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#Fitplot instructions pdf
#Fitplot instructions manual

view: Shows a random selection of rows from a data frame or matrix.stat_SLR_equation: Add Regression Line Equation and R-Square to a ggplot.srsdf: Extract a simple random sample from a ame.SquareLakePopn: Biological characteristics of the "Square Lake" population.

#Fitplot instructions pdf

simDistrib: Demonstrates the shape of the PDF and CDF for the given.

#Fitplot instructions manual

sdCalc: Shows the steps in the manual calculation of the standard.residPlot: Construct a residual plot from lm or nls objects.reexports: Objects exported from other packages.: Modificaton of () to streamline output.print.lm: Modificaton of print.lm() to streamline output.print.htest: Modificaton of print.htest() to streamline output.predictionPlot: Shows the predicted value and interval on a fitted line plot.powerSim: Dynamic simulation of power calculation in 1-sample mean.plot.htest: Plots test statistic and p-value area for z-, t-, and.percTable: Express table entries as percentage of marginal table.NCStats-internals: Internal functions used in NCStats.

NCStats: Support for statistics classes at Northland College.

mrnorm: Multiple Simulations from Normal Distributions.

meanMedian: Dynamic simulations to demonstrate how the mean and median.

levenesTest: Perform Levene's test for homogeneity of variances.

knitUtil: Specific utilities for use in a knitr document.

iqrCalc: Shows the steps in the manual calculation of the median and.

identify.formula: Identify points in a plot using a formula.

highlight: Labels a list of points on a two-dimensional plot.

gofCI: Pseudo- confidence intervals for multinomial levels.

glhtSig: Extracts names for significantly different comparisons.

Frogs: Numbers of frogs on lakes as determined by call and visual.

filterD: Subsets/filters a data frame and drops the unused levels.

expandTable: Converts results in a contingency table into the original raw.

distrib: Plots calculated areas or values from a wide variety of.

corrSim: Dynamic simulations to demonstrate how the correlation is.

corr: Compute correlation coefficients.

cltSim: A dynamic graph to illustrate the Central Limit Theorem.

ci.t: Constructs confidence intervals assuming normal distribution.

ciSim: A dynamic graph to illustrate the concept of confidence.

chisqPostHoc: Tests for significant differences among all pairs of.

assumptionCheck: Graphics for assessing assumptions of simple linear models.adTest: Anderson-Darling test for normality.addSigLetters: Places significance letters next to mean points on a fitPlot.addMargins: Puts Arbitrary Margins on Two-way Tables or Arrays.accuracyPrecision: Plot targets and histograms for illustrating accuracy and.ABDLakes: Data for lakes in Ashland, Bayfield, and Douglas counties.ABCens90: Data on Ashland and Bayfield County (WI) residents in 1990.