OVERVIEW OF THE TOPIC
Intelligence Quotient Index and related terms
Human intelligence is a defining characteristic that distinguishes Homo sapiens from other species, contributing to our success on the planet It encompasses abilities such as language, cultural development and transmission, reasoning, hypothesis testing, and comprehension of rules.
For much of the twentieth century, the psychological exploration of human intelligence concentrated on understanding the variations in intelligence among individuals It wasn't until the rise of cognitive psychology in the 1960s that researchers began to shift their focus towards the commonalities of human intelligence, exploring what unites people rather than what differentiates them.
Intelligence is assessed through intelligence tests that evaluate various cognitive abilities, including verbal reasoning, non-verbal reasoning, mental arithmetic, vocabulary, verbal comprehension, as well as perceptual, spatial, and memory skills (Mackintosh, 2011).
The total score derived from these several standardized tests designed to assess human intelligence is called Intelligence Quotient (IQ) Index
Intelligence test scores are measured on a scale where the average IQ is 100, with a standard deviation of 15 This means that about 96% of the population scores between 70 and 130 Notably, the highest recorded IQs are around 200 (de Jong and Das Smaal, 1995).
Theoretical Background
Intelligence quotient (IQ) is influenced by both genetic and non-genetic factors, with genetics playing a significant role While IQ tests are generally reliable for individuals aged ten and older, variations can occur, as approximately 25% of individuals may show a 10-point difference when taking different IQ tests at the same age Factors such as specific knowledge, vocabulary, expressive language, memory skills, visual-spatial abilities, fine motor coordination, and perceptual skills contribute to these variations Additionally, emotional factors like anxiety, tension, and unfamiliarity with the testing process can also impact IQ scores (Mackintosh, 2011).
The determination of IQ is influenced by a complex interplay of genetic and environmental factors, with studies suggesting that genetics account for approximately 50% of cognitive ability, a percentage that increases with age Environmental influences, including socioeconomic status and education, contribute around 45%, with shared environments accounting for 25% and non-shared environments for 20% Malnutrition has been shown to negatively impact IQ, while enriched environments can enhance cognitive performance Additionally, factors such as gender, religion, previous GPA, and height play a role in shaping both genetic and environmental influences on intelligence.
Our genetic makeup influences our brain volume, structure, and pathways, setting a baseline for intelligence; however, our achievements in intelligence are not solely determined by biology The lifestyle we lead plays a significant role in shaping our cognitive abilities (Gonzales et al., 1996).
MODEL SPECIFICATION
Methodology in the study
2.1.1 Method to derive the model
Our research employs Multiple Linear Regression to model the statistical relationship between a dependent variable and multiple independent variables Specifically, we analyze how the Intelligence Quotient Index is influenced by factors such as Gender, Height, and Religion.
2.1.2 Method to collect and analyze the data
2.1.2.1 Method to collect the data
This study aims to assess the factors influencing the Intelligence Quotient (IQ) of FTU students during the 2018-2019 academic year A random sample of 90 students was selected from this population to ensure a representative cross-section The data for this analysis was collected through a survey conducted among the participants.
2.1.2.2 Method to analyze the data
In order to analyze the dataset and interpret the correlation matrix between variables, we use STATA
Theoretical model specification
Having considering previous research as well as theoretical background, our group has built a function to analyze the influences of some factor on Intelligence Quotient Index:
Intelligence Quotient Index= f(Gender, Height, GPA, Religion)
With a view to determining the effects of these above- mentioned factors on Intelligence Quotient Index, our group decided to choose the regression analysis models
Intelligence Quotient Index i = β0 + β1 Genderi+ β 2 Heighti + β3 GPAi + β4
The model includes an intercept term (β0) and regression coefficients for various factors: Gender (β1), Height (β2), GPA (β3), and Religion (β4) Additionally, the disturbance term (εi) accounts for the Intelligence Quotient Index, although these factors are not explicitly included in the model.
Intelligence Quotient Index = + Gender+ Height+ ̂GPA +
: the estimator of β 1 :the estimator of β 2 ̂: the estimator of β3
: the estimator of ài- residual
- Dependent variable is Intelligence Quotinent (IQ), which is ranged from 1 to 10 in the questionnaire
No, i do not have any religion: 1
Variable GPA: The score is measured in number, it’s positive and the maximum is 4.0
2.2.3 Description of the data 2.2.3.1 Source of data
No Variable Obs Mean Std Dev Min Max
In order to analyze the correlation between the variables, we run corr IQIndex Gender GPA Religion Height
IQIndex Gender GPA Religion Height IQIndex 1.0000 0.1016 0.8621 0.1264 0.3082
Gender has a positive but pretty low correlation coefficient of 0.1016
Therefore, it has a positive effect on the dependent variable IQIndex
GPA has a positive and extremely high correlation coefficient of 0.8621
Threfore, it has a positive effect on the dependent variable IQIndex, Religion has a positive but pretty low correlation coefficient of 0.1016
Therefore, it has a positive effect on the dependent variable IQIndex
Height has a medium correlation coefficient of 0.3082 Therefore, it has a positive effect on the dependent variable IQIndex
SECTION3:ESTIMATED MODEL AND STATISTICAL INFERENCE
Estimated model
Variables Coefficient T P-value Confidence interval (95%) Constant -5.770058 -11.16 0.000 [-0.3532235; 0.3758733]
Intelligence Quotient Index i = + Gender i + Height i + GPA i
According to the estimated result from STATA and the Ordinary least squares (OLS) method, we obtained the sample regression model:
Intelligence Quotient Index i = -5.770058 +0.113249 Gender i + 0.267508 Height i + 3.045011 GPA i + 0.3290625 Religion i +
R 2 is 0.8547 means that the estimated model explains 85.47% of the total variation in the value of Intelligence Quotient Index in this sample
3.1.4 Meanings of estimated coefficients ̂ = -5.770058 means that if all 4 independent variables equal zero, the measurement ̂ = 0.267508 > 0 means that holding other factors fixed, when Height increases by 1 unit of measurement, the expected Intelligence Quotient Index increases by 0.267508 unit of measurement ̂= 3.045011 > 0 means that holding other factors fixed, when GPA increases by 1.0 point , the expected Intelligence Quotient Index increases by 3.045011 unit of measurement ̂= 0.3290625 > 0 means that holding other factors fixed, when you don’t have any religion, the expected Intelligence Quotient Index increases by 0.3290625 unit of measurement
The sum of squared residuals (RSS) is 34.4189844, indicating the sample variation in the data The standard error for the Gender variable is 0.1833497, suggesting that the average distance between the observations and the regression line is approximately 18%.
Similar with GPA, Religion and Height variable, the distance are about 15%, 4% and 51% respectively
3.2.1 Verifying the suitability of individual regression coefficient
Intelligence Quotient Index i = β 0 + β 1 Gender i + β 2 Height i + β 3 GPA i + β 4 Religion i + à i
Ts To verify the suitability of individual regression coefficient we use STATA and achieve the result as below:
+ P-value of Gender is 0.951 so P Gender > α (α = 5%)
At 5% level of significance, we accept the hypothesis and reject
At 5% level of significance, the estimated coefficient is not statistically significant
At 5% level of significance, Gender does not actually affect Intelligence Quotient index
+ P-value of Height variable is 0.000 so PHeight < α (α = 5%)
At 5% level of significance, we reject the hypothesis and accept
At 5% level of significance, the estimated coefficient is statistically significant
At 5% level of significance, Height does affect Intelligence Quotient index
+ P-value of GPA is 0.000 so PGPA < α (α = 5%)
At 5% level of significance, we reject the hypothesis and accept
At 5% level of significance, the estimated coefficient is statistically significant
At 5% level of significance, GPA does affect Intelligence Quotient
+ P-value of religion is 0.041, so Preligion