Statistics

What is sampling

the process of selecting a sample from a population of interest

Simple Random Sampling (SRS)

Select elements randomly from the population and each member has an equal chance

Stratified Random Sampling

A way to make sure that the sample represents the population in some relevant dimension Ex: Men and women

What are the forms of random sampling

Simple Random Sampling and Stratified Random Sampling

What is Nonrandom sampling or subject to bias sampling

Convenience, Volunteer, and Snowball

Convenience Sampling

select individuals who are available/handy Ex: College

Volunteer Sampling

Participants have volunteered to participate in/Self select Ex: Online polls

Snowball sampling

Select a few individuals who contact others/similar individuals

Random sampling

differences are due to random errors

Nonrandom sampling

differences may be due to systemic bias not just random chance

Null Hypothesis (H0)

A statement that is completely inconsistent with a proposed research hypothesis (no difference)

Alternative Research Hypothesis

A statement consistent with the proposed research hypothesis (will be a difference)

Nondirectional hypothesis

Hypothesizes that there is a difference, but not willing to speculate in advance on the direction of the difference

Directional Hypothesizes

Indicates the direction of the difference

Type 1 Error

Reject the null hypothesis when it is true Ex: false positive

Type 2 Error

fail to reject the null when in reality it is false Ex: false negative

What is the purpose behind using random sampling in research?

To stop researcher bias by giving everyone an equal chance of being chosen

One tailed difference

makes it easier to reject the null but in one direction only

Predictor variable (X)

The variable that is used to predict values and/or explain changes in the criterion variable

Criterion variable (Y)

the variable we are trying to predict given known values of the predictor variable

How does random sampling achieve population representativeness

By ensuring sample characteristics mirror population characteristics without researcher interference

What causes researcher response bias

When individuals who agree to participate in a study differ in important ways from those who decline to participate

How does non-response bias impact a research sample

It creates a non-representative sample limiting the ability to generalize findings to the population

What are strata

Mutually exclusive subparts or subgroups of a population divided among relevant dimensions such as age or gender

What are the advantages of using stratified over simple random sampling

It guarantees that key demographics or relevant dimensions are accurately represented in exact proportions

When to use snowball sampling

When the target characteristic is rare or difficult to locate

Advantages of random sampling

It removes researcher selection bias and increases the likelihood of obtaining a representative sample

Disadvantages of random sampling

It can be difficult and expensive and difficult to execute when a complete sampling frame is unavailable

Advantages of non random sampling

They are easier, less expensive, and easier to implement

Disadvantages of non random sampling

The sample is non-representative and subject to systemic sampling bias

What is sampling error

The natural gap between a sample result and the true population score, caused purely by random chance when picking a sample

What is systemic error

Error that occurs when specific segments of a population are systemically over or underrepresented

What are the three common causes of systemic sampling bias

Using non-representative sampling methods, improper weighting and very low response rates

How does population variability affect the required sample size in random sampling?

When variability is low a smaller random sample is sufficient; higher variability requires a larger sample