Week 2 Flashcards
Peabody Picture Vocabulary Test - the PPVT-4
- Children sit across from the experimenter, and are asked to point to the picture (from a choice of 4) which corresponds with a word.
- stops after failing a certain number of times in a row, and this level determines their overall score on the test.
- determine how strong an understanding children have of words and their meanings
- use age- based norms to determine whether a child is above, or below average in their vocabulary for their age.
Density curve
- smooth curve drawn through the tops of the histogram bars to smooth and refine distribution
- the peaks and troughs that don’t fit the curve cancel each other out: bumps, valleys and outliers are ignored
- can be skewed to reflect skewed data sets
- provides an idealised mathematical model of the distribution
- mean is the balance point
• Is always on or above the x-axis
• The area underneath is equal to 1 (100% of data)
Abraham DeMoivre
a french mathematician and astronomer. But it was his book on The Doctrine of Chances which was perhaps his largest contribution to normal distributions in statistics.
Frederick Gauss
Gauss determined the mathematical function that can describe normal distributions based on knowing the mean and standard deviation of a distribution.
Adolph Quetelet
- a Belgian mathematician and statistician
- he began to translate the normal distribution techniques that were traditionally used in Astronomy to the social sciences
- He applied these statistical techniques to understanding phenomena such as crime and marriage rates
- suggested that there were ‘average’ social traits, and that everyone exists somewhere along a normal distribution.
Sir Francis Galton
- wrote ‘Natural Inheritances’
- Galton was one of the proponents of our modern understanding of intelligence
- believed that Intelligence was normally distributed, from those few with very low intelligence to those with very high intelligence, and most people in the middle
- made some controversial suggestions of ways that intelligence could be ‘bred’ by allowing only intelligent people to breed, but his contributions to the wide use of distributions was extremely influential
Characteristics of normal distribution
- distribution is symmetrical
- unimodal
- bell shaped
- no limits
- mean, median and mode are equal
Standardising Scores
- z test
- t score
- stanine
- normal curve equivalent (NCE)
- intelligence quotient
- WAIS subtest scaled score
- look up image
Z distribution
• It is so common that it is often referred to as “The standard normal
distribution”
• The standard normal distribution (z distribution) has
• Mean = 0
• Standard deviation = 1
• All normal distributions, regardless of their mean and standard deviation can be converted into a standard normal distribution
Uses of Z scores
- Use #1: State how far away a score is from the mean in standard deviation units
- Use #2: Comparing scores from different distributions
- Use #3: Finding the proportion of observations above a score, below a score, or between two scores
- Use #4: Finding a value given a proportion
Z scores for comparison
• Example: Stephanie got a score of 76 out of 100 in her Stats and 82 out of 100 Philosophy. Which exam did she do better on relative to other students?
- take her score and the mean and SD from each, whichever is higher is what she actually did better in
Applications for finding proportions
- Find the percentage of people who score higher or lower than a certain value in tests
- Determining if a person/product is sufficiently deviant from the mean to be of concern
- A “normative” model for psychological functions and public health proposes that those outside of a “standard range” may suffer from a problem that needs intervention
