Statistical Theory for Data Analysis  097414





Lecture 
Exercise 
Laboratory 
Project or Seminar 
House Work 
Weekly Hours 
2 
1 

1 
4 

Determination of the grade according to progress during the semester and a final examination.
Prerequisites:
 
(
  Introductio to Data Science 
094201
 
  
and
 Introduction to Statistics 
094423
 ) 

or

(
  Introduction to Statistics 
094423
 
  
and
 Introduction to Computer Science N 
234221
 ) 

or

(
  Introduction to Statistics 
094423
 
  
and
 Introduction to Data Science and Engin. 
094700
 ) 
The Course Will Cover a Variety of Statistical Theory Topics Combined with Data Analysis. the Course Topics Include Multivariate Regression, Generalized Regression, NonParametric Statistics and ReSampling Methods, Decision Theory, Bayesian Statistics and and Methods of Handling Missing Data. at the End of the Course, the Students Will Be:
1. Able to Use Different Regression Methods
2. to Perform Statistical Inference on Datasets of Various Types Including Handling Missing Data.
Times and places of examinations
02/2020
2020/2021 Spring Semester
examination time  day  date  Season 

 Friday  30.07.2021  à 
 Tuesday  12.10.2021  á 
Timetable to semester 02/2020
2020/2021 Spring Semester
Room  Building  Hour  day  Lecturer  Exercise Lecture  no.  Registering Group 

  08:3010:30  Wednesday  Associate Professor Goldberg Yair  Lecture  10  11 
     Project  11 
  10:3011:30  Wednesday  Mr. Madmon Oron  Exercise  11 

  08:3010:30  Wednesday  Associate Professor Goldberg Yair  Lecture  10  12 
     Project  12 
  14:3015:30  Monday  Mr. Madmon Oron  Exercise  12 
TextbooksPublished  Publisher  Authors  Book 

2004  springer  larry wasserman  all of statistics a concise course in statistical inference 
2002  wiley  roderick j.a. little, donald b. rubin  statistical analysis with missing data 
Created in 06/03/2021 Time 01:42:23