Elements of descriptive statistics. Elements of probability and random variables. Introduction to point estimation theory and confidence intervals. Introduction to the theory of hypothesis testing.
Course Content - Last names D-L
Descriptive statstics: data collection and description. Measures of central tendency and measures of variability or dispersion. Elements of probability, random variables. Introduction to point estimation and interval estimation. Introduction to hypothesis testing.
Course Content - Last names M-P
Descriptive statstics: data collection and description. Measures of central tendency and measures of variability or dispersion. Elements of probability, random variables. Introduction to point estimation and interval estimation. Introduction to hypothesis testing.
Course Content - Last names Q-Z
Elements of descriptive statistics. Elements of probability and random variables. Introduction to point estimation theory and confidence intervals. Introduction to the theory of hypothesis testing.
P. Newbold, W.L. Carlson, B. Thorne. Statistica. 2007, Pearson / Prentice Hall.
Learning Objectives - Last names A-C
The course has been designed to acquaint the student with basic theory of statistics, survey and data analysis.
Learning Objectives - Last names D-L
Learn to understand the main features of statistics.
Learn how to analyze statistical data properly. Understand the role of formal statistical theory and informal data analytic methods.
Gain an understanding of statistical methods relevant to economics and busness.
Sharpen students statistical intuition and abstract reasoning as well as their reasoning from numerical data through examples.
Learning Objectives - Last names M-P
Learn to understand the main features of statistics.
Learn how to analyze statistical data properly. Understand the role of formal statistical theory and informal data analytic methods.
Gain an understanding of statistical methods relevant to economics and busness.
Sharpen students statistical intuition and abstract reasoning as well as their reasoning from numerical data through examples.
Learning Objectives - Last names Q-Z
The course has been designed to acquaint the student with basic theory of statistics, survey and data analysis.
Prerequisites - Last names A-C
none
Prerequisites - Last names D-L
None
Prerequisites - Last names M-P
None
Prerequisites - Last names Q-Z
none.
Teaching Methods - Last names A-C
Classroom lessons.
Teaching Methods - Last names D-L
Frontal lessons
Teaching Methods - Last names M-P
Frontal lessons
Teaching Methods - Last names Q-Z
Classroom lessons.
Further information - Last names A-C
course web page
e-l.unifi.it
Home page:
http://local.disia.unifi.it/gmm/stateco.html
Further information - Last names D-L
Moodle e-learning platform: http://e-l.unifi.it/
Further information - Last names M-P
Moodle e-learning platform: http://e-l.unifi.it/
Further information - Last names Q-Z
e-learning Moodle
Type of Assessment - Last names A-C
Written and oral examination.
Type of Assessment - Last names D-L
Written and oral examination. The admission to the oral exam requires to pass the written exam.
Type of Assessment - Last names M-P
Written and oral examination. The admission to the oral exam requires to pass the written exam.
Type of Assessment - Last names Q-Z
Written and oral examination.
Course program - Last names A-C
Definitions (population, statistical units, sample, variables, methods). Graphs and tables: classification of variables, frequency tables, graphics, cumulative frequencies, bivariate tables. Measures of central tendency: arithmetic mean, median, mode, geometric mean. Variability: range, interquartile range, quartiles, quantiles, box-plots, variance, standard deviation, coefficient of variation. Relationship between variables: covariance and correlation and linear regression. Random experiments. The probability and its axioms, rules of probability. Bivariate probability, Bayes' theorem. Probability distributions and discrete random variables.
Properties of discrete random variables. Binomial distribution. Joint distribution of two discrete random variables. Continuous random variables. Expected values of continuous random variables. Uniform distribution. Normal distribution. Approximation to the binomial distribution with the normal distribution. Joint distribution of two continuous random variables. Sampling from a population. Distribution of the sample mean and the sample proportion.
Properties of the estimators. Confidence intervals for the mean: variance known, variance unknown. Confidence intervals for proportions (large samples). Determination of the sample size. Hypothesis testing on a single population.
Course program - Last names D-L
Definitions (population, statistical units, sample, variables, methods). Graphs and tables: classification of variables, frequency tables, graphics, cumulative frequencies, bivariate tables. Measures of central tendency: arithmetic mean, median, mode, geometric mean. Variability: range, interquartile range, quartiles, quantiles, box-plots, variance, standard deviation, coefficient of variation. Relationship between variables: covariance and correlation and linear regression. Random experiments. The probability and its axioms, rules of probability. Bivariate probability, Bayes' theorem. Probability distributions and discrete random variables.
Properties of discrete random variables. Binomial distribution. Joint distribution of two discrete random variables. Continuous random variables. Expected values of continuous random variables. Uniform distribution. Normal distribution. Approximation to the binomial distribution with the normal distribution. Joint distribution of two continuous random variables. Sampling from a population. Distribution of the sample mean and the sample proportion.
Properties of the estimators. Confidence intervals for the mean: variance known, variance unknown. Confidence intervals for proportions (large samples). Determination of the sample size. Hypothesis testing on a single population.
Course program - Last names Q-Z
Definitions (population, statistical units, sample, variables, methods). Graphs and tables: classification of variables, frequency tables, graphics, cumulative frequencies, bivariate tables. Measures of central tendency: arithmetic mean, median, mode, geometric mean. Variability: range, interquartile range, quartiles, quantiles, box-plots, variance, standard deviation, coefficient of variation. Relationship between variables: covariance and correlation and linear regression. Random experiments. The probability and its axioms, rules of probability. Bivariate probability, Bayes' theorem. Probability distributions and discrete random variables.
Properties of discrete random variables. Binomial distribution. Hypergeometric distribution. Joint distribution of two discrete random variables. Continuous random variables. Expected values of continuous random variables. Uniform distribution. Normal distribution. Approximation to the binomial distribution with the normal distribution. Joint distribution of two continuous random variables. Sampling from a population. Distribution of the sample mean and the sample proportion.
Properties of the estimators. Confidence intervals for the mean: variance known, variance unknown. Confidence intervals for proportions (large samples). Determination of the sample size. Hypothesis testing on a single population.