Sampling Distributions

It guarantees an absolutely accurate representation due directly correlating increased numbers understanding concepts.

It ensures that every possible subset combination will be represented within her surveyed group

It reduces variability and thus tightens confidence intervals around estimated proportions leading towards greater precision and potentially accuracy if unbiased.

It results invariably correct estimates since bigger samples eliminate all forms bias or distortion inherently present within any set data points.

The standard deviation is halved.

The standard deviation remains unchanged.

The standard deviation doubles.

The standard deviation is multiplied by four.

Stratified Random Sampling

Systematic Sampling

Simple Random Sampling

Cluster Sampling

$\sqrt{\frac{p^2(n-1)}{n+1}}$

$p(1-p)\sqrt{n}$

$\sqrt{\frac{p(1-p)}{n}}$

$\sqrt{np(1-p)}$

Stratified Random Sampling

Simple Random Sampling

Convenience Sampling

Systematic Sampling

0.15

0.25

0.10

0.20

Random sampling

Sampling all members of the population

Census

Conducting an experiment

50

20

80

40

The fixed number of independent trials in an experiment.

The specific value order sequence of successes and failures in trials.

Only two possible outcomes for each trial (success or failure).

The probability of success being constant for each trial.

The margin of error.

The sample proportion.

The standard error.

The population proportion.