STATS vocab test

Types of Experimental Design

1. CRD (Completely Randomized Design) All experimental units assigned random among all treatments THIS IS NOT BLOCKING

2. BLOCKING goal: create homogeneous groups benefit: reduce variation A. RBD (Randomized Block Design) experimental units put into homogeneous blocks. The random assignment of the units to the treatments is carried out separately within each block. B. Matched Pairs: A form of blocking in which each subject receives both treatments in a random order or the subjects are matched in pairs as closely as possible and one subject in each pair receives treatment, determined at random

Advantage of using Stratified Random Sample Over an SRS

1. Guarantees each STRATA will be represented

2. Reduces variability in a SRA of same size

Experiment or Observational Study

1. Experiments have treatments and name the treatment.

2. Observational studies do not

Does correlation imply causation?

Observational studies do NOT show causation. Only well designed controlled experiment shows cause and effect (causation)

Blinding/Double Blinding

Purpose: to reduce bias

Blind: When the subject does not know which treatment was being administered

Double blinding: When the subject nor the evaluator does not know which treatment is being administered

Why use a control group?

1. Used to evaluate the effectiveness of the treatment

2. BY reducing the effect of confounding variables

Types of Bias

1.Volunteer Response: when only those that choose to participate do usually because they have an emotional connection (feel strongly)

2. Response Bias: give a response that is not truthful because of the wording of the question or because they are uncomfortable to respond truthfully

3. Undercoverage Bias: Where a certain group of the population is left out

4. Selection Bias: Where a certain population is over represented in the sample

Confounding Variable

A variable that is not controlled in the experiment (outside factor) that is effecting the response variable rather than the explanatory variable effecting it. Describe how it effects both groups in context

Methods of Sampling

1. SRS: Number of entire population, draw numbers from a hat (every set of n individuals has an equal chance of selection)

2. Stratified: Split the population into homogeneous groups, select an SRS from each group

3. Cluster: Split the population into heterogeneous groups called clusters, and randomly select whole clusters for the sample Ex. Choosing a cartoon of eggs actually chooses a cluster (group) of 12 eggs

4. Census: An attempt to reach the entire population

5. Convenience: Selects individuals easiest to reach- improper way to sample introduces bias

Randomization

Purpose: to reduce bias

Conclusions you can make:

For Random Sample (RS): Generalize the conclusions to the population

For Random Assignment (RA): Cause and Effect

Why?

Random Sample: Good representation of the population

Random Assignment: Create 2 roughly equal groups so the results will have reduced bias