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National IQs revisited: The first steps of a long-term project.

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Abstract and Figures

The dataset of national IQs presented by Richard Lynn and Tatu Vanhanen first in 2002 and most recently in 2012 was both frequently criticized and used in cross-national research. It has also become very popular in public discussions, for example in web forums, and thus well known to a broader audience. Because of this popularity, we consider it important that the dataset behind this list is maintained, continued and improved for future research. Furthermore, an improved transparency and traceability of the methods can be useful in communication of the results. For about a year a group of researchers decided to carry out this task, beginning with the collection, as much as was possible, of sources for national IQs, along with restructuring of the original work notes, which were shared willingly by Richard Lynn. In this talk we want to present the first results of this preliminary revision. All available sources which give raw scores for Raven’s Matrices were considered and all data were picked out which are necessary to understand the estimations and calculations from the raw scores to the final national IQ. This includes also a new and standardized estimation of the required Flynn Effect corrections, based on a meta-analysis conducted by Pietschnig and Voracek in 2015. Final and intermediate results were correlated with the original results as well as with common associated variables (PISA, TIMSS, GDP/C, latitude, skin color, etc.). The talk will include discussions about discrepancies between the original data and the revisit. Problems with our methods will be discussed, and their validity will be assessed. In addition, future plans –– further work on national IQ, and an open access online data set -- will be presented.
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National IQs revisited:
The first steps of a long-term project
David Becker
TU Chemnitz,
Germany
London Conference on Intelligence, 12-14 May 2017
G22 Lecture Theatre, Pearson Building, UCL
London
David Becker
TU-Chemnitz Chemnitz
Germany
Becker, London Conference on Intelligence, 12-14 May 2017
London 1
1. Reestimation of national IQs
1.1 Basics
Fig1 National IQs by Lynn & Vanhanen (2012)
2
Ref.: Lynn, R., & Vanhanen, T. (2012). Intelligence. A Unifying Construct for the Social Sciences.
London: Ulster Institute for Social Research
Becker, London Conference on Intelligence, 12-14 May 2017
London
3
Criticization of the data set (scientific only)
- Non-representative samples
- Hunt & Sternberg, 2006
- McDaniel, 2008
- No weighting for sample size
- Hunt & Sternberg, 2006
- Sub-Saharan Africa‘s IQs too low in Raven‘s tests
- Wicherts, Dolan, & van der Maas, 2010
Becker, London Conference on Intelligence, 12-14 May 2017
London
1. Reestimation of national IQs
1.1 Basics
4
Principal aims (long-term)
- Reestimation of national IQs
- Using strictly standardized methodes
- Ensure traceability of calculations and estimations
- Comparisons between original and reestimated data
- Extension of the dataset
- More nations
- More sources
-More data
Principal aims (for now)
- Reestimation of national IQs by using scores from Raven‘s tests
- Comparisons between original and reestimated data
- Controlling for possible bias
Becker, London Conference on Intelligence, 12-14 May 2017
London
1. Reestimation of national IQs
1.1 Basics
1. Reestimation of national IQs
1.2 Data selection
Fig.2 Data selection
5
Full dataset of L&V
Records:691
Nations: 152
Raven‘s Matrices
Records:347 (~50%)
Nations: 115 (~76%)
SPM:179 SPM+:21 CPM: 140 APM: 10
SPM:118 SPM+:19 CPM: 109 APM: 7
Reestimated dataset
Records:253 (~73%|~37%)
Nations: 92 (~80%|~61%)
No selection
Selection for RPM
Available sources
and usable data
Final dataset in analysis
Becker, London Conference on Intelligence, 12-14 May 2017
London
Natio nal I
Q
(P&V) Nat ional I
Q
(L&V) Na t iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
1. Reestimation of national IQs
1.3 Calculation
Fig3 Calculation (record)
6
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
7
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
8
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
9
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Fig.4 Calculation (115.1.6 Saudi Arabia)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Age N Mean SPM
scores NMean SPM
scores NMean SPM
scores
IQ
(SPM(GBR)
1979)
881
14.93
142
16.78
223
16.11
85.08
974
19.74
123
23.54
197
22.11
88.42
10 102
24.20
134
28.40
236
26.58
85.08
11 172
28.47
129
29.71
301
29.00
77.86
12 169
30.35
147
30.53
316
30.43
77.86
13 186
31.03
162
33.89
348
32.36
79.89
14 196
33.14
148
35.22
344
34.03
78.92
15 227
33.00
162
35.44
389
34.02
80.78
16 152
36.45
138
36.37
290
36.41
79.89
17 146
37.02
164
37.41
310
37.23
18 108
37.28
147
35.07
255
36.01
N-
weighted
average
12.42
30.00
80.96
Batterjee (2011, Table 3)
Male Female Total
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
11
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
12
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Fig.5 FLynn-Effects
1. Reestimation of national IQs
1.3 Calculation
Annual
P&V L&V 3PD
P&V 1 .51 invar.
L&V .000 1 invar.
3PD invar. invar. invar.
Summed
P&V L&V 3PD
P&V 1 .98 .97
L&V .000 1 .99
3PD .000 .000 1
Note: p-values below
the diagonal
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
14
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
15
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
16
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
Nat io nal I
Q
(P&V) Nat iona l I
Q
(L&V) Nat iona l I
Q
(3PD) Orig. IQ Comp.
(P&V) Comp.
(L&V) Comp.
(3PD) Ref.
(short)
103.00 -2.37 -2.87 -2.84
110.00 4.63 4.13 4.16
108.00 2.63 2.13 2.16
105.87 105.84 Lynn et al.
(1988a)
105.37
17
ID Country Year Sample
orig. Sample
comp. Age(M) N Test Year of
test-
standard. Domain
1968.0 6.5 to 13.5 13,822
1982.0 6.5 to 15.5 4,500
1987.0 (-10.5) 197
nat. rep. SPM 1979 Full52.1.3 Hong Kong
Calc.? Raw Uncor. IQ Fly nn-
Effect
(P&V)
Fly nn-
Effect
(L&V)
Fly nn-
Effect
(3PD)
Other
correct. Final IQ
(P&V) Final IQ
(L&V) Final IQ
(3PD)
Y 34.33 101.19 2.54 3.30 3.30 0.00 103.73 104.49 104.49
Y 41.47 110.89 -0.55 -0.80 -0.90 0.00 110.34 110.09 109.99
Y 42.61 108.51 -1.39 -2.08 -2.40 0.00 107.11 106.43 106.11
Fig3 Calculation (record)
1. Reestimation of national IQs
1.3 Calculation
Becker, London Conference on Intelligence, 12-14 May 2017
London
18
Fig.6 Descriptive statistics
2. Results
2.1 Overview
Note: p-values below the diagonal
All Raven's Tests
Level Record Cross-national
Est. L&V1 L&V2 3PD P&V L&V1 L&V2 3PD P&V
M
66.76 65.53 65.29 66.05 87.75 85.22 84.91 85.67
SD
36.78 36.30 36.19 36.49 10.67 13.08 13.10 12.98
N
236 253 253 253 91 92 92 92
L&V1 1 .95 .95 .94 1 .86 .86 .83
L&V2 0.000 1 >.99 >.99 0.000 1 >.99 .97
3PD 0.000 0.000 1 >.99 0.000 0.000 1 .97
P&V 0.006 0.009 0.000 1 0.004 0.175 0.034 1
Becker, London Conference on Intelligence, 12-14 May 2017
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Fig.8a Reestimated national IQs (L&V2)
2. Results
2.2 Cross-national level
Becker, London Conference on Intelligence, 12-14 May 2017
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Fig.8b Reestimated national IQs (3PD)
2. Results
2.2 Cross-national level
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Fig.8c Reestimated national IQs (P&V)
2. Results
2.2 Cross-national level
Becker, London Conference on Intelligence, 12-14 May 2017
London
22
Fig.8c Reestimated national IQs (P&V)
2. Results
2.2 Cross-national level
Becker, London Conference on Intelligence, 12-14 May 2017
London
23
Fig.9 Scatterplot between national IQs (L&V1; P&V;
r
= .83)
2. Results
2.2 Cross-national level
ARG AUS
BIH
BWA BRA
BFA
KHM CAN
CHL
CHN
COD
CRI
CUB DEN
DMA ECU
EGY
ERI
EST
ETH
FIN
FRC
GMB
DEU
GHA
GTM
HKG
HUN
ISL
IND
IDN
IRN
IRQ IRL
ISR
ITA
JAM
JPN
JOR
KAZ
KEN
KOR
KWT
KGZ
LBY
LTU
MYS MLT
MEX MNG
MAR
NAM
NLD
ANT
NZL
NGA
OMN
PAK
PSE
PER
PHL
POL
PRT
PRI
QAT ROU
RUS
ZAF
SAU
SRB
SGP
SVK
SVN
ESP
LKA
SDN
CHE
SYR
TWN
TJK
TZA THA
TUR
UGA
UKR
ARE
GBR
USA
UZB
VNM
YEM
50
60
70
80
90
100
110
120
60 70 80 90 100 110
National IQs (P&V)
National IQs (L&V1)
Becker, London Conference on Intelligence, 12-14 May 2017
London
24
Fig.10 Scatterplot between national IQs (L&V1) and source IQs (P&V)
2. Results
2.2 Cross-national level
50
60
70
80
90
100
110
120
130
60 70 80 90 100 110
Reestimated IQs per source
National IQs (L&V1)
SPM SPM+ CPM APM MIX Linear (L&V1)
Becker, London Conference on Intelligence, 12-14 May 2017
London
25
Fig.11 Scatterplot between national IQs (L&V1) and source IQs (P&V),
linear trends by mean Iqs separated by Raven‘s test
2. Results
2.2 Cross-national level
.88
.83
.75
.82
50
60
70
80
90
100
110
120
130
60 70 80 90 100 110
Reestimated IQs per source
National IQs (L&V1)
national IQ (L&V1) Linear (M(SPM)) Linear (M(SPM+))
Linear (M(CPM)) Linear (M(APM))
.88
.75
.83
.82
Becker, London Conference on Intelligence, 12-14 May 2017
London
26
Fig.12 Deviations between national IQs estimated by L&V1 and P&V
3. Review
3.1 Deviations between old and new data
.43
.83
.75
.82
Note: Blue represents higher estimates at L&V1
Becker, London Conference on Intelligence, 12-14 May 2017
London
27
Fig.13 Deviations between national IQs estimated by L&V1 and
P&V (SPM only)
3. Review
3.1 Deviations between old and new data
Note: Blue represents higher estimates at L&V1
Becker, London Conference on Intelligence, 12-14 May 2017
London
28
Fig.14 Correlations between absolute mean country latitude (CIA, 2017)
and IQ-var.
3. Review
3.2 Bias or not?
Ind. var.
r
L&V1 .59
P&V .58
P&V(SPM) .45
P&V(CPM) .69
L&V1 –
P&V* -.17
L&V1 –
P&V(SPM) .01
L&V1 –
P&V(CPM) -.06
-15.00
-10.00
-5.00
0.00
5.00
10.00
15.00
20.00
25.00
0.00 20.00 40.00 60.00 80.00
Abs. mean country latitude
* Dependent variable
in plot
Becker, London Conference on Intelligence, 12-14 May 2017
London
29
Fig.15 Correlations between real mean country latitude (CIA, 2017) and
IQ-variables
3. Review
3.2 Bias or not?
Ind. var.
r
L&V1 .44
P&V .43
P&V(SPM) .31
P&V(CPM) .45
L&V1 –
P&V* -.10
L&V1 –
P&V(SPM) .06
L&V1 –
P&V(CPM) -.02
* Dependent variable
in plot
-15.00
-10.00
-5.00
0.00
5.00
10.00
15.00
20.00
25.00
-80.00 -40.00 0.00 40.00 80.00
Real mean country latitude
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Fig.16 Correlations between mean country skin color (Biasutti, 1967) and
IQ-variables
3. Review
3.2 Bias or not?
Ind. var.
r
L&V1 -.83
P&V -.74
P&V(SPM) -.71
P&V(CPM) -.79
L&V1 –
P&V* .10
L&V1 –
P&V(SPM) .01
L&V1 –
P&V(CPM) -.03
* Dependent variable
in plot
-15.00
-10.00
-5.00
0.00
5.00
10.00
15.00
20.00
25.00
10.00 15.00 20.00 25.00 30.00 35.00
Mean country skin color
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31
Fig.17 Correlations between PPP-GNI 08 (US$) (Lynn & Vanhanen, 2012)
and IQ-var.
3. Review
3.2 Bias or not?
Ind. var.
r
L&V1 .58
P&V .55
P&V(SPM) .57
P&V(CPM) .63
L&V1 –
P&V* -.13
L&V1 –
P&V(SPM) -.27
L&V1 –
P&V(CPM) .04
* Dependent variable
in plot
-15.00
-10.00
-5.00
0.00
5.00
10.00
15.00
20.00
25.00
0.00 50000.00 100000.00
PPP-GNI 08 (US$)
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To Do List
- Finding causes for extreme deviations (mostly CPM)
- Unsuitable norms?
- Differences in testing conditions?
- Age-effects (mean age SPM = 12.25y; mean age CPM = 8.83y)
- What has not yet been thought of?
- Further adjustments and corrections
- Differences in national age-structures
- Attention to sample origin (urban > rural; schooling > non-schooling)
- Estimation of data quality and representativeness
- Extension of the data set
- Inclusion of other sources (~830 stored sources still unchecked)
- Inclusion of other tests (Wechsler; CRT; school assessment tests etc.)
- Extension for sup-populations (sexes, ethnicities, immigrants etc.)
3. Review
3.3 What‘s next?
Becker, London Conference on Intelligence, 12-14 May 2017
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3. Review
3.3 What‘s next?
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Batterjee, A. A. (2011). Intelligence and education: The Saudi case.
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Quarterly, 52,
133-190.
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Le razze e i popoli della terra.
Rom: Unione Tipografico.
CIA (2017). The World Fact Book. Geographic coordinates. https://www.cia.gov/
library/publications/the-world-factbook/fields/2011.html#rs
Hunt, E., & Sternberg, R. J. (2006). Sorry, wrong numbers: An analysis of a study
of a correlation between skin color and IQ.
Intelligence, 34,
131-137.
doi:10.1016/j.intell.2005.04.004
Lynn, R., Pagliari, C., & Chan, J. (1988). Intelligence in Hong Kong measured for
Spearman's g and the visuospatial and verbal primaries.
Intelligence, 12,
423-433. doi:10.1016/0160-2896(88)90005-0
Lynn, R., & Vanhanen, T. (2012).
Intelligence. A Unifying Construct for the Social
Sciences.
London: Ulster Institute for Social Research.
McDaniel, M. A. (2008). Book review. R. Lynn & T. Vanhanen (2006). IQ and
global inequality.
Intelligence, 36,
731-732. doi:10.1016/j.intell.2008.03.003
Wicherts, J. M., Dolan, C. V., & van der Maas, H. L. J. (2010). A systematic
literature review of the average IQ of sub-Saharan Africans.
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1-20. doi:10.1016/j.intell.2009.05.002
4. References
34
Becker, London Conference on Intelligence, 12-14 May 2017
London
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Measures of formal schooling are closely related to cognitive ability. Other socioeconomic factors also influence individual and national IQ, and the differences between nations in wealth, health, technological innovation, attitudes and values, economic development and political maturity are correlated with differences in the average IQ of the population. Using results from the application of the Standard Progressive Matrices (SPM) to a sample from the Saudi general education system (N= 3209), the mean IQ for Saudi Arabia is calculated to be 80.6 ± 11.1 according to British norms. The results of this study are compared with those of an earlier study in Saudi Arabia (Abu Hatab et al., 1977). This comparison shows IQ gains ("Flynn effects") for many of the younger, but not the oldest age groups. Analysis of IQ differences between public and private schools, and comparison of different age groups, indicate that children who are educated in the public school system of Saudi Arabia show an age-related IQ decline relative to children in Britain and the United States, on whom the SPM test was normed for different age groups. The study also shows that the better performance of females, combined with a significant effect of mothers' education on children's IQ, could strengthen the role of females in the society in the near future.
Article
On the basis of several reviews of the literature, Lynn [Lynn, R., (2006). Race differences in intelligence: An evolutionary analysis. Augusta, GA: Washington Summit Publishers.] and Lynn and Vanhanen [Lynn, R., & Vanhanen, T., (2006). IQ and global inequality. Augusta, GA: Washington Summit Publishers.] concluded that the average IQ of the Black population of sub-Saharan Africa lies below 70. In this paper, the authors systematically review published empirical data on the performance of Africans on the following IQ tests: Draw-A-Man (DAM) test, Kaufman-Assessment Battery for Children (K-ABC), the Wechsler scales (WAIS & WISC), and several other IQ tests (but not the Raven's tests). Inclusion and exclusion criteria are explicitly discussed. Results show that average IQ of Africans on these tests is approximately 82 when compared to UK norms. We provide estimates of the average IQ per country and estimates on the basis of alternative inclusion criteria. Our estimate of average IQ converges with the finding that national IQs of sub-Saharan African countries as predicted from several international studies of student achievement are around 82. It is suggested that this estimate should be considered in light of the Flynn Effect. It is concluded that more psychometric studies are needed to address the issue of measurement bias of western IQ tests for Africans.
Article
Values for Spearman's g for Hong Kong are calculated from data derived from the administration of Raven's Standard Progressive Matrices to several thousand children. The results indicate that the mean IQ in Hong Kong for the mid 1980s is approximately 108 in relation to a Caucasian mean of 100 for the United States and the United Kingdom. Values for the spatial and perceptual speed primaries are also substantially higher in Hong Kong. On the other hand Hong Kong children are relatively weak on the word fluency primary. The pattern of abilities of Chinese Hong Kong children is broadly similar to that obtained on other Mongoloid populations.
Article
We argue that the report by Templer and Arikawa contains misleading conclusions and is based upon faulty collection and analysis of data. The report fails to hold up for quality of data, statistical analysis, and the logic of science.
Le razze e i popoli della terra
  • R Biasutti
Biasutti, R. (1967). Le razze e i popoli della terra. Rom: Unione Tipografico.
The World Fact Book. Geographic coordinates
CIA (2017). The World Fact Book. Geographic coordinates. https://www.cia.gov/ library/publications/the-world-factbook/fields/2011.html#rs
Intelligence. A Unifying Construct for the Social Sciences
  • R Lynn
  • T Vanhanen
Lynn, R., & Vanhanen, T. (2012). Intelligence. A Unifying Construct for the Social Sciences. London: Ulster Institute for Social Research.
IQ and global inequality
  • M A Mcdaniel
McDaniel, M. A. (2008). Book review. R. Lynn & T. Vanhanen (2006). IQ and global inequality. Intelligence, 36, 731-732. doi:10.1016/j.intell.2008.03.003