Sampling Techniques and Statistical Analysis Review

Flashcards on probability and statistics concepts discussed in lectures, focusing on sampling techniques.

Inclusion Probability

The probability of picking a specific member from a population sample.

T-Critical Value

A value grabbed from a probability distribution for a given degrees of freedom.

Simple Random Sampling

A sampling technique where each member of the population has an equal chance of being selected.

Stratified Random Sampling

Technique that divides a population into subgroups before sampling.

Weight

Factor used to adjust individual data points based on their relative importance.

Representative Sampling

The idea that the sample taken must represent the population

Substrata

Subgroups within a population used in stratified random sampling.

Mutually Exclusive

A rule of strata where every sample belongs to exactly one stratum.

Collectively Exhaustive

Means all possible samples from the population are included.

Weighted Mean Value

A method of getting individual stats from each stratum and consolidation into one value that represents all.

Pooled Mean

A mean value that is calculated based on stratum weight.

Pooled Standard Error

A standard error that has a weight and a square.

Stratum Weight

The weight assigned based on how much it represents the whole population.

Variance

The sum of weighted variances from each stratum.

Degrees of Freedom

The freedom to randomize things and then freedom to not randomize things.

T Crit Value

The value used to sample from the same table to get that fixed value.

Covariance

How two measurements relate to each other.

Paired Approach

Using a same site to monitor measurements.

Independent Approach

Using a different site to monitor measurements.

Sampling Efficiency

Ratio of variances in sampling techniques.