Analysis of Critical Thinking Skills in Decision Making with R Project in Mathematical Statistics Course

Rani Farida Sinaga; Lolyta Damora Simbolon; Efron Manik; Sofy Kristiani Manalu

doi:10.36312/panthera.v6i1.1122

Authors

Rani Farida Sinaga Mathematics Education Study Program, Faculty of Teacher Training and Education, HKBP Nommensen University, Sutomo Street Number 4A, Medan, North Sumatera 20235, Indonesia
Lolyta Damora Simbolon Mathematics Education Study Program, Faculty of Teacher Training and Education, HKBP Nommensen University, Sutomo Street Number 4A, Medan, North Sumatera 20235, Indonesia
Efron Manik Mathematics Education Study Program, Faculty of Teacher Training and Education, HKBP Nommensen University, Sutomo Street Number 4A, Medan, North Sumatera 20235, Indonesia
Sofy Kristiani Manalu Mathematics Education Study Program, Faculty of Teacher Training and Education, HKBP Nommensen University, Sutomo Street Number 4A, Medan, North Sumatera 20235, Indonesia

DOI:

https://doi.org/10.36312/panthera.v6i1.1122

Keywords:

Critical Thinking, Decision Making, Mathematical Statistics, Quantitative Study, R Project Software

Abstract

This study aims to analyze how the use of R Project Software in mathematical statistics courses can contribute to improving students' critical thinking skills, especially in the context of data-based decision making. Indicators of critical thinking in decision making with R Project: 1) interpretation (can write what is known and asked in the question clearly or identify the problem correctly); 2) analysis (can write what must be done in solving the problem); 3) inference (can draw conclusions from what is asked logically and visualize the results); 4) evaluation (can write down the solution to the problem and build a model to evaluate alternatives); and 5) explanation (can provide reasons for the conclusions drawn). The research method uses a descriptive quantitative approach. This research has a population of 80 students with a sample size of 40 students using non-probability sampling with the purposive sampling technique. By using a significance level of 5% and a df value of nk = 40 - 2 = 38, the t_table value is 1.686. The t_count value of 3.383 exceeds the t_table value of 1.686, indicating that the null hypothesis is rejected at a 95% confidence level. And, keep the abstract concise by stating only the conclusion of the statistical test (significant positive effect). Thus, R Project can be recommended as a natural analysis tool for learning mathematical statistics.

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