Data
PromptBeginner5 minmarkdownQuality: 22
fitaov <- aov(outcomevar ~ group_var
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 22
abline(lm(outcome_var ~ predictor
data = df)
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Data
PromptBeginner5 minmarkdownQuality: 22
df <- read.csv(your_data.csv
stringsAsFactors = FALSE)
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Data
PromptBeginner5 minmarkdownQuality: 22
- Formula interface: `pairs(~ var1 + var2 + var3
data = df)`.
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Data
PromptBeginner5 minmarkdownQuality: 22
- Formula interface: `cor.test(~ x + y
data = df) — note the ~` with no LHS.
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Data
PromptBeginner5 minmarkdownQuality: 26
- Default bandwidth: bw = nrd0 (Silverman's rule of thumb). For multimodal data
consider SJ or bcv.
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Data
PromptBeginner5 minmarkdownQuality: 26
- Default kernel: gaussian. Range of density extends beyond data range (controlled by cut
default 3 bandwidths).
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Data
PromptBeginner5 minmarkdownQuality: 22
- Returns a matrix of p-values
not test statistics.
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Data
PromptBeginner5 minmarkdownQuality: 26
- 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: 26
- If data fits too exactly (no residual noise)
convergence check fails — use control = list(scaleOffset = 1) or jitter data.
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Data
PromptBeginner5 minmarkdownQuality: 22
- Returns data frame with size
isdir
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Data
PromptBeginner5 minmarkdownQuality: 22
- Formula interface (`aggregate(y ~ x
data
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Data
PromptBeginner5 minmarkdownQuality: 22
- If FUN returns multiple values
result column is a matrix column inside the data frame.
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Data
PromptBeginner5 minmarkdownQuality: 22
- For data frames
operates on whole rows. For lists
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Data
PromptBeginner5 minmarkdownQuality: 26
- 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: 22
- rbind on data frames matches columns by name
not position. Missing columns get NA.
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Data
PromptBeginner5 minmarkdownQuality: 26
- 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: 26
- 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: 26
- 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: 26
- On a data frame
apply coerces to matrix via as.matrix first — mixed types become character.
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Data
PromptBeginner5 minmarkdownQuality: 26
- 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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Data
PromptBeginner5 minmarkdownQuality: 26
- Data frame [ with single column: `df[
1]` returns a vector (drop=TRUE default for columns)
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Data
PromptBeginner5 minmarkdownQuality: 22
- Matrix indexing a data frame (`df[cbind(i
j)]`) coerces to matrix first — avoid.
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Data
PromptBeginner5 minmarkdownQuality: 22
- `ts(data
start
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