lecture 6 * diagnostics*
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1
why can't we use z score in skewd tests ?
z score : 1,1 migh actually be pretty normal
z score assumes normal distribution
z score assumes normal distribution
2
what test do we use in skewed ?
normalized standard scores
only with large group
only with large group
3
how do we get to the normalized score?
base on precentile
1. raw → precentile
2. precentile → equivalent z score = normalized standard score
3. use z score as normalized standard score
1. raw → precentile
2. precentile → equivalent z score = normalized standard score
3. use z score as normalized standard score
4
how are normalised standard scores ?
non linear as they are basing them on percentiles
5
what does the non liniar transformation tell us ?
raw score charcteristics distorted
different correlations
different correlations
6
what are other normalized standard score ?
stanine
c score
sten
c score
sten
7
what are the M and SD of stanine ?
M = 5, SD = 2
8
what are the M and SD of c score ?
M= 5, SD = 2
9
what are the M and SD of sten ?
M =5.5, SD= 2
10
how do we compare norms for different tests?
tranform both in the same score
11
how do we tranform a z score into a t score ?
12
how do we transform a t score into a z score ?
( T score _ 50 ) / 10 = z score
13
which way of comparing tests is better ?
transform z score to t score is better
14
what is the goal of absolute norms ?
1. criterion referenced
2. domain referenced
3. developmentally
2. domain referenced
3. developmentally
15
what types of absolute norms are there ?
1. summative assesments
2. formative assesments
2. formative assesments
16
what are summative assesments ?
slection / qualification / prognosis
MTA1 exam
MTA1 exam
17
what are formative assesments ?
tells us something about strengths and weaknesses
aim is to instruct
pollas / feedback
aim is to instruct
pollas / feedback
18
what are the norm requirments ?
1. representativeness
2. size
3. placement
2. size
3. placement
19
what does representativeness mean ?
take into acount many characteristics : → who is the test for
sex
age
class
education
ethnicity
religion
city \ rural
sex
age
class
education
ethnicity
religion
city \ rural
20
what methods of sampling are there?
1. randomn sampling
2. stratisfied randomn sampling : look at charcteristics and try to include all of them in the same ratios
2. stratisfied randomn sampling : look at charcteristics and try to include all of them in the same ratios
21
what size requirments are there for important decisions ?
important decisions :
good more than 400
sufficinet between 300 and 400
insufficient less than 300
good more than 400
sufficinet between 300 and 400
insufficient less than 300
22
what duraility requirments are there ?
1. timely
after 15 years outdated
after 20 years no longer usable
2. societal changes
3. educational changes
after 15 years outdated
after 20 years no longer usable
2. societal changes
3. educational changes
23
what subgroups requirments are there?
relavant norm groups in regards to age,sex, ethinicity and region ( rural / urban )
class and grade must be taken into consideration
class and grade must be taken into consideration
24
what is the Flynn effect ?
ncrease in both fluid and crystallized intelligence test scores that were measured in many parts of the world over the 20th century
25
what information do we need to determine when a score no longer "normal"?
severity
characteristics and traits of the person
we can use arbitrary or test specific
characteristics and traits of the person
we can use arbitrary or test specific
26
what are the most common intervals of normality ?
high more than 2 SD
above average more than 1SD
average between _1 and 1 SD
below average more than 1SD
low more than 2 SD
above average more than 1SD
average between _1 and 1 SD
below average more than 1SD
low more than 2 SD
27
what specifications do we need to create a norm table ?
range score
mean
standard deviation
mean
standard deviation
28
how do we determine the cut off average ?
→ high scores : mean +2SD up until maximum
→ above average : more than mean + 1SD
→ average scores : between mean + 1SD and mean _ 1SD
→below average : mean _ 1SD
→ low scores : between minimum and mean _2 SD
→ above average : more than mean + 1SD
→ average scores : between mean + 1SD and mean _ 1SD
→below average : mean _ 1SD
→ low scores : between minimum and mean _2 SD
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