View courses by:
Faculty Subject Area Cycle (Bachelor / Master) Semester (Autumn/Spring)
| Field | Work language | Acad. cycle | ECTS credits | Semester | Course code |
|---|---|---|---|---|---|
| Economic | LV ENG | Bachelor | 3 | Spring | EkonP173 |
To provide knowledge about the issues of probability theory and about the role of statistics, the application of its methods in data processing.
To acquire elements of probability theory and calculation of probabilities of events. To acquire concepts of random variables and their distribution laws. To acquire skills in collecting, processing and analyzing measurement and statistical data, sampling and evaluate the parameters of the population with the characteristics of the sample. To find out the basic issues of correlations.
Knowledge
• Explains the concept “event” and event probability definitions.
• Explains event probability calculation formulas.
• Explains the concept of discrete and continuous, random variables.
• Explains the concept of discrete and continuous random variable distribution and the function of integral and differential distribution of random variables.
• Explains the characteristics of random variable - mathematical expectation (mean), variance, standard deviation, mode and median.
• Explains the distributions of continuous case sizes (uniform, normal, Poisson, etc.)
• Understands the basic tasks of mathematical statistics and explains the concepts of general and sample sets.
• Explains empirical distribution functions, series of variations, polygon, histogram construction.
• Understands the concept of confidence interval and defines its calculation formula.
• Explains the essence of linear and nonlinear regression - to find the relationship between factorial and resultant feature.
• Explains the significance of the correlation coefficient to characterize the closeness of the relationship between the factorial and outcome feature in the case of linear regression and the significance of the coefficient of determination () in the case of nonlinear regression.
• Understands the concept of statistical hypothesis. Outlines the main tasks of hypothesis testing; the null hypothesis and the alternative hypothesis in relation to the areas of acceptance (acceptance) and rejection of the named hypotheses, define the level of significance in the acceptance of hypotheses.
Skills
• Calculates the probabilities of occurrence of an event in the given examples.
• Apply the necessary formula to calculate the probabilities of the sum of given independent and dependent events.
• Selects the necessary formulas for calculating the probability of given disjoint and overlapping events.
• Finds the type of relationship and closeness between two features.
• Selects the necessary statistical methods to solve the problem.
Competences
• Evaluates the adequacy of theoretical knowledge and skills acquired in the course in solving tasks.
• Performs tasks according to the topic using IT tools, e.g., MS EXCEL.
• Evaluates the results of the solved task.
Submit solutions for all independent work tasks It is necessary to get a positive evaluation of the solution of each task
Tests and the exam should be passed
View courses by:
Faculty Subject Area Cycle (Bachelor / Master) Semester (Autumn/Spring)
| Field | Work language | Acad. cycle | ECTS credits | Semester | Course code |
|---|---|---|---|---|---|
| Economic | LV ENG | Bachelor | 3 | Spring | EkonP173 |
To provide knowledge about the issues of probability theory and about the role of statistics, the application of its methods in data processing.
To acquire elements of probability theory and calculation of probabilities of events. To acquire concepts of random variables and their distribution laws. To acquire skills in collecting, processing and analyzing measurement and statistical data, sampling and evaluate the parameters of the population with the characteristics of the sample. To find out the basic issues of correlations.
Knowledge
• Explains the concept “event” and event probability definitions.
• Explains event probability calculation formulas.
• Explains the concept of discrete and continuous, random variables.
• Explains the concept of discrete and continuous random variable distribution and the function of integral and differential distribution of random variables.
• Explains the characteristics of random variable - mathematical expectation (mean), variance, standard deviation, mode and median.
• Explains the distributions of continuous case sizes (uniform, normal, Poisson, etc.)
• Understands the basic tasks of mathematical statistics and explains the concepts of general and sample sets.
• Explains empirical distribution functions, series of variations, polygon, histogram construction.
• Understands the concept of confidence interval and defines its calculation formula.
• Explains the essence of linear and nonlinear regression - to find the relationship between factorial and resultant feature.
• Explains the significance of the correlation coefficient to characterize the closeness of the relationship between the factorial and outcome feature in the case of linear regression and the significance of the coefficient of determination () in the case of nonlinear regression.
• Understands the concept of statistical hypothesis. Outlines the main tasks of hypothesis testing; the null hypothesis and the alternative hypothesis in relation to the areas of acceptance (acceptance) and rejection of the named hypotheses, define the level of significance in the acceptance of hypotheses.
Skills
• Calculates the probabilities of occurrence of an event in the given examples.
• Apply the necessary formula to calculate the probabilities of the sum of given independent and dependent events.
• Selects the necessary formulas for calculating the probability of given disjoint and overlapping events.
• Finds the type of relationship and closeness between two features.
• Selects the necessary statistical methods to solve the problem.
Competences
• Evaluates the adequacy of theoretical knowledge and skills acquired in the course in solving tasks.
• Performs tasks according to the topic using IT tools, e.g., MS EXCEL.
• Evaluates the results of the solved task.
Submit solutions for all independent work tasks It is necessary to get a positive evaluation of the solution of each task
Tests and the exam should be passed
View courses by:
Faculty Subject Area Cycle (Bachelor / Master) Semester (Autumn/Spring)
| Field | Work language | Acad. cycle | ECTS credits | Semester | Course code |
|---|---|---|---|---|---|
| Economic | LV ENG | Bachelor | 3 | Spring | EkonP173 |
To provide knowledge about the issues of probability theory and about the role of statistics, the application of its methods in data processing.
To acquire elements of probability theory and calculation of probabilities of events. To acquire concepts of random variables and their distribution laws. To acquire skills in collecting, processing and analyzing measurement and statistical data, sampling and evaluate the parameters of the population with the characteristics of the sample. To find out the basic issues of correlations.
Knowledge
• Explains the concept “event” and event probability definitions.
• Explains event probability calculation formulas.
• Explains the concept of discrete and continuous, random variables.
• Explains the concept of discrete and continuous random variable distribution and the function of integral and differential distribution of random variables.
• Explains the characteristics of random variable - mathematical expectation (mean), variance, standard deviation, mode and median.
• Explains the distributions of continuous case sizes (uniform, normal, Poisson, etc.)
• Understands the basic tasks of mathematical statistics and explains the concepts of general and sample sets.
• Explains empirical distribution functions, series of variations, polygon, histogram construction.
• Understands the concept of confidence interval and defines its calculation formula.
• Explains the essence of linear and nonlinear regression - to find the relationship between factorial and resultant feature.
• Explains the significance of the correlation coefficient to characterize the closeness of the relationship between the factorial and outcome feature in the case of linear regression and the significance of the coefficient of determination () in the case of nonlinear regression.
• Understands the concept of statistical hypothesis. Outlines the main tasks of hypothesis testing; the null hypothesis and the alternative hypothesis in relation to the areas of acceptance (acceptance) and rejection of the named hypotheses, define the level of significance in the acceptance of hypotheses.
Skills
• Calculates the probabilities of occurrence of an event in the given examples.
• Apply the necessary formula to calculate the probabilities of the sum of given independent and dependent events.
• Selects the necessary formulas for calculating the probability of given disjoint and overlapping events.
• Finds the type of relationship and closeness between two features.
• Selects the necessary statistical methods to solve the problem.
Competences
• Evaluates the adequacy of theoretical knowledge and skills acquired in the course in solving tasks.
• Performs tasks according to the topic using IT tools, e.g., MS EXCEL.
• Evaluates the results of the solved task.
Submit solutions for all independent work tasks It is necessary to get a positive evaluation of the solution of each task
Tests and the exam should be passed
View courses by:
Faculty Subject Area Cycle (Bachelor / Master) Semester (Autumn/Spring)
| Field | Work language | Acad. cycle | ECTS credits | Semester | Course code |
|---|---|---|---|---|---|
| Economic | LV ENG | Bachelor | 3 | Spring | EkonP173 |
To provide knowledge about the issues of probability theory and about the role of statistics, the application of its methods in data processing.
To acquire elements of probability theory and calculation of probabilities of events. To acquire concepts of random variables and their distribution laws. To acquire skills in collecting, processing and analyzing measurement and statistical data, sampling and evaluate the parameters of the population with the characteristics of the sample. To find out the basic issues of correlations.
Knowledge
• Explains the concept “event” and event probability definitions.
• Explains event probability calculation formulas.
• Explains the concept of discrete and continuous, random variables.
• Explains the concept of discrete and continuous random variable distribution and the function of integral and differential distribution of random variables.
• Explains the characteristics of random variable - mathematical expectation (mean), variance, standard deviation, mode and median.
• Explains the distributions of continuous case sizes (uniform, normal, Poisson, etc.)
• Understands the basic tasks of mathematical statistics and explains the concepts of general and sample sets.
• Explains empirical distribution functions, series of variations, polygon, histogram construction.
• Understands the concept of confidence interval and defines its calculation formula.
• Explains the essence of linear and nonlinear regression - to find the relationship between factorial and resultant feature.
• Explains the significance of the correlation coefficient to characterize the closeness of the relationship between the factorial and outcome feature in the case of linear regression and the significance of the coefficient of determination () in the case of nonlinear regression.
• Understands the concept of statistical hypothesis. Outlines the main tasks of hypothesis testing; the null hypothesis and the alternative hypothesis in relation to the areas of acceptance (acceptance) and rejection of the named hypotheses, define the level of significance in the acceptance of hypotheses.
Skills
• Calculates the probabilities of occurrence of an event in the given examples.
• Apply the necessary formula to calculate the probabilities of the sum of given independent and dependent events.
• Selects the necessary formulas for calculating the probability of given disjoint and overlapping events.
• Finds the type of relationship and closeness between two features.
• Selects the necessary statistical methods to solve the problem.
Competences
• Evaluates the adequacy of theoretical knowledge and skills acquired in the course in solving tasks.
• Performs tasks according to the topic using IT tools, e.g., MS EXCEL.
• Evaluates the results of the solved task.
Submit solutions for all independent work tasks It is necessary to get a positive evaluation of the solution of each task
Tests and the exam should be passed
View courses by:
Faculty Subject Area Cycle (Bachelor / Master) Semester (Autumn/Spring)
| Field | Work language | Acad. cycle | ECTS credits | Semester | Course code |
|---|---|---|---|---|---|
| Economic | LV ENG | Bachelor | 3 | Spring | EkonP173 |
To provide knowledge about the issues of probability theory and about the role of statistics, the application of its methods in data processing.
To acquire elements of probability theory and calculation of probabilities of events. To acquire concepts of random variables and their distribution laws. To acquire skills in collecting, processing and analyzing measurement and statistical data, sampling and evaluate the parameters of the population with the characteristics of the sample. To find out the basic issues of correlations.
Knowledge
• Explains the concept “event” and event probability definitions.
• Explains event probability calculation formulas.
• Explains the concept of discrete and continuous, random variables.
• Explains the concept of discrete and continuous random variable distribution and the function of integral and differential distribution of random variables.
• Explains the characteristics of random variable - mathematical expectation (mean), variance, standard deviation, mode and median.
• Explains the distributions of continuous case sizes (uniform, normal, Poisson, etc.)
• Understands the basic tasks of mathematical statistics and explains the concepts of general and sample sets.
• Explains empirical distribution functions, series of variations, polygon, histogram construction.
• Understands the concept of confidence interval and defines its calculation formula.
• Explains the essence of linear and nonlinear regression - to find the relationship between factorial and resultant feature.
• Explains the significance of the correlation coefficient to characterize the closeness of the relationship between the factorial and outcome feature in the case of linear regression and the significance of the coefficient of determination () in the case of nonlinear regression.
• Understands the concept of statistical hypothesis. Outlines the main tasks of hypothesis testing; the null hypothesis and the alternative hypothesis in relation to the areas of acceptance (acceptance) and rejection of the named hypotheses, define the level of significance in the acceptance of hypotheses.
Skills
• Calculates the probabilities of occurrence of an event in the given examples.
• Apply the necessary formula to calculate the probabilities of the sum of given independent and dependent events.
• Selects the necessary formulas for calculating the probability of given disjoint and overlapping events.
• Finds the type of relationship and closeness between two features.
• Selects the necessary statistical methods to solve the problem.
Competences
• Evaluates the adequacy of theoretical knowledge and skills acquired in the course in solving tasks.
• Performs tasks according to the topic using IT tools, e.g., MS EXCEL.
• Evaluates the results of the solved task.
Submit solutions for all independent work tasks It is necessary to get a positive evaluation of the solution of each task
Tests and the exam should be passed