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B000365 - STATISTICS
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Further information
Type of Assessment
Course program
Academic Year 2010-11
Course year
Second year - First Semester
Belonging Department
Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)
Course Type
Single education field course
Scientific Area
SECS-S/01 - STATISTICS
Credits
9
Teaching Hours
60
Teaching Term
04/10/2010 ⇒ 22/12/2010
Attendance required
No
Type of Evaluation
Final Grade
Course Content
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Course program
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Lectureship
- Last names A-K PETRUCCI ALESSANDRA
- Last names L-Z PETRUCCI ALESSANDRA
Teaching Language - Last names A-K
italian
Course Content - Last names A-K
Probability; Probability distributions: Bernoulli, Binomial, Normal, t-Student, Chi-square; Sampling distributions; Statistical inference: point and interval estimation, Comparison between two groups; Association measures between variables: descriptive and inferential approaches; Functional and statistical relationship between two variables; Linear regression; Introduction to multivariate analysis.
Suggested readings - Last names A-K (Search our library's catalogue)
Agresti Alan e Finlay Barbara (2009) "Statistica per le scienze sociali". Pearson, Prentice Hall.
Borra Simone e Di Ciaccio Agostino (2008) "Statistica. Metodologie per le scienze economiche e sociali". Seconda Edizione. McGraw-Hill
Borra Simone e Di Ciaccio Agostino (2008) "Statistica. Metodologie per le scienze economiche e sociali". Seconda Edizione. McGraw-Hill
Learning Objectives - Last names A-K
Understanding the relationship between random variables and their distributions. Being able to use the basic tools of statistical inference (estimation, comparison of two groups, etc..) Build and evaluate a simple regression model. Analysing a two-way and three-way contingency table.
Prerequisites - Last names A-K
no one
Teaching Methods - Last names A-K
LESSONS AND PRACTICE IN CLASSROOM
Further information - Last names A-K
no one
Type of Assessment - Last names A-K
WRITTEN EXAMINATION AND ORAL DEFENSE
Course program - Last names A-K
Introduction to probability: primitive concepts; Events and event algebra; Postulates of probability; Measure of the probability approach classical conditional probability and independence. Random variables, probability distributions for discrete variables and continuous probability, Normal distribution, Outline of probability distributions: Chi-square, t-Student-and F-Fisher.; Central limit theorem.
Sample statistics and sampling distributions, the distribution of the sample mean. Point estimate and estimator; properties of estimators; Point Estimation of the population mean, Point estimation of variance of the population. Confidence interval for the proportion, confidence interval for the mean; Determination of sample size.
Comparisons of two groups: Comparing two proportions; Comparing two means; Comparing averages for dependent samples.
Association between categorical variable: contingency tables, chi-square test of independence; investigate the association structure by residual analysis; Measuring association in contingency tables.
Statistical and functional relationship between two variables, specification of simple linear regression model, point estimates of regression coefficients, the decomposition of the total variance and the linear coefficient of determination, coefficient of determination.
Sample statistics and sampling distributions, the distribution of the sample mean. Point estimate and estimator; properties of estimators; Point Estimation of the population mean, Point estimation of variance of the population. Confidence interval for the proportion, confidence interval for the mean; Determination of sample size.
Comparisons of two groups: Comparing two proportions; Comparing two means; Comparing averages for dependent samples.
Association between categorical variable: contingency tables, chi-square test of independence; investigate the association structure by residual analysis; Measuring association in contingency tables.
Statistical and functional relationship between two variables, specification of simple linear regression model, point estimates of regression coefficients, the decomposition of the total variance and the linear coefficient of determination, coefficient of determination.