A statistical table presents statistical data in a systematic arrangement of numbers and describes phenomena. It consists of vertical columns and horizontal rows with headings indicating the subject and predicate. Statistical tables are used to determine if statistical results exceed required significance levels by showing values of distribution functions for different parameter values. T score and Z score tables specifically show descriptions of samples drawn from populations and are used in analyses like t-tests, regression, and building confidence intervals by standardizing scores based on population means and standard deviations.

1. STATISTICAL TABLES

2. (Statistics) tables showing the values of the cumulative distribution functions, probability
functions, or probability density functions of certain common distributions for different
values of their parameters, and used especially to determine whether or not a particular
statistical result exceeds the required significance level.

4. A statistical table is a way you can present statistical data by arranging the numbers systematically
and describing some mass process or phenomenon.
A statistical table can be seen as a representation of a subject and a predicate. The subject is the
group of phenomenon discussed in the table. The predicate is the characteristics that describe the
subject.
Statistical tables consist of vertical columns and horizontal rows. The subject is usually entered in the
rows of the table, while the predicate is entered in the columns. The column and row intersection
forms the cells. This is where the numerical data will be arrayed. The headings of the corresponding
column and row indicate what every number means.

5. T SCORE
TABLE
 In statistics and probability, the T score table is a member
of a continuous distribution of probability that arises when
the normally distributed population mean is estimated.
 This is done in conditions where the standard deviation of
the population is unknown and the sample size is few.
 It was founded by William Sealy Gosset. T score shows the
description of samples drawn from a complete population.
 Accordingly, the T score table for each size of a sample is
different, and the bigger the sample, the more the table
shows the resemblance of a normal distribution.
 The T score table plays a vital role in a number of broadly
used analyses of statistics.
 This includes linear regression analysis, Student’s t-test for
the assessment of the statistical importance of the difference
in the two means of the sample, the building up of
confidence intervals for the difference of two population
means.
 The T score table also arises from a normal family in the
Bayesian data analysis. You can use nifty T score calculators
from Stat Calculators to speed up computation.

6. Z SCORE TABLE
 In statistics, the Z score table is the standard deviation signed number by which a data or an
observation is above the mean.
 A Z score table is a score that is derived. It is used to make interpretations that are norm-referenced,
for which the standard deviation and the mean are selected to make the interpretations easier.
 A positive Z score table shows the indication of a datum that is above the mean, while a negative Z
score table shows the indication of a datum that is below the mean.
 It is a quantity that is dimensionless gotten by the subtraction of the population mean from a single
raw score and then the division of their difference by the standard deviation of the population.
 This process of conversion is called normalizing or standardizing.
 Z score can be calculated using a table or a z score calculator.
 The Z score table is mostly used in comparing a sample to a standard normal deviation, even though
they may be defined without normality assumptions

7. USES
 Tables are widely used in communication, research, and data analysis.
 To show many and precise numerical values and other specific data in a small
space
 To compare and contrast data values with several shared characteristics or
variables
 To show the presence or absence of specific characteristics