Biostatistics I: Inference

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Biostatistics I: Inference

Orinal Author Antoine Soetewey

Modifications by Nicholas Kaukis

Inference for:

one mean

Sample Mean:

$\overline{x} =$

sample Size:

$n =$

Population standard deviation

$\sigma$ known

$\sigma =$

Sample Standard Deviation:

$s$

Differences sample mean:

$\overline{x}_D =$

Differences Sample Size:

$n_D =$

Differences population standard deviation

$\sigma_D$ known

$\sigma_D =$

Differences sample standard deviation:

$s_D$

$\overline{x}_1 =$

$n_1$

$\overline{x}_2 =$

$n_2$

Population standardard deviations known.

$s_1$

$s_2$

Assuming

$\sigma_1 = \sigma_2$

$\sigma_1 \neq \sigma_2$

$\sigma_1 =$

$\sigma_2 =$

Sample size

$n =$

Proportion of success

$\hat{p}$

Number of successes

$x$

Proportion of success

$\hat{p} =$

Number of successes

$x =$

Sample size 1

$n_1 =$

Sample size 2

$n_2 =$

Proportion of success

$\hat{p}$

Number of successes

$x$

Proportion of success

$\hat{p}_1 =$

$\hat{p}_2 =$

Number of successes

$x_1 =$

$x_2 =$

Null hypothesis

$H_0 : \mu =$

$H_0 : \mu_1 - \mu_2 =$

$H_0 : \mu_D =$

$H_0 : p =$

$H_0 : p_1 - p_2 =$

Alternative

$\neq$

$>$

$<$

Significance level

$\alpha =$ 0.0010.1000.050.0010.0110.0210.0310.0410.0510.0610.0710.0810.0910.1