# Fundamentals of Data Analysis

Learning outcomes of the course unit:

After completion of course student should

1. optimally design and assemble the measuring system

2. properly proceed measurements

3. identify sources of measurement errors

4. interpret the results of statistical tests

5. carry out statistical analysis of measurement results and errors

6. properly collect and present the results of the measurements

1.What is inductive reasoning?

2.What is deductive reasoning?

3.What do we mean by measurement?

4.What is the null hypothesis?

5.What is the alternative hypothesis?

6.Give the definition of error.

7.Characterize types of errors.

8.What are the measures of errors?

9.Whatis an estimate?

11.When the estimator is consistent?

12.When the estimate is sufficient?

13.What is the point estimate?

14.What is the interval estimation?

15.Why do we use the method of maximum likelihood?

16.Define correlation.

17.Define the regression.

18.How to create a correlation diagram?

19.How to create correlation table?

20.What conditions must be met to apply the analysis of variance?

21.What are the ways to increase the precision of measurements?

22.Why do we use the analysis of co-variance?

•  Lecture 1 Pobierz
•  Lecture 2 Pobierz
•  Lecture 3 Pobierz
•  Lecture 4 Pobierz
•  Lecture 5 Pobierz
•  Lecture 6 Pobierz
•  Lecture 7 Pobierz
•  Lecture 8 Pobierz
•  Lecture 9 Pobierz
•  Lecture 10 Pobierz
•  Lecture 11 Pobierz
•  Lecture 12 Pobierz
•  Lecture 13 Pobierz
•  Table for Dixons Test Pobierz
•  Tables for Grubbs Tests Pobierz