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Educational guide | |||||||||||||||||||||||||||||||||||||||
IDENTIFYING DATA | 2024_25 | |||||||||||||||||||||||||||||||||||||||
Subject | STATISTICS II | Code | 00508013 | |||||||||||||||||||||||||||||||||||||
Study programme |
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Descriptors | Credit. | Type | Year | Period | ||||||||||||||||||||||||||||||||||||
6 | Compulsory | Second | First |
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Language |
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Prerequisites | ||||||||||||||||||||||||||||||||||||||||
Department | ECONOMIA Y ESTADISTICA |
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Coordinador |
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pblaa@unileon.es msoma@unileon.es |
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Lecturers |
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Web | http:// | |||||||||||||||||||||||||||||||||||||||
General description | Probability models. Sampling and inferential statistics. Parametric estimation and hypothesis testing. Non-parametric tests. | |||||||||||||||||||||||||||||||||||||||
Tribunales de Revisión |
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Competencias |
Code | |
A19163 | |
A19165 | |
A19169 | |
B5847 | |
B5848 | |
B5852 | |
B5853 | |
B5857 | |
B5858 | |
C2 | CMECES2 That students know how to apply their knowledge to their work or vocation in a professional manner and possess the skills that are usually demonstrated through the development and defense of arguments and the resolution of problems within their area of study. |
C3 | CMECES3 That students have the ability to gather and interpret relevant data (normally within their area of study) to make judgments that include reflection on relevant issues of a social, scientific or ethical nature. |
Learning aims |
Competences | |||
A19169 |
B5848 B5852 B5857 |
C2 C3 |
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A19165 |
B5847 B5848 B5852 B5857 B5858 |
C2 |
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A19169 |
B5847 B5848 B5852 B5853 B5857 B5858 |
C3 |
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A19163 A19169 |
B5847 B5848 B5852 B5857 B5858 |
C2 C3 |
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A19163 A19169 |
B5848 B5852 B5857 B5858 |
C2 C3 |
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A19165 |
B5857 B5858 |
C2 C3 |
Contents |
Topic | Sub-topic |
INTRODUCTION TO STATISTICAL INFERENCE | UNIT 1. PROBABILITY MODELS 1. Probability theory and random variables (revision) 2. Discrete probability models 3. Continuous probability models UNIT 2. SAMPLING: SAMPLE STATISTICS AND THEIR DISTRIBUTIONS 1. Statistical inference: concept and classification 2. Sampling methods 3. Sampling distributions 4. Sample statistics and their sampling distribution |
PARAMETER ESTIMATION | UNIT 3. ESTIMATION 1. Estimation: parameters, estimators and estimates 2. Properties of point estimators 3. Basic definitions 4. Pivot method 5. Confidence intervals of a single population 6. Sample-size determination |
HYPOTHESIS TESTING | UNIT 4. HYPOTHESIS TESTING 1. Basic concepts 2. Hypothesis test procedure 3. Hypothesis tests of a single population 4. Two population hypothesis tests 5. Hypothesis tests and confidence intervals UNIT 5. NON-PARAMETRIC TESTS 1. Tests for location 2. Tests for comparing two populations 3. Tests for contingency tables 4. Goodness of fit tests 5. Tests for randomness |
Planning |
Methodologies :: Tests | |||||||||
Class hours | Hours outside the classroom | Total hours | |||||||
Lecture | 15 | 22.5 | 37.5 | ||||||
Problem solving, classroom exercises | 15 | 22.5 | 37.5 | ||||||
Practicals using information and communication technologies (ICTs) in computer rooms | 15 | 22.5 | 37.5 | ||||||
Personal tuition | 5 | 5 | 10 | ||||||
Mixed tests | 6 | 18 | 24 | ||||||
Objective multiple-choice tests | 1 | 2.5 | 3.5 | ||||||
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Description | |
Lecture | |
Problem solving, classroom exercises | |
Practicals using information and communication technologies (ICTs) in computer rooms | |
Personal tuition |
Personalized attention |
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Assessment |
Description | Qualification | ||
Practicals using information and communication technologies (ICTs) in computer rooms | 2 | ||
Mixed tests | 6 | ||
Objective multiple-choice tests | 2 | ||
Other comments and second call | |||
Sources of information |
Access to Recommended Bibliography in the Catalog ULE |
Basic |
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Complementary |
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Recommendations |
Subjects that it is recommended to have taken before | |||
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Other comments | |
A certain level of competence in descriptive statistics and probability theory is required. Students should also be familiar with Microsoft Excel spreadsheets. |