1.3: Data Collection & Experimental Design

Vocabulary flashcards generated from lecture notes covering data collection, experimental design, and various sampling techniques.

Design of Statistical Study

guidlines of statistical study

1. WHAT/WHO — identify variables of interest (the focus) & population of study

2. HOW — develop detailed plan for collecting data (make sure sample is representative of population)

3. collect data

4. describe data using descriptive statistical tenchiques

5. interpret data & make decisions about population using inferential stats

6. identify any possible errors

Design of Statistical Study

Observational Study

researcher observes and measures characteristics of interest of part of a population but does NOT change existing conditions.

Design of Statistical Study

Experimental Study

• researcher applies a treatment to part of a population and observes the responses

• control group has no treatment applied (usually given placebo)

Data Collection

Simulation

The use of a mathematical or physical model to reproduce the conditions of a situation or process.

Data Collection

Survey

An investigation of one or more characteristics of a population, usually carried out on people by asking them questions through interviews.

Experimental Design

3 Key Elements for a Well-Designed Experiment

1. control

2. randomization

3. replication

Experimental Design

Confounding Variable

A factor that occurs when an experimenter cannot tell the difference between the effects of different factors on a variable.

Experimental Design

Placebo Effect

An effect that occurs when a subject reacts favorably to a placebo when in fact the subject has been given a fake treatment.

• can be avoided by: single bind & double bind

Experimental Design

Single Blind

• technique to avoid placebo effect

• subjects do not know whether they are receiving a treatment or a placebo.

Experimental Design

Double Blind

• technique to avoid placebo effect

• neither the researcher nor the subjects know whether a given subject is receiving the treatment or the placebo.

Experimental Design

Randomization

A process of randomly assigning subjects to different treatment groups.

• 3 types of design: simple randomized, randomized block, matched pair

Experimental Design

Simple Randomized Design

An experimental design in which subjects are assigned to different treatment groups through random selection.

• type of randomization

Experimental Design

block

group of subjects with certain characteristics

Experimental Design

Randomized Block Design

An experimental design in which individuals are first sorted into blocks based on certain characteristics, and then a random process is used to assign each individual in the block to one of the treatments.

• type of randomization

Experimental Design

Matched-Pairs Design

An experimental design in which subjects are paired up according to similarity, and one subject in each pair is randomly selected to receive the treatment while the other receives a different treatment.

• type of randomization

Experimental Design

Sample Size

The number of subjects in a study.

Experimental Design

Replication

The repetition of an experiment under the same or similar conditions.

Sampling Techniques

Census

A count or measure of an ENTIRE population.

• rarely used because it’s expensive & time-consuming

Sampling Techniques

Sample

A count or measure of PART of a population

• more commonly used

Sampling Techniques

Sampling Error

The difference between the results of a sample and those of the population.

Sampling Techniques

Random Error

A measurement mistake caused by factors that vary from one measurement to another

• statistical error due to chance.

Sampling Techniques

Random Sample

A sample in which EVERY member of the population has an equal chance of being selected, progressing without definite aim, reason, or pattern.

Sampling Techniques

Simple Random Sample

A sample in which every possible sample of the same size has the equal chance of being selected.

Sampling Techniques

Stratified Random Sampling

members of the population are divided into two or more subsets, called strata, that share a similar characteristic, and a sample is then randomly selected from each stratum.

Sampling Techniques

Cluster Sampling

population is divided into groups, called clusters, and all members in one or more (but not all) of the clusters are selected.

Sampling Techniques

Systematic Sample

each member of the population is assigned a unique number, a starting number is randomly selected, and sample members are chosen at regular intervals from the starting number.

Sampling Techniques

Convenience Sampling

drawing representative data by selecting people because of the ease of their volunteering or selecting units because of their availability or easy access.

Sampling Techniques

Multistage Sampling

population is divided into a number of primary groups from which samples are drawn, which are then divided into secondary groups from which samples are drawn, and so on.

• basically making smaller & smaller & smaller groups