Analysis of Environmental and Genetic Factors on General Intelligence

This report investigates the impact of environmental and genetic factors on general intelligence (GI). The study utilizes a dataset encompassing variables like ID, age, GI, years of higher education (YOE), genetic polymorphism (TRM), MKM, and secondary school education scores (SSEQ-E and SSEQ-S). Descriptive and regression analyses are performed using SPSS to identify the influence of these variables on GI. The analysis includes checking data suitability, identifying outliers, and assessing linear relationships and multicollinearity. The results indicate a medium impact of independent variables on GI, with age acting as a significant moderator. The report also examines the relationship between TRM and GI, moderated by secondary school education quality (QE). Findings suggest that both genetic and environmental factors, particularly age and educational background, significantly affect GI levels. The research aligns with previous studies, emphasizing the importance of providing quality education to enhance students' GI. Statistical analysis confirms the relevance of moderation models.

IMPACT OF ENVIRONMENTAL FACTORS AND
GENETIC FACTORS ON GENERAL INTELLIGENCE

TABLE OF CONTENTS
Introduction......................................................................................................................................1
Checking of suitability of data for analysis.....................................................................................1
Descriptive analysis and regression analysis...................................................................................2
Moderator variable age and relationship between GI and 5 IV.......................................................3
Relationship between TRM and GI along with QE.........................................................................4
Discussion section............................................................................................................................5
Conclusion.......................................................................................................................................6

Introduction
In past few years lots of research is done on general intelligence by scientists. In past time
period many researches are carried out in respect to intelligence and different results were
obtained on them. In the current research report an attempt is made to identify the impact that
genetic factors and environment in which children grow have on their intelligence level. In
respect to this data set is taken in to account which encompass variables like ID, age, general
intelligence (GI), YOE (Year of higher education), TRM (Genetic polymorphism), MKM,
SSEQ-E (Secondary school education score measured by tool) and SSEQ-S (Secondary school
education score measured sample units at their own level).
Varied tools like regression analysis and descriptive analysis will be used to analyse data
and to identify whether five variables have significant impact on general intelligence level of
individuals or sample units. Hence, it can be said that scope of present research study is wide and
lots of facts will be identified from results that will be generated from SPSS software. There is
sample of 500 people which indicate that sufficient sample units are taken for research purpose.
Hence, there will be very high reliability of results that will be generated in the current research
work.
In order to deep dive more in research work between variables moderator variable is also
taken in to account so that accurate conclusions can be deduced from the research work. Detailed
analysis of data done and discussion section is prepared. In this way, entire research work will be
carried out in the present research study.
Checking of suitability of data for analysis
In order to ensure that data is suitable for analysis first of all outliers present in the data were
identified through box plot chart and same were removed manually in SPSS. Thereafter scatter
chart was prepared to identify linear relationship between variables. It is first of assumption that
is checked in multiple regression. Second, assumption for multiple regression is that there must
not be multi-collinearity between independent variables. In order to check this assumption
correlation table is prepared in SPSS and strong relationship is not identified between
independent variables. Third, assumption is that there must be homoscedasticity between
variables. Means that data or scatter points representing X and Y must be near to upward slope.
In this regard, scatter chart is prepared in SPSS and it is identified that scatter points are very
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close to slope line. By doing so it is ensured that there is no outliers and results will not be
affected by same. Apart from this, measures were taken to identify whether data was normally
distributed. These were two steps that were taken to ensure that data quality was perfect and it
can be used without any problem. Thus, it can be said that data is normally distributed.
Descriptive analysis and regression analysis
Minimum age of the sample unit is 18 and maximum age is 27. Average mean value is 22
which indicate that sample units taken in the sample have an average age of 22. Standard
deviation is 2 for age. GI statistic are (MAX =87, MIN = 35, M = 59.76, SD = 9.9) which indicate
that most of sample units have average GI of 35). There is same statistic for QE and QS (MIN =
1, MAX = 5, M = 2.52 for QE and 2.5540 for QS, SD = 1.41 for QE and 1.40 for QS). In case of
TRM and MKM value of statistic is (MIN = 0.00, MAX = 1, M = 0.50 for TRM and 0.4940 for
MKM, SD = 0.50). Thus, it can be said that there are almost same results in case of TRM and
MKM as well as QE and QS).
Table 1
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .485a .236 .228 8.70534
a. Predictors: (Constant), yoe, mkm, qs, trm, qe
b. Dependent Variable: GI
Table 2
ANOVA
Model Sum of
Squares
df Mean
Square
F Sig.
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Regression 11534.807 5 2306.961 30.442 .000b
Residual 37436.815 494 75.783
Total 48971.622 499
a. Dependent Variable: GI
b. Predictors: (Constant), yoe, mkm, qs, trm, qe
Regression analysis
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H0: There is no significant impact of independent variables on general intelligence of subjects.
H1: There is significant impact of independent variables on general intelligence of subjects.
Interpretation
It can be seen from the Table 1 that value of statistic is (R = 0.485, R2 = 0.236, p=
0.00<0.05) which reflect that there is medium impact of independent variable on the dependent
variable. Value of (R2 = 0.236) in Table 1 which means that due to change in independent
variable 23% variation comes in dependent variable. In Table 2 value of level of significance is
(p = 0.00) which indicate that there is significant impact of independent variable on dependent
variable. Hence, alternative hypothesis accepted. Coefficient value (TRM = 2.873, MKM = -
3.466, QE = 2.324, QS = 0.097 and YOE =0.381). This is indicating that with change in TRM
GI will be changed by 2.87, with change in MKM GI will be changed by -3.466 which means
that if MKM value increase GI will decline. QE coefficient is 2.324 which means that with
change in QE GI will be changed by 2.32 points. In case of QE and QS value of coefficient is
0.097 and 0.381 which is indicating that with change in these two variables any big change
cannot be seen in GI.
Moderator variable age and relationship between GI and 5 IV
H0: There is no significant impact of age along with four IV on GI.
H1: There is significant impact of age along with four IV on GI.
Table 3
ANOVA
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 11534.807 5 2306.961 30.442 .000b
Residual 37436.815 494 75.783
Total 48971.622 499
2
Regression 12076.774 6 2012.796 26.896 .000c
Residual 36894.848 493 74.837
Total 48971.622 499
a. Dependent Variable: GI
b. Predictors: (Constant), yoe, mkm, qs, trm, qe
c. Predictors: (Constant), yoe, mkm, qs, trm, qe, age
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Interpretation
In regression model variable age is added. Effect is not independent of age as it can be
seen that value of level of significance is (p = 0.00) in Table 3 which is indicating that age have
significant impact on the results of the model. Value of statistic (R =0.497, R2 = 0.247, p = 0.00)
which is indicating that with change in independent variable significant change is observed in
GI. (R = 0.497) which indicate that there is moderate relationship between variables. 24% of
variation on GI is explained by independent variable. 0.707 is coefficient value of GI to age
which is indicating that 70% variation may come in GI due to IV. Hence, alternative hypothesis
accepted.
Relationship between TRM and GI along with QE
H0: There is no significant impact of TRM on GI on moderation of SSEQ-Q
H1: There is significant impact of TRM on GI on moderation of SSEQ-Q
Table 4
ANOVA
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 4743.109 1 4743.109 53.406 .000b
Residual 44228.513 498 88.812
Total 48971.622 499
2
Regression 10378.154 2 5189.077 66.824 .000c
Residual 38593.468 497 77.653
Total 48971.622 499
a. Dependent Variable: GI
b. Predictors: (Constant), trm
c. Predictors: (Constant), trm, qe
Interpretation
Value of level of significance is (p = 0.00) in Table 4 which is indicating that QE have
moderated impact on the relationship of QE on GI. Value of (R=0.311 in case of TRM and GI
and R = 0.460) which is indicating that on moderation of variable QE relationship become
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stronger among these variables. Value of (R2 = 0.097 and after moderation value of R2= 0.212)
which again reflect that with inclusion of moderator variable in model now 21% of variation in
dependent variable can be explained which was just 9% without including moderator variable in
the model. Value of level of significance (p = 0.00<0.05) in case of both models which indicate
that without and with inclusion of QE in every condition there is significant impact of IV on DV.
Hence, alternative hypothesis accepted.
Discussion section
In past time period also, researchers make an attempt to identify impact of genetic and
environment factors on general intelligence level of human being. In these research study focuses
was on identifying similarity and difference in general intelligence within family members.
Results of these studies revealed that there was 50% difference in general intelligence level on
individuals (Plomin and Deary, 2015). In these research studies it was also identified that
environmental factors also have strong influence on the intelligence level of human beings.
Means that environment that child see at his home, school and colleges, parenting, availability of
resources and nutrition level, all of these factors have impact on children general intelligence
level. Research results indicated that both genetic and environmental factors have impact on GI.
In most of cases value of P is less then 0.05 for most of IV. Hence, it is clear that both category
(Genetic and environmental factors) have impact on the GI. Thus, it can be said that research
results match to same of past research studies. Age is the one of the most important factor that
greatly affect GI. This is because with increase in age individual understanding about varied
things also increase (Kovacs. and Conway, 2016). Thus, this lead to increase in GI. QE or
secondary school education quality determine study background of individuals. Hence, it can be
said that environmental factor has great impact on GI. Hence, if good environment can be made
available to the students then in that case their GI can be increased rapidly. Overall, it can be said
that current research result matched to the past results. Genetic factors not doubt have impact on
the student GI level but environment specially of schools also have a huge impact on student GI
level. Schools and colleges must ensure that they are making available quality of education to
their students. It is also observed that there is medium correlation between DV and IV even there
is presence or absence of moderator variable in model. So, moderation model must always be
used for statistical analysis.
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Conclusion
On the basis of above discussion, it is concluded that there is significant impact of genetic
and environmental factor on the general intelligence level of individuals. It is also concluded that
some of the factors like age and secondary school background seems to be irrelevant for research
but they have significant impact on GI.
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