Chapter 1 The Nature of Statistics

Statistics

the science of data

Descriptive Statistics

consists of methods for organizing and summarizing information

Population

a collection of all individuals or items under consideration

Sample

the part of population from which information is obtained

Census

the collection of data from every member of a population

Inferential Statistics

consist of methods for drawing and measuring the reliability

observational Study

data collection method where the experimental units samples are observed in their natural setting

Designed experiment

data collection method where the researcher exerts full control over the characteristics of the experimental units sampled

Simple Random Sampling

a sampling procedure for which each possible sample of a given size is equally likey to be the one obtained

simple random sample

a sample obtained by simple random sampling

representative sample

exhibits characteristics typical of those possessed by the population

Simple random sampling with replacement (SRSWR)

a member of the population can be selected more than once

Simple random sampling without replacement (SRS)

a member of the population can be selected at most once

Random Number Tables

table of random number that you can find numbers which correlate to certain data to be tested

Stratified Sampling

subdivide the population into at least two different subgroups (or strata) so subject in each group share the same characteristics

• divide population into subpopulations (strata)

• from each stratum, obtain simple random sample of size proportional to the size of the stratum,

• sample size for a stratum= total sample size (stratum size/population size)

• use all the members obtained in Step 2 as the sample

Systematic Sampling

• determine sample size, divide the population size by the ideal sample size and round the result down to the nearest whole number, m

• select some starting point then select every kth element in the population (between 1 and m)

• select for the sample those members of the population that are numbered k,k+m,k+2m.,,

Cluster Sampling

• divide the population area into sections (clusters)

• obtain a simple random sample of the cluster

• use all the members of the clusters obtained in step 2 as the sample

Experimental Units

the individuals or items on which the experiment is performed

Subjects

when humans are the experimental units

Principles of Experimental Design

Control, Randomization, Replication

Control

two or more treatments should be compared

Randomization

the experimental units should by randomly divided into groups to avoid unintentional selection bias

Replication

a sufficient number of experiment units should be used to ensure that randomization creates group that show similar results

Response Variable

the characteristic of the experimental outcome that is to be measured or observed

Factor

variable whose effect on the response variable is of interest in the experiment

level

the possible values of a factor

treatment

each experimental condition/ possibility

Completely Randomized Design

all the experimental units are assigned randomly among all the treatments

Randomized Block Design

the experimental units are assigned randomly among all the treatments separately within each block

Block

experimental units that are similar in ways that can affect the response variable are grouped