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Statistical Methods in Neuroimage Analysis

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    • Category : Medical Sciences & Pharmacy > Medicine
    • Keyword : Gaussian kernel,Type-I error,Type-II error,Adler?s formulation,Sparse regression
    • Taught by : Mookyung Chung
    • Created By : Seoul National University
    • Offered By : KOCW
    • Date Added : 2016.12.26

    The focus of the course is on the learning modern statistical methodology. R and MATLAB will be used as a language of instruction. The following topics will be covered: general linear model, likelihood estimation methods, nonparametric test procedures, multiple comparisons, false discovery rates, random field theory, permutation tests, logistic regression, longitudinal growth model, mixed effect model, discriminant analysis, multivariate test procedures

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Number of lessons: 9 facebook twitter line whatsapp kakaotalk

차시별 강의
No Contents Type & Play Subject Description URL
1. Type docunent Subject Description
  • This is an orientation of the course
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2. Type docunent Subject Description
  • This lecture examines the application of Gaussian kernel smoothing in the radom fields.
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3. Type docunent Subject Description
  • This lecture examines various random fields of imaging errors.
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4. Type docunent Subject Description
  • This lecture examines various random fields of imaging errors.
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5. Type docunent Subject Description
  • This lecture examines various random fields of imaging errors.
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6. Type docunent Subject Description
  • This lecture examines various random fields of imaging errors.
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7. Type docunent Subject Description
  • This lecture examines the principles of subcortical structure modeling with SurfStat.
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8. Type docunent Subject Description
  • This lecture examines the principles of cortical asymmetry analysis through sparse regression.
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9. Type docunent Subject Description
  • This is an final exam of the course
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