STA301 Glossary

Absolute Measure of Dispersion

An absolute measure of dispersion is one that measures the dispersion in terms of the same units, or in the square of units as the units of the data.

Acceptance and rejection region:

All possible values which a test-statistic may assume can be divided into two mutually exclusive groups: One group consisting of values which appear to be consistent with the null hypothesis (i.e. values which appear to support the null hypothesis), and the other having values which lead to the rejection of the null hypothesis. The first group is called the acceptance region and the second set of values is known as the rejection region for a test

Addition law

A probability law used to compute the probability of a union of two events, denoted A and B. It is P(AÈB)=P(A)+P(B)-P(AÇB). For mutually exclusive events, because P(AÇB)=0, it reduces to P(AÈB)=P(A)+P(B).

Alternative hypothesis

The hypothesis concluded to be true if the null hypothesis is rejected.

ANOVA

Analysis of variance is defined as the procedure by means of which the total variability of the set of data measured by total sum of square is partitioned into components that measure different sources of variations. The procedure thus permits the decomposition of the total SS into to the component SS which are corresponding to the real and suspected sources of variations.

ANOVA table · STA301 · Glossary

A table used to summarize the analysis of variance computations and results. It contains columns showing the source of variation, the sum of squares, the degrees of freedom, the mean square, and the F values.

Arithmetic Mean

Arithmetic Mean is a value obtained by dividing the sum of the observations by their numbers.

Average

Basic Randomized Designs:

Randomization Replication Local Control

Bayes' theorem

A method used to compute posterior probabilities.

Binomial experiment

A probability experiment having the following four properties: consists of n identical trials, two outcomes (success and failure) are possible on each trial, probability of success does not change from trial to trail, and the trials are independent.

Binomial probability distribution

A probability distribution showing the probability of x successes in n trials of a binomial

Binomial probability function

The function used to compute probabilities in a binomial experiment.

Blocking

The process of using the same or similar experimental units for all treatments. The purpose of blocking is to remove a source of variation from the error term and hence provide a more powerful test for a difference in population or treatment means.

Box and Whisker plot

A Box and Whisker plot provides a graphical representation of data through its five number summary.

Box plot

A graphical summary of data. A box, drawn from the first to the third quartiles, shows the location of the middle 50% of the data. Dashed lines, called whiskers, extending from the ends of the box show the location of data values greater than the third quartile and data values less than the first quartile. The locations of any outliers are also noted.

Central limit theorem

A theorem that enables one to use the normal probability distribution to approximate the sampling distribution of the sample mean and sample proportion whenever the sample size is large.

Chebshev's Theorm

Chebshev's Theorem states that " For any number K greater than one at least 1-1/k2 of the data values fall with in K standard deviations of the mean i.e. within the interval.

Class Mark or Mid Point

The class mark or mid point is that value which divides a class into two equall parts.

Class midpoint

The point in each class that is halfway between the lower and upper class limits.

Class of Sets

A set of sets is called a class.

Classification

The process of arranging data in classes or categories according to some common characteristics present in the data is called classification.

Complement of event A

The event consisting of all sample points that are not in A.

Complete Randomized Designs

In this design treatments are applied to the experimental units completely at random, that is randomization is done without any restrictions. Design is completely flexible, any number of treatments and any number of units per treatments can be applied.

Conditional Probability

The probability of the occurence of an event A when it is known that some other event B has already occured is called the conditional probability.

Consistency

A property of a point estimator that is present whenever larger sample sizes tend to provide point estimates closer to the population parameter