freeny

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Attachment	Size
dataset-41301.csv	1.58 KB

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Documentation
Freeny's Revenue Data Freeny's data on quarterly revenue and explanatory variables. Usage freeny freeny.x freeny.y Format There are three ‘freeny’ data sets. `freeny.y` is a time series with 39 observations on quarterly revenue from (1962,2Q) to (1971,4Q). `freeny.x` is a matrix of explanatory variables. The columns are `freeny.y` lagged 1 quarter, price index, income level, and market potential. Finally, `freeny` is a data frame with variables `y`, `lag.quarterly.revenue`, `price.index`, `income.level`, and `market.potential` obtained from the above two data objects. Source A. E. Freeny (1977) A Portable Linear Regression Package with Test Programs. Bell Laboratories memorandum. References Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole. Examples require(stats); require(graphics) summary(freeny) pairs(freeny, main = "freeny data") # gives warning: freeny$y has class "ts" summary(fm1 <- lm(y ~ ., data = freeny)) opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0), mar = c(4.1, 4.1, 2.1, 1.1)) plot(fm1) par(opar)

Freeny's Revenue Data

Freeny's data on quarterly revenue and explanatory variables.

Usage

freeny
freeny.x
freeny.y

Format

There are three ‘freeny’ data sets.

freeny.y is a time series with 39 observations on quarterly revenue from (1962,2Q) to (1971,4Q).

freeny.x is a matrix of explanatory variables. The columns are freeny.y lagged 1 quarter, price index, income level, and market potential.

Finally, freeny is a data frame with variables y, lag.quarterly.revenue, price.index, income.level, and market.potential obtained from the above two data objects.

Source

A. E. Freeny (1977) A Portable Linear Regression Package with Test Programs. Bell Laboratories memorandum.

References

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

Examples

require(stats); require(graphics)
summary(freeny)
pairs(freeny, main = "freeny data")
# gives warning: freeny$y has class "ts"

summary(fm1 <- lm(y ~ ., data = freeny))
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
            mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)
par(opar)

Curated Data	File Size
OpenIntro Statistics Dataset - yrbss_samp	7.62 KB
OpenIntro Statistics Dataset - yrbss	1.03 MB
OpenIntro Statistics Dataset - yawn	861 bytes
OpenIntro Statistics Dataset - xom	4.95 KB
OpenIntro Statistics Dataset - winery_cars	489 bytes

All Public Datasets	File Size
PSID
wage1	328 bytes
OpenIntro Statistics Dataset - yrbss_samp	7.62 KB
OpenIntro Statistics Dataset - yrbss	1.03 MB
OpenIntro Statistics Dataset - yawn	861 bytes

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Recent Queries	App/Dataset	By	Date
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Picostat Output - Visual Summaries	R Dataset / Package datasets / esoph	hyi2	October 29, 2020 - 5:42 AM
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Picostat Output - Visual Summaries	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:17 PM

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freeny

How To Create a Barplot

How To Create a Stacked Barplot

How To Create a Pie Chart

How To Compute the Mean

How To Create a Plot

How to Compute the Median

Boxplot

Correlation Coefficient

Cumulative Frequency Histogram

Dotplot

Hollow Histogram

Numerical Summaries

Pie Chart

Plot

Regression

Stem and Leaf Plots

Visual Summaries

Freeny's Revenue Data

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