**Independent Samples**

*t-*test
Researchers use the independent samples

*t*-test to find out if there is a significant difference between two sets of data. In the behavioral sciences, the data are often two sets of scores on tests or survey items.
Significance can mean a lot of different things. In
behavioral science, it is common to think of significance as a frequently occurring,
and thus reliable, difference. Sometimes the language of statistics can be confusing.
The independent sample

*t*-test evaluates the differences between the arithmetic means of the two groups of scores, and assumes the scores are normally distributed.
Usually, a difference needs to be at least large enough that
a score difference as large, or larger than the one obtained, occurs only 5% of
the time by chance.

The calculations are usually done in spreadsheets like Excel
or Google Sheets or in a program like SPSS.

You will find the following text in Chapter 16
of Creating
Surveys. I also cover

*t*-tests in*Statistics for Counselors.*

Creating SurveysCreate better surveys for work and schoolRead FREE on Amazon Kindle UnlimitedDOWNLOAD today AMAZON |

The statistical procedure results in a

*t*-value and a*p*value. The larger the*t*-value, the more likely it is that the difference between the group means is significant. The*p*-value represents the probability that the*t*-value of the size obtained did not occur by chance. As in many cases, the*p*-value is reported based on a 95% probability that the*t*-value did not occur by chance. The*p*-value is usually reported by considering the likelihood that it occurs by chance greater or less than 5% of the time where 5% is written as .05. If the probability is less than .05 that a*t*-value as large or larger than the one obtained did not occur by chance, the researcher would report the results as*p*< .05. If the*t*-value was too small to meet the level needed for significance, the researcher would just report the finding as not significant (*p*> .05).
I and my colleagues have studied forgiveness.
Suppose we found that people who attended a forgiveness seminar obtained higher
forgiveness scores compared to those who did not attend.

Here’s how we might write the results (Chapter 16,

**).***Creating Surveys*
We found that people who did attended the forgiveness
seminar were significantly more forgiving (

*M*= 39,*SD*= 5) than were people who did not attend the seminar (*M*= 30,*SD*= 5),*t*(98) = 6.75,*p*< .05.Applied Statistics: Concepts for CounselorsAvailable in over 12 countries. |

You can calculate the independent samples

Also, here is an online calculator where you can enter two sets of values and obtain a

EasyCalculation.com

*t*-test by hand. If you are interested, here's a link to an example at*UC Davis.*Also, here is an online calculator where you can enter two sets of values and obtain a

*t*-test result.EasyCalculation.com

**Connections and Links to Resources**

TWITTER @Geoff.W.Sutton

LinkedIN Geoffrey Sutton PhD

**Publications (many free downloads)**

Academia Geoff W Sutton (PhD)

ResearchGate Geoffrey W Sutton (PhD)

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