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
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 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
The course has been designed to acquaint the student with basic theory of statistics, survey and data analysis.
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 Q-Z
none.
Teaching Methods - Last names A-C
Classroom lessons.
Teaching Methods - Last names D-L
classroom lessons
Teaching Methods - Last names Q-Z
Classroom lessons.
Further information - Last names A-C
course web page
Further information - Last names D-L
course web page
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.
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. 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.
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. 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.
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.