Course code: 252201  Subject title: STATISTICS  
Credits: 6  Type of subject: Basic  Year: 1  Period: 2º S  
Department:  
Lecturers:  
UGARTE MARTINEZ, M. DOLORES (Resp) [Mentoring ] 
Descriptive statistics, probability, statistical inference.
Descriptive statistics and statistical software R will be dealt with through the whole course.
R1. To perform descriptive statistical analysis to databases.
R2. To apply appropriate statistical treatments according to the nature of the statistical variables in databases.
R3. To use a statistical package for statistical analysis of databases and simulation results of random phenomena.
R4. To recognize the main probability distributions, both discrete and continuous, together with methods general of probability.
R5. To use statistical tools to adequately estimate the unknown model parameters raised in engineering by methods of point estimation and intervals.
R6. To learn statistical techniques for facilitating the process of decision making in uncertain environment.
Methodology  Activity 
Attendance 
Selfstudy 
A1 Lectures 
45 

A2 Practical classes 
15 

A3 Selfstudy 
75 

A4 Exams, tests, and tutorial 
15 

Total 
75 
75 
Learning outcomes 
Evaluation activities 
Weight 
Recovery character 
R1, R3, R4, R5, R6 
Final Exam (a minimun of 5 over 10 is necessary to overcome this part) 
60% 
Yes, second exam 
R1, R2 
Evaluation proofs 
30% 
No 
R6 
Monitoring proofs and active participation in class 
10% 
No 
1.Exploring Data
Displaying Qualitative and Quantitative Data
Measures of Location and Spread
Bivariate and Multivariate data
2. General Probability and Random Variables
Counting Techniques (a review)
Axiomatic Probability
Discrete and Continuous Random Variables
3. Univariate probability distribution
Discrete and Continuous Univariate Probability Distributions
6. Sampling and Sampling Distributions
Sampling
Parameters
Estimators
Sampling Distribution of the Sample Mean, Sample Variance and Sample Proportion
Sampling Distributions Associated with the Normal Distribution
7. Point Estimation and Confidence Intervals
Properties of Point Estimators
Confidence Intervals
8.Hypothesis Testing
Type I and Type II Errors
Power Function
Uniformly Most Powerful Test
pValue or Critical Level
Tests of Significance
9. Introduction to modeling in statistics
Access the bibliography that your professor has requested from the Library.
TEXTBOOK:
Ugarte, M. D., Militino, A. F., Arnholt, A. T. (2016). Probability and Statistics with R. Second Edition. CRC Press/Chapman and Hall.
OTHER BOOKS:
Devore, J. (2005) Applied statistics for engineers and scientists. Thomson