Scoring systems and conversions (1)

In this unit, you will be introduced to the use of statistics in psychometric testing, focusing especially on how raw scores are turned into meaningful information through score systems such as percentiles, Z scores, T scores, and others. You’ll learn the basics of normal distribution, how to interpret and calculate percentile ranks, and the pros and cons of different standard score systems. This session aims to build your confidence with the numbers involved, ensuring you can understand and communicate test results clearly.

After this talk, you will:

• Understand why statistics are necessary when interpreting psychometric test results.

• Be aware of how raw scores from tests need to be converted into more meaningful scores.

• Be able to describe what a normal distribution curve is and why it's important in psychometric testing.

• Know what a percentile score is and how to calculate it.

• Understand common misunderstandings around percentile scores and how to explain them clearly to others.

• Recognise the limitations and problems with percentile scores, including the issue of non-linearity.

• Know that percentiles compare individuals to others, not to the total number of questions answered correctly.

• Be introduced to other standard score systems, such as z-scores, T scores, stens, stanines, and IQ scores.

• Understand that each scoring system has pros and cons, and that you may need to convert between systems.

• Realise the importance of using norm tables and being careful when interpreting and reporting test scores.