bar{x}=\frac{x_1, x_2, x_3,...,x_n}{n}.$$

The formula tells us that we need to add all the observations and then divide by the number of observations to compute the mean.

Example 1

Compute the mean of $A = \{1,2,3\}$.

$$\bar{x} = \frac{1+2+3}{3} = 2.$$

How To Create a Plot

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Usage

Select two columns which are to be used in the scatterplot. The first column clicked will be the independent variable (X-axis).

Description

This web application describes how to create a scatterplot of two dataset variables plotted on the xy-axes.

How to Compute the Median

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Median Value

Description

Compute the sample median.

Usage

median(x, na.rm = FALSE, ...)

Arguments

x

an object for which a method has been defined, or a numeric vector containing the values whose median is to be computed.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

...

potentially further arguments for methods; not used in the default method.

Value

The default method returns a length-one object of the same type as x, except when x is logical or integer of even length, when the result will be double.

If there are no values or if na.rm = FALSE and there are NA values the result is NA of the same type as x (or more generally the result of x[FALSE][NA]).

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM

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Correlation Coefficient

Submitted by pmagunia on April 22, 2018 - 3:08 PM

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Cumulative Frequency Histogram

Submitted by pmagunia on April 22, 2018 - 3:09 PM

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Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM

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Hollow Histogram

Submitted by pmagunia on April 22, 2018 - 3:10 PM

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Mean

Submitted by pmagunia on April 22, 2018 - 3:11 PM

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Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM

Please see the full application for additional options and documentation.

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Plot

Submitted by pmagunia on April 22, 2018 - 3:07 PM

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Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

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Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM

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Summary

Submitted by pmagunia on April 22, 2018 - 2:51 PM

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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM

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Submitted by pmagunia on March 9, 2018 - 1:06 PM
Attachment Size
dataset-45040.csv 15.43 KB
Dataset License
GNU General Public License v2.0
Documentation

Australian and Related Historical Annual Climate Data, by region

Description

Australian regional temperature data, Australian regional rainfall data, and Annual SOI, are given for the years 1900-2008 or 1900-2011 or 1900-2012. The regional rainfall and temperature data are area-weighted averages for the respective regions. The Southern Oscillation Index (SOI) is the difference in barometric pressure at sea level between Tahiti and Darwin.

Usage

bomregions

Format

This data frame contains the following columns:

Year

Year

eastAVt

Eastern temperature

seAVt

Southeastern region average temperature (degrees C)

southAVt

Southern temperature

swAVt

Southwestern temperature

westAVt

Western temperature

northAVt

Northern temperature

mdbAVt

Murray-Darling basin temperature

auAVt

Australian average temperature, area-weighted mean

eastRain

Eastern rainfall

seRain

Southeast Australian annual rainfall (mm)

southRain

Southern rainfall

swRain

Southwest rainfall

westRain

Western rainfall

northRain

Northern rainfall

mdbRain

Murray-Darling basin rainfall

auRain

Australian average rainfall, area weighted

SOI

Annual average Southern Oscillation Index

co2mlo

Moana Loa CO2 concentrations, from 1959

co2law

Moana Loa CO2 concentrations, 1900 to 1978

CO2

CO2 concentrations, composite series

sunspot

Annual average sunspot counts

Source

Australian Bureau of Meteorology web pages:

http://www.bom.gov.au/climate/change/index.shtml

The CO2 series co2law, for Law Dome ice core data. is from http://cdiac.ornl.gov/trends/co2/lawdome.html.

The CO2 series co2mlo is from Dr. Pieter Tans, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends/)

The series CO2 is a composite series, obtained by adding 0.46 to he Law data for 1900 to 1958, then following this with the Moana Loa data that is avaiable from 1959. The addition of 0.46 is designed so that the averages from the two series agree for the period 1959 to 1968

Sunspot data is from http://sidc.oma.be/sunspot-data/

References

D.M. Etheridge, L.P. Steele, R.L. Langenfelds, R.J. Francey, J.-M. Barnola and V.I. Morgan, 1998, Historical CO2 records from the Law Dome DE08, DE08-2, and DSS ice cores, in Trends: A Compendium of Data on Global Change, on line at Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. http://cdiac.ornl.gov/trends/co2/lawdome.html

Lavery, B., Joung, G. and Nicholls, N. 1997. An extended high-quality historical rainfall dataset for Australia. Australian Meteorological Magazine, 46, 27-38.

Nicholls, N., Lavery, B., Frederiksen, C.\ and Drosdowsky, W. 1996. Recent apparent changes in relationships between the El Nino – southern oscillation and Australian rainfall and temperature. Geophysical Research Letters 23: 3357-3360.

SIDC-team, World Data Center for the Sunspot Index, Royal Observatory of Belgium, Monthly Report on the International Sunspot Number, online catalogue of the sunspot index: http://www.sidc.be/sunspot-data/, 1900-2011

Examples

plot(ts(bomregions[, c("mdbRain","SOI")], start=1900),
     panel=function(y,...)panel.smooth(bomregions$Year, y,...))
avrain <- bomregions[,"mdbRain"]
xbomsoi <- with(bomregions, data.frame(Year=Year, SOI=SOI,
                cuberootRain=avrain^0.33))
xbomsoi$trendSOI <- lowess(xbomsoi$SOI, f=0.1)$y
xbomsoi$trendRain <- lowess(xbomsoi$cuberootRain, f=0.1)$y
xbomsoi$detrendRain <-
  with(xbomsoi, cuberootRain - trendRain + mean(trendRain))
xbomsoi$detrendSOI <-
  with(xbomsoi, SOI - trendSOI + mean(trendSOI))
## Plot time series avrain and SOI: ts object xbomsoi
plot(ts(xbomsoi[, c("cuberootRain","SOI")], start=1900),
     panel=function(y,...)panel.smooth(xbomsoi$Year, y,...),
     xlab = "Year", main="", ylim=list(c(250, 800),c(-20,25)))
par(mfrow=c(1,2))
rainpos <- pretty(xbomsoi$cuberootRain^3, 6)
plot(cuberootRain ~ SOI, data = xbomsoi,
     ylab = "Rainfall (cube root scale)", yaxt="n")
axis(2, at = rainpos^0.33, labels=paste(rainpos))
mtext(side = 3, line = 0.8, "A", adj = -0.025)
with(xbomsoi, lines(lowess(cuberootRain ~ SOI, f=0.75)))
plot(detrendRain ~ detrendSOI, data = xbomsoi,
     xlab="Detrended SOI", ylab = "Detrended rainfall", yaxt="n")
axis(2, at = rainpos^0.33, labels=paste(rainpos))
with(xbomsoi, lines(lowess(detrendRain ~ detrendSOI, f=0.75)))
mtext(side = 3, line = 0.8, "B", adj = -0.025)
par(mfrow=c(1,1))
--

Dataset imported from https://www.r-project.org.

Documentation License
GNU General Public License v2.0

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