Investigating relationships between student marks and majors taken. A descriptive and inferential statistics using SAS - Telford, Nicholas Scott;Nkongolo, Mike
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Project Report from the year 2016 in the subject Mathematics - Statistics, grade: Bsc (Hons), , course: Data Analysis And Exploration IV, language: English, abstract: Our investigation set out to determine if there was a relationship between the number of majors a student took and their likely achievement. We cleaned the data, removing missing values and unnecessary attributes. We then transformed the data and performed statistical tests to acquire both descriptive and inferential statistics. Our investigation discovered the association between majors taken and results obtained. Students…mehr

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Produktbeschreibung
Project Report from the year 2016 in the subject Mathematics - Statistics, grade: Bsc (Hons), , course: Data Analysis And Exploration IV, language: English, abstract: Our investigation set out to determine if there was a relationship between the number of majors a student took and their likely achievement. We cleaned the data, removing missing values and unnecessary attributes. We then transformed the data and performed statistical tests to acquire both descriptive and inferential statistics. Our investigation discovered the association between majors taken and results obtained. Students majoring only in applied maths were found to be more likely to pass than students doing a double major. In addition, students in different fields had different chances of succeeding. The University can now determine appropriate actions to take to increase its students' performance.
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Autorenporträt
Mike Nkongolo received the BSc (Hons) degree in computer science from the University of the Witwatersrand, Johannesburg, South Africa, in 2016. He is currently working toward the Masters degree in the School of Computer Science and Applied Mathematics, University of the Witwatersand. His research interests include the theory and applications of Intelligent Systems, Web-based platforms and Machine Learning, Sentiment detection in Web Mining, and Artificial Intelligence/Natural Languages Processing.