KSSTA Editor-in-Chief Jón Karlsson introduces a series on statistics to be published in KSSTA over the coming months. The series will include practical guidelines, underline important details in standard research statistics, and introduce newer concepts such as machine learning and deep learning. The series is intended to help authors do better research and increase the quality of their articles.
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Subject number
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Title
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1
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P-Values and Associated Misinterpretation
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2
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Sample Size Calculations
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3
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Fragility Index, How to Calculate it, And How it Can Shape Research
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4
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Mean, Median, Mode – How distributions can influence scientific messages
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5
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Multivariate vs Multiple Regression, A common source of confusion
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6
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Survival Curves, Cox-Proportional Hazards, and Assumptions (Competing Risks?)
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7
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Machine Learning
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8
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Supervised Machine Learning – Associated Algorithms
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9
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Unsupervised Machine Learning – Value and Pitfalls
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10
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Reinforcement Machine Learning – The Holy Grail?
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11
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Overfitting in ML – the most common mistake
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12
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Deep Learning – foundations in computer vision, NLP, etc
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