Dashboard

Sticky Name Description
Contingency Table For Categorical Data
Provides a contingency table for a dataset or vector.
Correlation Coefficient
Compute the Pearson correlation coefficient of two or more variables.
Cumulative Frequency Histogram
This type of histogram shows cumulative (total) frequency achieved by each bin, rather than the frequency in that particular bin. Each bin will be of equal height or taller than the bin immediately preceeding it.
Dotplot
Create a dotchart (dotplot) based on a dataset vector
Hollow Histogram
Plots a hollow histogram as seen in the OpenIntro textbook Advanced High School Statistics
IQR
Computes the IQR (interquartile range.)
Normal Random Samples
Generate random samples from a Normal distribution with specified mean and standard deviation.
Pie Chart for Contingency Table

Pie Chart for Contingency Table

Creates a pie chart from a

Pie Chart for Count Data
Draws a pie chart for count data (as opposed to frequencies).
Proportions
Express table entries as fraction of marginal table
Name Authored by Filename File size Changed Authored on File MIME type
US Baby Names in 2015 admin dataset-47139.csv 510.53 KB March 28, 2017 - 9:04 PM March 25, 2017 - 6:31 PM text/csv
BOD admin dataset-93773.csv 53 bytes May 12, 2017 - 8:41 PM February 26, 2017 - 11:28 AM text/csv
CO2 admin dataset-23612.csv 3.14 KB May 12, 2017 - 8:42 PM February 26, 2017 - 11:28 AM text/csv
ChickWeight admin dataset-45458.csv 6.19 KB May 12, 2017 - 8:44 PM February 26, 2017 - 11:28 AM text/csv
DNase admin dataset-31941.csv 2.72 KB May 12, 2017 - 8:44 PM February 26, 2017 - 11:28 AM text/csv
EuStockMarkets admin dataset-62794.csv 51.44 KB May 12, 2017 - 8:45 PM February 26, 2017 - 11:28 AM text/csv
Formaldehyde admin dataset-34296.csv 76 bytes May 12, 2017 - 8:45 PM February 26, 2017 - 11:28 AM text/csv
HairEyeColor admin dataset-85766.csv 851 bytes May 12, 2017 - 8:45 PM February 26, 2017 - 11:28 AM text/csv
Indometh admin dataset-58856.csv 674 bytes May 12, 2017 - 8:46 PM February 26, 2017 - 11:28 AM text/csv
InsectSprays admin dataset-41513.csv 482 bytes May 12, 2017 - 8:46 PM February 26, 2017 - 11:28 AM text/csv

Recent Blog Content

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A Tale of Two Numbers: Kindergarten Math On College Software

How to add two numbers in SAS, Quadstat, and R. This doesn't have too much to do with statistics just yet.

May 8, 2017 - 3:41 AM admin
Setting Up With SAS Statistical Software

Setup SAS University to follow along with the Statistics textbook OpenIntro.

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Setting Up With R

How to setup your computer to follow along with R.

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Using Quadstat With OpenIntro's Advanced High School Statistics

This book describes how to use Quadstat statistical software with the OpenIntro textbook Advanced High School Statistics.

May 7, 2017 - 6:39 PM admin

Recent Queries

VariableValue
Image
RX <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-47806.csv", sep=",", header = TRUE);
dfr <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-47806.csv", sep=",", header = TRUE);
colNam <- colnames(X);
X <- cbind(X[,6], X[,5]);
colnames(X) <- c(colNam[6], colNam[5]);
dfr <- as.data.frame(c(dfr[6], dfr[5]))
png(file = "/tmp/operation-92215-%01d.png", bg = "transparent");
plot(X)
dev.off();
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VariableValue
Output outcome
group no event stroke
control 214 13
treatment 191 33
RX <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-61804.csv", sep=",", header = TRUE);
dfr <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-61804.csv", sep=",", header = TRUE);
colNam <- colnames(X);
X <- cbind(X);
colnames(X) <- colNam;
table(dfr);

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Select entire datasetYes
VariableValue
Output [1] -0.30815060 0.06610493 -0.11274762 -1.05188619 3.27955279 0.12951645 0.99745465 0.94337586 -0.03209745 -2.09442703 0.73925104 -0.47267894 -0.47218781 -1.03952037 0.13189299 0.71206430
[17] -0.01135115 0.56430784 -0.30442590 0.59433873 -0.93026200 0.24294524 -1.13328775 -0.15281440 0.56011136 1.35363143 -0.30841586 1.15735852 0.03356956 -0.41124478 -0.59582664 0.05185727
[33] -0.83087769 -0.21360416 0.29766827 1.70871383 -0.48319272 -0.46048093 -0.89340071 -0.13826972 -0.35387765 -0.54194896 -1.75584679 -0.40804427 0.49077650 1.22882119 -0.69810355 -0.98621292
[49] 0.19429406 -0.11401204 0.32603019 0.40337629 0.85507948 -1.79249974 1.32642676 -1.83109175 -0.68383922 -2.21777014 -1.72491774 0.63400882 -1.34837227 0.91944384 -0.80010288 -0.74454029
[65] 1.21513919 0.13109634 -0.76643761 -0.09392543 1.33136158 0.01855151 1.28611750 0.69765595 2.07996793 -0.78549161 -2.14943879 -0.63950197 -1.44761003 -0.70779934 -0.14699093 -0.44857142
[81] -1.12631800 -0.56333920 1.91673296 1.42208999 -0.08537054 -0.88799365 -1.68911700 2.79820445 -0.78511684 -0.91761507 0.20654202 0.02910560 0.28431086 -0.56454923 1.02122966 0.66470061
[97] -1.66041765 -0.03822494 0.69760399 -0.34487893
Rrnorm(100, 0, 1);
n100
Mean0
Standard deviation1
VariableValue
image
Outputy = -0.117 x + 10.5136

p-value: 0.20244231

RX <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-41414.csv", sep=",", header = TRUE);
dfr <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-41414.csv", sep=",", header = TRUE);
colNam <- colnames(X);
X <- cbind(X[,3], X[,1]);
colnames(X) <- c(colNam[3], colNam[1]);
dfr <- as.data.frame(c(dfr[3], dfr[1]))
png(file = "/tmp/operation-83521-%01d.png", bg = "transparent");
l <- lm(X[,1] ~ X[,2], dfr);
writeLines(paste("y = ", round(l$coefficients[2], digits = 4),"x + ", round(l$coefficients[1], digits = 4)));
f <- summary(l)$fstatistic;
p <- pf(f[1],f[2],f[3],lower.tail=F);
writeLines(paste("\np-value: ", round(p, digits = 8),"\n\n"));
plot(dfr[,2], dfr[,1], xlab = colnames(dfr)[2], ylab = colnames(dfr)[1]);
abline(l);
dev.off();
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VariableValue
Output airline
Min. : 1.00
1st Qu.:14.75
Median :28.50
Mean :28.50
3rd Qu.:42.25
Max. :56.00


[1] IQR: 27.5


[1] Mean: 28.5
[1] Stanard deviation: 16.3095064303001
[1] Variance: 266


breaks Freq cumFreq relative
1 (0.945,8.86] 8 8 0.1428571
2 (8.86,16.7] 8 16 0.1428571
3 (16.7,24.6] 8 24 0.1428571
4 (24.6,32.4] 8 32 0.1428571
5 (32.4,40.3] 8 40 0.1428571
6 (40.3,48.1] 8 48 0.1428571
7 (48.1,56.1] 8 56 0.1428571



The decimal point is 1 digit(s) to the right of the |

0 | 123456789
1 | 0123456789
2 | 0123456789
3 | 0123456789
4 | 0123456789
5 | 0123456

RX <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-41414.csv", sep=",", header = TRUE);
dfr <- read.table("https://quadstat.com/system/files/datasets/admin/dataset-41414.csv", sep=",", header = TRUE);
colNam <- colnames(X);
X <- cbind(X[,1]);
colnames(X) <- c(colNam[1]);
dfr <- as.data.frame(c(dfr[1]))
print(summary(X));
writeLines("\n");
print(noquote(paste("IQR: ", IQR(X))));
writeLines("\n");
print(noquote(paste("Mean: ", mean(X))));
print(noquote(paste("Stanard deviation: ", sd(X))));
print(noquote(paste("Variance: ", var(X))));
writeLines("\n");
breaks <- factor(cut(X, breaks = nclass.Sturges(X)))
xout <- as.data.frame(table(breaks))
xout <- transform(xout, cumFreq = cumsum(Freq), relative = prop.table(Freq))
print(xout)
writeLines("\n");
stem(X);
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