When should I use an I-MR chart instead of an X̄-R chart?

Use I-MR when you get one value per sampling point — a batch, a lab result, a daily figure — or when readings close together would not be independent. Use X̄-R when you can take a small rational subgroup of 2 to 9 readings at each point.

What is the difference between a p chart and an np chart?

Both chart defective units. The p chart plots the fraction defective and handles varying sample sizes; the np chart plots the number defective and needs a constant sample size. With a constant n they give identical signals.

What is the difference between a c chart and a u chart?

Both chart defects (flaws), not defective units. The c chart plots the count per sample and needs the same amount of product inspected each time; the u chart plots defects per unit and handles a varying amount.

When should I use an X̄-S chart instead of X̄-R?

When subgroups have 10 or more readings, or whenever software is doing the arithmetic. The standard deviation uses every reading in the subgroup; the range uses only two.

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Which Control Chart Should I Use? — Answer Four Questions

Measurements or counts, subgroup size, constant or varying sample size, and whether small shifts matter: four answers pick between I-MR, X̄-R, X̄-S, p, np, c, u, EWMA and CUSUM, with the reason and a link straight to the chart.

1. What are you recording?

2. How many readings per sample?

3. Do small, slow drifts matter most?

Use the

X̄-R chart

Subgroups of 2 to 9 readings taken close together. At these sizes the range is nearly as efficient as the standard deviation, and it is what most shop-floor sheets are written for.

Open the X̄-R chart

Also consider

X̄-S chartIf software is doing the arithmetic anyway: the standard deviation uses every reading, and is slightly more efficient even at n = 5.

The whole decision on one table

Control chart selection by data type and sample structure
Chart	Data	Sample	Plots	Distribution
I-MR	Measurement	One value per point	Individual values and moving ranges	Normal
X̄-R	Measurement	Subgroups of 2–9	Subgroup averages and ranges	Normal
X̄-S	Measurement	Subgroups of 10+	Subgroup averages and std. deviations	Normal
p	Defective items	Any sample size	Fraction defective	Binomial
np	Defective items	Constant sample size	Number defective	Binomial
c	Defects	Constant inspection area	Defects per sample	Poisson
u	Defects	Varying inspection area	Defects per unit	Poisson
EWMA	Measurement	Individuals or averages	Weighted moving average	Normal
CUSUM	Measurement	Individuals or averages	Cumulative deviation from target	Normal

Not sure the limits will be right yet? Start with a run chart, which needs no limits at all. Already have X̿ and R̄, or p̄ and n? The control limits calculator turns them into UCL and LCL directly.

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Variables data or attribute data?

Variables data is measured on a continuous scale: a diameter, a weight, a temperature, a cycle time. Attribute data is counted: how many parts failed, how many scratches on a panel. Measurements carry far more information per reading, so where a characteristic can be measured, a variables chart will detect a change with fewer samples.

Attribute data splits again. A defective is a unit that fails — it either does or it does not, so the count follows a binomial distribution and goes on a p or np chart. A defect is a flaw, and one unit can have several, so the count follows a Poisson distribution and goes on a c or u chart. Choosing the wrong pair gives the wrong limits.

Rational subgroups

A subgroup should be a handful of readings taken so close together that only common-cause variation can act within it — five consecutive parts off one spindle, not five parts gathered across a shift. The within-subgroup variation then sets the limits, and anything that changes between subgroups shows up as a signal. If you can only get one reading at a time (a batch, a daily lab result), that is what the individuals chart is for.

Shewhart, or time-weighted?

Shewhart charts — every chart in the table except EWMA and CUSUM — are quick to react to a large, sudden change and slow to notice a small, sustained one. When the shifts that matter are under about 1.5σ, an EWMA or CUSUM chart detects them in a fraction of the samples. They are harder to explain on the shop floor, so many sites run them alongside a Shewhart chart rather than instead of one.

Common questions

When should I use an I-MR chart instead of an X̄-R chart?: Use I-MR when you get one value per sampling point — a batch, a lab result, a daily figure — or when readings close together would not be independent. Use X̄-R when you can take a small rational subgroup of 2 to 9 readings at each point.
What is the difference between a p chart and an np chart?: Both chart defective units. The p chart plots the fraction defective and handles varying sample sizes; the np chart plots the number defective and needs a constant sample size. With a constant n they give identical signals.
What is the difference between a c chart and a u chart?: Both chart defects (flaws), not defective units. The c chart plots the count per sample and needs the same amount of product inspected each time; the u chart plots defects per unit and handles a varying amount.
When should I use an X̄-S chart instead of X̄-R?: When subgroups have 10 or more readings, or whenever software is doing the arithmetic. The standard deviation uses every reading in the subgroup; the range uses only two.