Problem Description
Despite global concerns about students' declining performance in mathematics and science, there is a pressing need to investigate the role of reading proficiency in data analysis assignment. The study seeks to address whether students' reading abilities significantly impact their achievements in mathematics and science. Analyzing PISA data and applying statistical methods, we aim to uncover the relationship between reading skills and scholastic performance, offering insights for educational improvements worldwide.
Introduction
Education systems worldwide have been grappling with students' underwhelming results in mathematics and science exams over the past decade. Recent research suggests that reading comprehension can play a vital role in improving students' performance in these subjects. To address this issue, innovative teaching strategies are needed. The Program for International Student Assessment (PISA) conducted by the Organization for Economic Cooperation and Development (OECD) provides valuable data to explore the impact of reading abilities on students' mathematics and science scores. In this study, we aim to investigate how students' reading performance influences their achievements in mathematics and science.
Aim and Research Questions
Research questions:
 Is there a significant difference in the average reading performance between male and female students?
 Do students' reading performance, mathematics scores, and science scores significantly differ?
 Does students' reading performance significantly affect their mathematics performance?
Descriptive Statistics
We utilized four main variables from the PISA dataset to summarize our findings:
 Math score
 Minimum: 261.12
 Maximum: 727.45
 Mean: 492.44
 Median: 493.42
 Standard deviation: 83.80
 Science score
 Minimum: 253.60
 Maximum: 786.08
 Mean: 512.14
 Median: 514.08
 Standard deviation: 93.86
 Reading Performance
 Minimum: 222.50
 Maximum: 795.86
 Mean: 516.65
 Median: 519.50
 Standard deviation: 100.79
Furthermore, we looked at the distribution of students by gender:
 Gender
 Female: 496 (49.6%)
 Male: 504 (50.4%)
Hypotheses
To address our research questions, we tested the following hypotheses:
 Null Hypothesis 1: There is no significant difference in average reading performance between male and female students.
 Alternative Hypothesis 1: There is a significant difference in average reading performance between male and female students.
 Null Hypothesis 2: There is no significant difference between students' average reading performance, math scores, and science scores.
 Alternative Hypothesis 2: There is a significant difference between students' average reading performance, math scores, and science scores.
 Null Hypothesis 3: There is no significant linear relationship between students' mathematics scores and their reading performance, gender, attitude toward school, subjective wellbeing, and perception of the difficulty of the PISA test.
 Alternative Hypothesis 3: There is a significant linear relationship between students' mathematics scores and their reading performance, gender, attitude toward school, subjective wellbeing, and perception of the difficulty of the PISA test.
Inferential Statistics
We performed an independent ttest to investigate the difference in average reading performance between male and female students. The results showed a significant difference (p = .002) in average reading performance between the two genders.

SEX  95% CI  

Male  Female  t  df  Lower  Upper  
Reading Performance  506.92 (102.93) 
526.53 (97.68) 
3.09  998  7.149  32.060 
 Table 1: Comparison of students’ average reading performance between gender
An ANOVA was conducted to explore the differences in students' average reading performance, math scores, and science scores. The results revealed a significant difference (p < .001) between the groups. Posthoc tests showed that students' reading and science scores belonged to one homogeneous group, while math scores formed another group.
Performance  Sum of Squares  df  Mean Square  F  pvalue 

Between Groups  331430.302  2  165715.151  19.127  .000 
Within Groups  25965285.577  2997  8663.759  
Total  26296715.878  2999 
 Table 2: Comparison of students’ average reading performance, math scores, and science scores
 Figure 1: Mean plot of the students’ subject performance.
Multiple linear regression was employed to examine the impact of reading performance on students' mathematics scores. The results indicated a strong positive relationship between reading performance and math scores. Moreover, gender significantly affected mathematics scores, while attitude toward school, subjective wellbeing, and perception of the PISA test's difficulty did not.
 Figure 2: Scatter plot of the relationship between the student's reading performance and math score
The scatter plot indicated a strong positive relationship between the student's reading performance and math score. The table below showed the summary of the regression results;
Variables  Coefficient  Std. Error  tvalue  pvalue 

(Constant)  71.089  14.797  4.804  .000 
Reading  .753  .013  57.151  .000 
Sex  26.859  2.369  11.338  .000 
Attitude  .903  .547  1.650  .099 
Well_being  .031  .627  .049  .961 
Difficulty  .318  .663  .479  .632 
Fvalue = 839.87, p<0.001, Rsquare = 0.809
The Fvalue in the ANOVA table tests whether the overall regression model is a good fit for the data. The table showed a significant linear relationship between the students' mathematics scores and their reading performance, gender, attitude towards school, subjective wellbeing, and perception of the difficulty of the PISA test [F (5, 994) = 839.87, p < .001]. The model is significant.
Conclusion
This study delved into the relationship between students' reading performance and their achievements in mathematics and science. The analysis of PISA data revealed significant differences in reading performance between genders and among subjects. It also showed that reading performance strongly influences mathematics scores. These findings emphasize the importance of reading comprehension in enhancing students' scholastic performance in mathematics and science, providing valuable insights for educators and policymakers.