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Formula Review

Central limit theorem for sample means: $\bar{X}$ ~ N $(μ_{x}, \frac{σ x}{\sqrt{n}})$

Mean $\bar{X}$ : μ_x

Central limit theorem for sample means z-score and standard error of the mean: $z = \frac{\bar{x} - μ_{x}}{(\frac{σ_{x}}{\sqrt{n}})}$

Standard error of the mean (standard deviation ( $\bar{X}$ )): $\frac{σ_{x}}{\sqrt{n}}$

Central limit theorem for sums: ∑X ~ N[(n)(μ_x),( $\sqrt{n}$ )(σ_x)]

Mean for sums (∑X): (n)(μ_x)

Central limit theorem for sums z-score and standard deviation for sums: $z for the sample mean = \frac{Σ x - (n) (μ_{X})}{(\sqrt{n}) (σ_{X})}$

Standard deviation for sums (∑X): $(\sqrt{n})$ (σ_x)