| Educational guide Faculty of Business and Economics |
english |
| Bachelor's Degree in Business Administration and Management (2009) |
 Subjects |
| STATISTICS II |
| Contents |
| IDENTIFYING DATA | 2023_24 |
| Subject | STATISTICS II | Code | 16214104 | |||||
| Study programme |
|
Cycle | 1st | |||||
| Descriptors | Credits | Type | Year | Period | ||||
| 6 | Compulsory | Second | 2Q |
|||||
| Competences | Learning outcomes | Contents |
| Planning | Methodologies | Personalized attention |
| Assessment | Sources of information | Recommendations |
| Topic | Sub-topic |
| 0. INTRODUCCION TO PROBABILITY | 0.1. Random experiments, sample spaces and events 0.2. Algebra of events 0.3. Probability spaces 0.4. Conditional probability 0.5. Independent events 0.6. Total probability theorem 0.7. Bayes' theorem |
| 1. ONE-DIMENSIONAL RANDOM VARIABLES | 1.1. Discrete random variables 1.1.1. Probability function (quantity). Properties 1.1.2. Distribution function. Properties 1.2. Continuous random variables 1.2.1. Distribution function. Properties 1.2.2. Density function. Properties CHARACTERISTICS OF RANDOM VARIABLES 1.3. Expectation of a random variable. Properties 1.4. Moments about origin and about mean 1.5. Variance of a random variable. Properties 1.6. Chebitchev inequality |
| 2. PROBABILITY DISTRIBUTION MODELS | 2.1. DISCRETE DISTRIBUTIONS 2.1.1. Discrete uniform distribution 2.1.2. Bernoulli distribution 2.1.3. Binomial distribution 2.1.4. Hypergeometric distribution 2.1.5. Poisson distribution 2.2. CONTINUOUS DISTRIBUTIONS 2.2.1. Uniform distribution 2.2.2. Exponential distribution |
| 3. NORMAL DISTRIBUTION AND RELATED DISTRIBUTIONS | 3.1. Definition. Standardized normal 3.2. Properties. Use of tables 3.3. Approximation of the binomial by the normal 3.4. Importance of the normal distribution: central limit theorem 3.5. Distributions related to normal 3.5.1. Student's t-distribution 3.5.2. Chi square distribution 3.5.3. F de Snedecor distribution |
| 4. SAMPLING. SAMPLE DISTRIBUTIONS | 4.1. Sampling. Types of sampling 4.2. Population parameters and sample statistics 4.3. Sampling error 4.4. Sample distribution of the average sample statistic 4.5. Distribution of variance and sample quasivariance 4.6. Distribution of other sample statistics |
| 5. ESTIMATION THEORY | 5.1. Classical conception of estimation PUNCTUAL ESTIMATION 5.2. Concept of estimator 5.3. Desirable properties of estimators 5.3.1. Non-biased estimators 5.3.2. Efficient estimators 5.3.3. Asymptotic properties INTERVAL ESTIMATION 5.4. Concept of confidence interval 5.5. Determination of some confidence intervals |
| 6. PARAMETRIC HYPOTHESIS TESTING | 6.1. General approach. Basics 6.2. Types of statistical hypotheses 6.3. Test statistic. Critical region 6.4. Types of error 6.5. Significance level. p-value 6.6. Contrasts between mean and difference in averages 6.7. Contrasts between variance and difference in variances 6.8. Contrasts over proportions and differences in proportions |
| 7. INTRODUCTION TO ECONOMETRICS | 7.1 Simple linear regression model. Adjustment for ordinary least squares 7.2 Parameter hypothesis contracts |
