Experimental Unit & Population – A Statistics Study

Experimental Unit & Population – A Statistics Study

This is a Statistics Study about Experimental Unit & Population groups.


is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. In addition statistics is about proving a measure of confuse in any conclusions.


a fact or proposition used to daw occlusions or make a decision


the entire group to be studied


is a person or object that a member of the population being studied


is a subset of the population that is being studied


is a numerical summary of a sample

Descriptive Statistics

consist of organizing and summarizing date. Depicts the data through numerical summaries, tables, and graphs.

Inferential Statistics

uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result.


is a numerical summary of a population

Qualitative (or categorical) Variables

allow for the classification of individuals based on some attribute or characteristic

Quantitative Variables

provide numerical measures of individuals. The values of a quantitative variable can be added or subtracted and prove meaningful results.


a way to look at and organize a problem so that it can be solved.

Discrete Variable

is a quantitative variable that has either a finite number of possible values or countable number of possible value. The term countable means that the values result from counting, such as 0,1,2,3, and so on. A discreet variable cannot take on every possible value between any two possible values.

Continous Variable

is a quantitative variable that has an infinite number of possible valued that are not countable. A continuous variable may take on every possible value between any two values.


the list of observed values for a variable

Qualitative Data

are observations corresponding to a qualitative variable

Quantitative Data

are observations corresponding to a quantitative variable

Discrete Data

are observations corresponding to a discrete variable

Continous Data

are observations corresponding to a continuous variable

Nominal Level of Measurement

if the values of the variable name, label, or categorize. In addition, the naming scheme does not allow for the valued of the variables to be arranged in a ranked or specific order.

Ordinal Level of Measurement

if it has the properties of the nominal level of measurement, however the naming scheme allows for the valued of the variable to be arranged in a ranked or specific order.

Interval Level of Measurement

if it has the properties of the ordinal level of measurement and the differences in the vales of the variables have meaning. A value of zero does not mean the absence of the quantity. Arithmetic operations such as addition and subtraction can be performed on valued of the variable.

Ratio Level of Measurement

if it has the properties of internal level of measurement and the ratios of the variable have meaning, A value of zero means the absence of quantity. Arithmetic operations such as multiplication and divisions can be performed on the values of the variable.

Explanatory Variable

the variable that determines the response of the response variable

Response Variable

the variable that reacts as a result of a explanatory variable

Observational Study

measures the value of the response variable without attempting to influence the value of either the response or explanatory variables. That is, in an observational study, the researcher observes the behavior of the individuals without trying to influence the outmode of the study.

Designed Experiment

is a experiment in which a researcher assigns the individuals in a study to a certain group, intentionally changes the value of an explanatory variable, and then records the value of the response variable for each group.


is when the effects of two or more explanatory variables are not separated. Therefor, any relation that may exist between an explanatory variable and the response variable may be due to some other variable or variables not accounted for in the study.

Lurking Variable

is an explanatory variable that as not considered in a study, but that affects the value of the response variable in the study. In addition, lurking variables are typically related to explanatory variables considered in the study.

Confounding Variable

is an explanatory variable that was not considered in a study whose effect cannot be distinguished from a second explanatory variable in a study.


studies that require individuals to look back in time or require the researcher to look at existing records.


is a list of all individuals in a population along with certain characteristics of each individual.

Random Sampling

is the process of using chance to select individuals from a population to be included in the sample.

Simple Random Sampling

if every possible sample of size n has an equally likely chance of occurring.


a list of all the individuals within the population.

Sample Without Replacement

an individual who is selected is removed from the population an cannot be chosen again.

Sample With Replacement

a selected individual is placed back into the population and could be chosen a second time.


is an initial point for the generator to start creating random numbers.

Stratified Sample

is obtained by separating the population into non overlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each spectrum should be homogeneous (or similar) in some way.

Systematic Sample

is obtained by selecting ever kth individual from the population. The first individual selected corresponds to a random number between 1 and k.

Cluster Sample

is obtained by selecting all individuals within a randomly selected collection or group of individuals.

Convince Sample

is a sample in which the individuals are easily obtained and not based on the randomness.


is when the individuals themselves decide to participate in a survey or some other voluntarily done act.

Voluntary Response*

is when the individuals themselves decide to participate in a survey or some other voluntarily done act.


when the results of the sample are not representative of the population.

Sampling Bias

is when the technique used to obtain the sample’s individuals tend to favor one part of the population over another.


is when the proportion of one segment of the population is lower in a sample than it is in the population.

Nonresponse Bias

is when individuals selected to be in the sample who do not respond to the survey have different opinions from those who do. This can happen when the selected individuals do not wish to respond or the interviewer was unable to contact them.

Response Bias

is when the answers on a survey do not reflect the true feelings of the respondent.

Nonsampling Error

is the result from the undercoverage, nonresponse bias, response bias, or data-entry error. Such errors could also be present in a complete census of the population.

Sampling Error

results from using a sample to estimate information about a population. This type of error occurs because a sample gives incomplete information about a population.


is a controlled study conducted to determine the effect of caring one or more explanatory variables or factors has on a response variable.


another term for explanatory variable.


any combination of the values of the factors.

Experimental Unit

is a person, object, or some other well defined item upon which a treatment is applied.


often referred to as the experimental unit.

Control Group

serves as a baseline treatment that can be used to compare it to other treatments.


is an innocuous medication, such as a salt tablet, that looks, tastes, and smells like the experiment medication.


refers to nondisclosure of the treatment an experimental unit is receiving.


the experimental unit does not know which treatment he or she is receiving.


neither the experimental unit nor the researcher in contact with the experimental unit knows which treatment the experimental unit is receiving.

Completely Randomized Design

is one in which each experimental unit is randomly assigned to a treatment.

Matched-pairs Design

is an experimental design in which experimental units are paired up. The pairs are selected so that they are related in some way (that is, the same person before and after a treatment, twins, husband, and wife, same geographical location, and so on). They are only two levels of treatment in this type of design.


is when you group together similar experimental units and then randomly assigning the experimental units within each group to a treatment.


the term used to refer to each group of homogenous individuals in a blocking experiment.

Randomized Block Design

is used when the experimental units are divided into homogenous groups called blocks. Within each block the experimental units are randomly assigned to treatments.