We often hear people saying “this research study proved that…” Well, researchers never **prove** anything when testing hypotheses. We do collect evidence that may or may not support our claims. In a well-designed research study in which the null hypothesis (H0) is rejected, all that can be said is that empirical evidence was collected to support the formulated alternative hypothesis.
Karl Popper (as cited here) said, ‘All swans are white cannot be proved true by any number of observations of white swan – we might have failed to spot a black swan somewhere – but it can be shown false by a single authentic sighting of a black swan. Scientific theories of this universal form, therefore, can never be conclusively verified, though it may be possible to falsify them.’
The video below shows how to change tables in SPSS to comply with the APA Style.
Often times we need to calculate age from birthdate. Follow the link below to learn how this can be done in SPSS.
Reporting research results in a manuscript is not an easy task. The American Psychological Association has its own requirements. Dr. Kahn (Illinois State University) provides a summary of such requirements in his webpage.
For further information, visit the APA Style Manual’s site here.
Creating a correlation matrix by hand is time consuming and not worth the effort, especially if the analysis was done with SPSS.
You don’t need to have access to MS Excel, SPSS or other expensive piece of software to create charts/diagrams. Online Chart Tool is free and very user friendly.
Calculating percentiles for a data set by hand is tedious, if not impossible often times. In the video below, I demonstrate three methods for calculating percentile scores for a data set using SPSS.
To calculate age in terms of years, months, and days, DATEDIF is a handy function.
… where “birthday” is the cell containing the DOB and “date” is the current date. Ensure to preserve the order of the elements depicted inside the parenthesis.
UPDATE: You can also use SPSS to compute age from birthdate. Click here to learn how this is done.
According to Vincent and Weir (2012) “power is the ability of a test to detect a real effect in a population based on a sample taken from that population” (p. 166). There are many applications capable of determining “power” and sample size. Perhaps the best one is called G*Power which can be downloaded for free here. The video below simply shows how to install the application in a PC running Windows 7.
G*Power 3 is a major extension of, and improvement over, G*Power 2. It covers statistical power analyses for many different statistical tests (e.g., F-test, t test, χ2–test, etc.).
The application can be download for free here and an excellent article on G*Power can be found here. You can also learn how to use G*Power by reviewing the site’s user guide section, which can be found under this link.
Watch video below: [video_lightbox_youtube video_id=”NQJuNLyhBPo&rel=false” width=”640″ height=”485″ auto_thumb=”1″]