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Course Description
This course is designed to help students master and analyze the substance of content and processes in statistics as well as apply and present data from statistical testing results oriented towards active, innovative, creative, effective and adaptive science and technology learning in the context of problem solving. The material provided includes basic concepts of statistics, sampling and population, variables, and measurement scales (ordinal, nominal, interval, ratio); presentation of statistical data; data reliability and validity; parametric statistics and nonparametric statistics; descriptive statistics: frequency distribution, graphical presentation, central tendency, variability, normal distribution; inferential statistics: probability, sampling distribution, recommendations, z test, t test, chi-square test; Statistical test of data using Microsoft Excel and SPSS. This course aims to provide understanding and skills regarding descriptive statistical theory, measurement scales, central tendency, statistical test requirements, parametric and non-parametric statistics and statistical analysis using SPSS. Lectures are carried out by providing material, introducing statistical applications in the form of SPSS and then practicing calculating using the SPSS application. indicators of success are that students are able to map research using statistical calculations, students are able to apply statistics to research, and students can use the SPSS application well
Program Objectives (PO)
- Analisis konsep dan prosedur penelitian agar Anda mampu merancang dan melaksanakan penelitian di bidang Pendidikan Non-formal secara kritis, kreatif, kolaboratif, komunikatif, terampil dalam teknologi informasi (TI), serta memiliki integritas dan karakter (C4).
- Evaluasi keterampilan untuk melaksanakan langkah-langkah dalam melakukan penelitian dalam desain penelitian (C5)
- Mengidentifikasi sikap positif untuk berpartisipasi dalam proses belajar dengan baik (A5)
Aktifitas Pembelajaran
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Pertemuan 1 Ruang lingkup dan penggunaan statistik dalam pendidikan -
Pertemuan 2 Pemahaman tentang skala pengukuran data (nominal, ordinal, interval, dan rasio). -
Pertemuan 3 Pemahaman tentang daftar distribusi frekuensi, grafik, dan diagram -
Pertemuan 4 Besarnya variasi -
Pertemuan 5 Pemahaman tentang Probabilitas dan distribusinya, kurva, serta distribusi normal standar. -
Pertemuan 6 Pemahaman tentang persyaratan uji statistik parametrik -
Pertemuan 7 Pemahaman tentang persyaratan uji t parametrik -
Pertemuan 8 Pemahaman tentang uji persyaratan statistik parametrik Pearson untuk korelasi momen produk -
Pertemuan 9 Pemahaman tentang uji korelasi momen produk Pearson, penentuan, tabel r -
Pertemuan 10 Pemahaman tentang perbedaan antara dua rata-rata (uji t), tabel distribusi t-Student -
Pertemuan 11 Pemahaman tentang Analisis Varians Sederhana -
Pertemuan 12 Pemahaman tentang Uji Kruskal-Wallis (ANOVA satu arah sederhana untuk statistik non-parametrik) -
Pertemuan 13 Pemahaman tentang uji korelasi peringkat Spearman (rho) dan uji tanda (T) -
Pertemuan 14 Pemahaman tentang Uji Wilcoxon dan Uji Mann-Whitney (uji perbedaan antara dua rata-rata dalam statistik nonparametrik), Tabel U Mann-Whitney. -
Pertemuan 15 Pemahaman tentang penggunaan Teknologi Informasi dan Komunikasi (TIK) dalam menganalisis statistik -
Pertemuan 16 Memiliki pemahaman yang komprehensif tentang pengujian dalam statistik.
References
- Casella, G., & Berger, R. L. (2020). Statistical Inference (2nd ed.). Cengage Learning.
- Rice, J. A. (2020). Mathematical Statistics and Data Analysis (3rd ed.). Cengage Learning.
- Montgomery, D. C., & Runger, G. C. (2021). Applied Statistics and Probability for Engineers (7th ed.). Wiley.
- YUSUF, A. (2025). PENGARUH LITERASI DAN NUMERASI TERHADAP PRESTASI TES ASESMEN NASIONAL BERBASIS KOMPUTER (ANBK). ALFARISI: Jurnal Pendidikan MIPA, 7(2).
- Efron, B., & Hastie, T. (2021). Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press.
- Agresti, A. (2021). Statistical Methods for the Social Sciences (5th ed.). Pearson. Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (2020). Discrete Multivariate Analysis: Theory and Practice. MIT Press.
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning: with Applications in R (2nd ed.). Springer.
- Friedman, J., Hastie, T., & Tibshirani, R. (2020). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer.
- Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2021). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience.
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2020). Bayesian Data Analysis (3rd ed.). CRC Press.
- Hastie, T., Tibshirani, R., & Wainwright, M. (2021). Statistical Learning with Sparsity: The Lasso and Generalizations. CRC Press.
- Lehmann, E. L., & Romano, J. P. (2020). Testing Statistical Hypotheses (3rd ed.). Springer.
Lecturer
Difficult Things About Education.
$75$10
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