What is T- Test | Meaning | Types | Example

Welcome to Research Hub.

A t-test is
the final statistical measure

for determining differences
between two means

that may or may not be related.

The testing uses
randomly selected samples

from the two categories
or groups.

It is a statistical method in which
samples are chosen randomly.

There is no perfect
normal distribution.

A t-test is a statistical test

that is used to compare
the means of two groups.

It is often used in hypothesis testing

to determine whether
a process or treatment

actually has an effect
on the population of interest,

or whether two groups
are different from one another.

Okay, when to use a t-test?

A t-test can only be used

when comparing the means of two groups,

a.k.a.
pairwise comparison.

If you want to compare
more than two groups

or if you want to do
multiple pairwise comparisons,

use an ANOVA test
or a post-hoc test.

The t-test is
a parametric test of difference,

meaning that it makes the same
assumptions about your data

as other parametric tests.

The t-test assumes your data

1,
are independent,

2,
are approximately normally distributed

3,
have a similar amount of variance

within each group being compared,

a.k.a.
homogeneity of variance.

Types of t-test.

1,
one-sample t-test.

The one-sample t-test is a
statistical method that helps determine

if the mean of a single sample
is significantly different

from a known
or supposed population mean.

It is valuable for working with
small sample sizes

and normally distributed data.

The test allows researchers and analysts

to draw meaningful conclusions
from limited data.

The one-sample t-test involves
calculating the t-statistic

by taking the mean of the sample,

subtracting the assumed population mean,

and then dividing by
the standard error of the mean.

It is widely used in research
across several domains

to examine if a sample
is representative

of a larger population.

2,
independent two-sample t-test.

This is the test conducted when samples

from two different groups,
species, or populations

are studied and compared.

It is also known as
an independent t-test.

The two-sample t-test,
also known as

the independent samples t-test,
is a method used to test whether

the unknown
population means of two groups

are equal or not.

For example,
if a teacher wants to compare

the height of male students
and female students,

she would use
the independent two-sample test.

The t-test formula
used to calculate this is...

The need to compare
the means of height

between two independent group,
male and female,

independent samples t-test
could be performed.

This hypothesis testing is conducted
when two groups

belong to the same population or group.

The groups are studied either
at two different times

or under two varied conditions.

The paired samples t-test
is a statistical test

used to determine if two paired groups

are significantly different
from each other

on your variable of interest.

Your variable of interest
should be continuous,

be normally distributed.

The formula used to
obtain the t-value is...

For equal-variance t-test,

this test is conducted

when the sample size in
each group or population is the same,

or the variance of
the two data sets is similar.

It is also referred to
as pooled t-test.

The formula applied:

mean 1 and mean 2
equal average value

of each set of samples.

Variable 1 and variable 2
equal variance

of each set of samples.

n1 and n2
equal number of records in each set.

5,
unequal variance t-test.

The unequal variance testing is used

when the variance and
the number of samples in each group

are different.

It is often referred to as Welch's test,

and the formula is...

mean 1 and mean 2
equals average value

of each set of samples.

Var 1 and var 2 equals
variance of each set of samples.

n1 and n2 equals
number of records in each set.

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