'Sided tests' presentation slideshows

Hypothesis Testing

Hypothesis Testing. Presenting: Lihu Berman. Agenda. Basic concepts Neyman-Pearson lemma UMP Invariance CFAR. X is a random vector with distribution. is a parameter, belonging to the parameter space. disjoint covering of the parameter space. denotes the hypothesis that.

848 views • 43 slides

Krisztina Boda PhD Department of Medical Informatics, University of Szeged

Biostatistics, statistical software V . Statistical errors, one-and two sided tests. One-way and multifactor analysis of variance. Krisztina Boda PhD Department of Medical Informatics, University of Szeged. One- and two tailed (sided) tests. Two tailed test H 0 : there is no change

492 views • 35 slides

Hypothesis Testing

322 views • 21 slides

Lecture 4

Lecture 4. Main Tasks Today 1. Review of Lecture 3. 2. Accuracy of the LS estimators 3. Significance Tests of the Parameters 4. Confidence Interval. 5. Prediction and Prediction Interval. Review of Lecture 3. The LS- Estimators of and :. Properties :.

287 views • 20 slides

284 views • 14 slides

147 views • 14 slides