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RM2 Lab report

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Abstract
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Nature versus nurture has been the debate amongst academia for decades. Many
academics debated biological sex differences regarding intelligence. Howard Gardner proposed
eight intellectual abilities; these were musical-rhythmic, visual-spatial, verbal-linguistic, logicalmathematical, bodily-kinesthetic, interpersonal, intrapersonal, and naturalistic (Slavin, 2009).
Questions such as whether men perform better at mathematics or women better at linguistics
arose by researcherse. Cattell (1943) proposed that there are two forms of intelligence:
crystallized and fluid. Crystallized intelligence was described as knowledge acquired through
experience, which could be demonstrated through one’s vocabulary and general knowledge.
However, Crystallized intelligence was not equated to long-term memory, though it was thought
to be required to access it. Fluid intelligence was described as the capacity to reason, identify
patterns and solve problems logically. It was not thought to require knowledge from the past.
Spatial Abilities
Spatial abilities are important for many everyday activities, including sports, navigation,
academic success in science, technology, engineering and mathematics (STEM; Jansen &
Lehmann, 2013; Labate, Pazzaglia, & Hegarty, 2014; Lubinski, 2010). Spatial abilities are
divided into two main dimensions with a 2 x 2 model proposed by Uttal, Miller, and Newcombe
(2013). They are static-dynamic and intrinsic-extrinsic; there are four types of spatial subabilities after combining the dimensions. Static-intrinsic involves the ability to perceive objects
in complex shapes, while static-extrinsic is the understanding of abstract spatial principles.
Dynamic-extrinsic is visualizing objects that occupy different locations in space, such as in
perspective-taking tasks. Dynamic-intrinsic involves mentally transforming objects, such as
mental rotation tasks that involve perceiving and rotating 2D or 3D objects (Scheer, Mattioni, &
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Jansen, 2018). Commonly, it requires one to perceive 3D objects with a 2D drawing in a mental
rotation test (MRT).
MRT
In an MRT, the participant is to compare a base-image of an object with other images.
Only one image has the same object but rotated on an axis, while others are mirrored or similar
images of the object to confuse the participant (Shepard & Metzler, 1971). The researcher judges
the participant’s accuracy and time to distinguish the images. On average, men performed better
than women (Linn & Petersen, 1985; Voyer & Voyer, 1995). However, a recent study of MRT
that used eye-tracking methods and electroencephalography (EEG) behavioral analysis showed
there were no differences in reaction time nor in the accuracy rate between men and women
(Scheer et al., 2018). However, a crucial limitation of this study was the small sample of
participants: 15 men and 15 women. A larger sample size was needed to for the findings to be
more convincing. Nonetheless, Scheer et al.’s study indicated that men tended to use a holistic
strategy and women a piecemeal strategy while performing the MRT. Thus, this finding shows
there are differences between sex in processing spatial tasks.
Fluid Intelligence
Cattell (1943) described fluid intelligence as the ability to discriminate and perceive relations
between any new or old fundaments, such as lines, dots, patterns and shapes. It is also the ability
to recognize patterns and provide solutions through inductive and deductive reasoning. During
his research with children’s intelligence tests, Cattell discovered that fluid intelligence does not
require prior knowledge or experience. This ability peaks until adolescence and then deteriorates
slowly.
Cattell’s Culture Fair Intelligence Test (CCFIT)
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Cattell developed the CCFIT to eliminate social, cultural and environmental factors. The
test consists of non-verbal visual puzzles. It requires participants to solve mazes, copy symbols,
identify sequences and fill in the blanks for the missing images (Domino & Domino, 2006). A
study found that men obtain higher intelligence quotient (IQ) scores than women (Halpern &
Lamay, 2000). However, research has shown that there are no significant sex differences in
CCFIT scores (Colom & García-López, 2002; Đapo & Kolenović,-Đapo, 2012; D. F. Halpern &
Tan, 2001). That contrasts Halpern and Lamay’s research and a meta-analysis of 22 studies by
Irwing and Lynn (2005) that shows men obtain higher IQ scores than women.
Aim and Hypotheses
Our research aims to measure and compare men and women’s MRT and CCFIT scores in an
Australian sample. From the mentioned literature, we predict that (1) men will score higher than
women in MRT, and (2) men and women will have no significant difference in CCFIT.
Additionally, a study that consisted of exclusively women participants found no correlation
between MRT and CCFIT scores (Meneghetti, Cardillo, Mammarella, & Caviola, 2017). We aim
to further Meneghetti et al.’s study and conduct it with men and women. Hence, (3) we predict
there will be no correlation between MRT and CCFIT scores.
Method
Participants
We used the Horlin (2018) dataset made available by a researcher at the School of Psychology,
University of Glasgow. This dataset consisted of 205 participants’ information. There were 32
men, 107 women and 66 unspecified (mean±SD; men, 22±2 year; women 21±3 year). Data of
participants who had missing information would be removed from this study, such as sex, CCFIT
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scores or MRT scores. 120 participants were included from the initial pool (26 men and 94
women). No other demographics measures were used.
Measures
The participants in the Horlin (2018) dataset took the MRT test that consists of two 10-item
sessions with three minutes for each section (Parsons et al., 2004). Each item presents four threedimensional target drawings of an arrangement of blocks and a reference-drawing. Participants
were asked to select the two alternatives, which presented the same arrangement of blocks as the
reference-drawing but in a randomly rotated manner. Participants could score 2 points for both
correct answers, 1 point for one correct answer with the other not selected, or 0 points for either
one or both incorrect answers. The sum of the scores from each item is the total score, which
ranges from 0 to 40.
The same participants also took the subtest-3 in the CCFIT test, this consisted of 96
questions and each question is scored differently (Domino & Domino, 2006). CCFIT has a
standard deviation of 24, main bell curve range of 85-115 and the average range is 76-124. This
is different to most IQ tests which use a standard deviation of 15 that has a median of 100 (Essa
et al., 2016).
Preparations and Assumptions
Four assumptions were made prior to receiving the Horlin (2018) dataset. 1) The data collected
are interval/ratio, 2) the data collected are independent, 3) the data are normally distributed, and
4) there is homogeneity of variance between the groups. We decided that if the data fails
assumptions one and two, we will stop this study as the data would not be valid or reliable. If the
data fails assumption three, we will examine the histogram but continue the study. If the data
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fails assumption four, we will conduct a Welch t-test. Additionally, if there are any missing data
from the Horlin (2018) dataset, these participants will be removed from the study.
Statistical Analysis
Since there were no time-of-completion data for either tests in the dataset, there will be no
comparisons for reaction time.
Descriptive Statistics
This study will calculate the following descriptive statistics, grouped by the factor of sex,
for MRT and CCFIT scores: mean, standard deviation, maximum, minimum, median, degrees of
freedom, Cohen’s d, p-value, and t-value. Two histograms and violin-box plots for MRT and
CCFIT will be produced for visualizing distribution.
Inferential Statistics
This study will carry out two t-test calculations for MRT and CCFIT for men versus
women to compare their mean scores and significance. Additionally, this study will carry out
Pearson’s correlation test between MRT and CCFIT scores to examine their relationship. A linear
regression plot will be produced for the relation between MRT and CCFIT scores.
Software Used
All calculations will be carried out in R.studio using the following packages: “tidyverse”,
“broom” and “ggpubr”.
Results
Pre-registration
All hypotheses, descriptive, and inferential analyses were pre-registered except for hypothesis
(2) and t-test for CCFIT (see Appendix B).
Assumptions
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The Horlin (2018) dataset is interval data and each sample are independent of others. As
illustrated in Figure 1, 2, 3 and 4, the data is normally distributed. The Levene’s test (see
Appendix A) showed that the data does not have homogeneity of variance between groups.
Hence, Welch t-test was used in this study.
Figure 1. The distribution of participants’ total score of CCFIT.
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Figure 2. The distribution of participants’ total score of MRT.
Figure 3. Violin boxplot of men and women’s total scores for CCFIT.
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Figure 4. Violin boxplot of men and women’s total scores for MRT.
The mean score of men was significantly greater than the mean score of women in MRT
(Table 1). This supports hypothesis 1 which stated that men would perform better than women in
MRT. The mean scores between men and women showed no significant difference in CCFIT
(Table 1). This supports hypothesis 2 which stated that there would be no significant difference
in men and women’s performance in CCFIT. Interesting to note that the maximum and minimum
scores for men and women in both tests were similar and their maximum scores for both tests
were equal.
Table 1
Significance report between men (n = 26) and women (n = 94) for MRT and CCFIT
Test
M
SD
df
t
p
Men
Women
Men
Women
MRT
17.15
12.41
5.30
42.2
4.74
< .001*
4.96
CCFIT
32.27
30.94
4.65
4.11
36.5
1.33
0.19**
*Note: The means for men and women in MRT are significant (p < .05).
** Note: The means for men and women in CCFIT are insignificant (p > .05).
d
0.92
0.30
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Table 2
The median, maximum and minimum scores for MRT and CCFIT
Test
MRT
CCFIT
Median
Men
Women
17.5
12
33
31
Maximum
Men
Women
24
24
39
39
Minimum
Men
Women
8
2
18
22
We found a medium, significant, positive correlation between MRT (M = 13.44, SD
= 5.57) and CCFIT (M = 31.23, SD = 4.25, r(120) = 0.41, p < .001, see Table 3 and Figure 5,
Borenstein & Cohen, 1988). This rejects hypothesis 3 which stated that there will be no
correlation between MRT and CCFIT scores.
Table 3
Pearson’s correlations among MRT and CCFIT
MRT
CCFIT
MRT
0.41*
CCFIT
0.41*
*Note: Correlation is medium significant.
p
< .001
< .001
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Figure 5. Scatter plot showing correlation and linear regression between MRT scores and CCFIT
scores.
Discussion
The results show that men did better than women in MRT and had no significant
difference in CCFIT between men and women. The effect size is large and small for MRT and
CCFIT t-tests, respectively. Both of these results agree with previous research (Colom & GarcíaLópez, 2002; Đapo & Kolenović,-Đapo, 2012; D. F. Halpern & Tan, 2001; Linn & Petersen,
1985; Voyer & Voyer, 1995). There is a medium correlation between MRT and CCFIT scores
which was unexpected which contrasts previous study by Meneghetti et al. (2017). A possible
explanation to the contrast is the study by Meneghetti et al. consisted of only women. The lack of
data of men might cause the authors to have type II error. A type II error occurs when the null
hypothesis is false but the researchers failed to reject it (Shermer, 2002).
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Previous research show that there is no significant sex differences in CCFIT scores
(Colom & García-López, 2002; Đapo & Kolenović,-Đapo, 2012; D. F. Halpern & Tan, 2001).
However, that does not imply individuals with better spatial abilities would not have an
advantage in CCFIT. This indicates, though not strong since the correlation is medium, that
participants with high spatial abilities can be benefited in CCFIT. Both groups managed to
achieve the same highest scores for MRT. This indicates that, though the mean is significantly
different in MRT, the statistics does not reflect the entirety of the individual abilities.
Scheer et al.’s (2018) study stated the different strategies used by men and women in
MRT; men tend to use a holistic strategy and women use a piecemeal strategy. This indicates that
there is no best strategy to solve the CCFIT questions as there are no significant sex differences.
It is possible that we had overestimated the sex differences in MRT and underestimated the
similarities between MRT and CCFIT in the hypothesizing stage.
There are many limitations in this study. First, the amount of available data (n=120) is
small and the lack of data of men might have affected the results. Second, the sample data was
collected from Australia. This study cannot draw cultural inferences due to the lack of cross
cultured data. Third, the participants’ reaction time and time of completion of both tests were not
available. The difference in strategies between men and women might achieve similar results in
both tests. However, one strategy may complete the tests with a shorter amount of time than the
other. Fourth, the participant’s background information, such as interests, upbringing, strengths,
weaknesses and academic performance were not provided. This information may add more
insight into the nature versus nurture aspect.
Men and women have differences. However, individual differences also contribute to
difference performances. Nonetheless, it is improbable to factor individual differences into this
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study due to the limitations. It is crucial to note that CCFIT scores had no sex difference. CCFIT
may be a more reliable IQ test. Additionally, the sex differences in MRT scores were small,
which does not affect MRT’s utility. The relationship between special abilities and fluid
intelligence should be further explored. The eight intelligence abilities (Slavin, 2009) may be
more interconnected than researchers had assumed. Future studies should collect data from
different cultures, record the reaction and completion time and collect background information to
gain a wider perspective in this area.
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References
Last Name, F. M. (Year). Article Title. Journal Title, Pages From - To.
Last Name, F. M. (Year). Book Title. City Name: Publisher Name.
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Footnotes
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Tables
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Figures title:
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Category 1
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Series 1
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Series 3
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