Data
PromptBeginner5 minmarkdownQuality: 24
df <- read.csv(your_data.csv
stringsAsFactors = FALSE)
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Data
PromptBeginner5 minmarkdownQuality: 24
- Formula interface: `pairs(~ var1 + var2 + var3
data = df)`.
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Data
PromptBeginner5 minmarkdownQuality: 24
- Formula interface: `cor.test(~ x + y
data = df) — note the ~` with no LHS.
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Data
PromptBeginner5 minmarkdownQuality: 28
- Default kernel: gaussian. Range of density extends beyond data range (controlled by cut
default 3 bandwidths).
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Data
PromptBeginner5 minmarkdownQuality: 28
- Default bandwidth: bw = nrd0 (Silverman's rule of thumb). For multimodal data
consider SJ or bcv.
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Creative
PromptBeginner5 minmarkdownQuality: 24
- nstart > 1 recommended (e.g.
nstart = 25): runs algorithm from multiple random starts
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Data
PromptBeginner5 minmarkdownQuality: 24
- Returns a matrix of p-values
not test statistics.
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Data
PromptBeginner5 minmarkdownQuality: 28
- For composite hypotheses (parameters estimated from data)
p-values are conservative (too large). Use dgof or ks.test with exact = NULL for discrete distributions.
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Data
PromptBeginner5 minmarkdownQuality: 28
- If data fits too exactly (no residual noise)
convergence check fails — use control = list(scaleOffset = 1) or jitter data.
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Creative
PromptBeginner5 minmarkdownQuality: 28
- aov is a wrapper around lm that stores extra info for balanced ANOVA. For unbalanced designs
Type I SS (sequential) are computed — order of terms matters.
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Creative
PromptBeginner5 minmarkdownQuality: 24
- Self-starting models (SSlogis
SSasymp
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Creative
PromptBeginner5 minmarkdownQuality: 28
- model.matrix creates the design matrix including dummy coding. Default contrasts: contr.treatment...
contr.poly for ordered.
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Creative
PromptBeginner5 minmarkdownQuality: 24
- `substr(x
start
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Data
PromptBeginner5 minmarkdownQuality: 24
- Returns data frame with size
isdir
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Data
PromptBeginner5 minmarkdownQuality: 24
- If FUN returns multiple values
result column is a matrix column inside the data frame.
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Data
PromptBeginner5 minmarkdownQuality: 24
- Formula interface (`aggregate(y ~ x
data
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Data
PromptBeginner5 minmarkdownQuality: 24
- For data frames
operates on whole rows. For lists
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Data
PromptBeginner5 minmarkdownQuality: 28
- Result is always an array (even 1D)
class table. Convert to data frame with as.data.frame(tbl).
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Data
PromptBeginner5 minmarkdownQuality: 24
- rbind on data frames matches columns by name
not position. Missing columns get NA.
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Data
PromptBeginner5 minmarkdownQuality: 28
- cbind on data frames calls data.frame(...)
not cbind.matrix. Mixing matrices and data frames can give unexpected results.
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Data
PromptBeginner5 minmarkdownQuality: 28
- Default by is `intersect(names(x)
names(y))` — can silently merge on unintended columns if data frames share column names.
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Data
PromptBeginner5 minmarkdownQuality: 28
- Returns an array (not a data frame). Class info on return values is discarded (e.g.
Date objects become numeric).
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Data
PromptBeginner5 minmarkdownQuality: 28
- On a data frame
apply coerces to matrix via as.matrix first — mixed types become character.
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Data
PromptBeginner5 minmarkdownQuality: 28
- subset argument uses non-standard evaluation — column names are resolved in the data frame
which can silently pick up wrong variables in programmatic use. Use [ with explicit logic in functions.
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