Executive
Education
Courses
Take Executive Education courses at Riga Business School to keep up with the latest developments in business education. Whether you’re a recent graduate or it’s been years since you called yourself a student, we welcome you to continue growing. This is an opportunity for you to develop and update your talents.
Wednesday, Jan 10 – Apr 17
6:00 pm – 9:00 pm
In-Person
EUR 750 + VAT
Andrejs Koliškins
Managerial Statistics
Statistical methods are widely used in accounting, finance, management, and marketing. A manager needs to know how to use the available information to make better decisions.
The course objectives are to learn how to properly present and describe information, to understand how to draw conclusions about large populations based only on information available from samples, to learn how to improve processes, and to understand how to obtain reliable forecasts.
| Class | Topic |
|---|---|
| Class 1 | Introduction to business statistics by examples. The frequency distribution. The relative frequency distribution. The histogram and polygon. Cumulative distributions and cumulative polygons. Measures of central tendency. Measures of dispersion. Other descriptive measures. Shapes of distributions. Five-number summary and box-and-whisker plot. Approximating measures of central tendency and variation |
| Class 2 | Basic probability concepts. Simple and joint probability. Addition rule. Conditional probability. Multiplication rule. Bayes’ theorem. Discrete probability distributions. Mathematical expectation and the expected monetary value. Applications in finance. |
| Class 3 | Binomial and Poisson probability distributions. Continuous random variables. The normal distribution. Characteristics of the normal distribution. Normal approximation to the binomial distribution. |
| Class 4 | Sampling designs and sampling errors. Sample statistics. Sampling distribution of the mean. Sampling distribution of the proportion |
| Class 5 | Point and confidence interval estimates. Confidence interval estimation for the mean. Confidence interval estimation for the proportion. Determining the size of a sample. Sample midterm exam problems. |
| Class 6 | The hypothesis-testing procedure. Type I and type II errors. Test of hypothesis for the mean when the population standard deviation is known. One-tailed and two-tailed tests. Power of a test. The p–value approach to hypothesis testing. Sample midterm exam problems. |
| Class 7 | Midterm exam |
| Class 8 | Test of hypothesis for the mean when the population standard deviation is unknown. Test of hypothesis for a proportion. F test for differences in two variances. |
| Class 9 | Test for the difference between two means. Test for the difference between two population proportions. Chi-square tests. Types of regression models, the simple linear regression equation. Standard error of the estimate. Measures of variation in regression and correlation. |
| Class 10 | Regression diagnostics. Nonlinear relations. Confidence interval estimates. Applications. |
| Class 11 | Multiple regression models. Applications of multiple regression. Analysis of variance. |
| Class 12 | Decision making. Quality control. Review. Sample final exam problems. |
| Class 13 | Case presentations. Introduction to multivariate statistics. |
| Class 14 | Final exam. |
Course is priced at 750 Eur + VAT
Requirements to receive the certificate:
- 80% attendance
- active participation in classes that includes discussions, group and individual work.
Managerial Statistics
EUR 750 + VAT
Andrejs Koliškins
Wednesday, Jan 10 – Apr 17
6:00 pm – 9:00 pm
In-Person
Statistical methods are widely used in accounting, finance, management, and marketing. A manager needs to know how to use the available information to make better decisions.
The course objectives are to learn how to properly present and describe information, to understand how to draw conclusions about large populations based only on information available from samples, to learn how to improve processes, and to understand how to obtain reliable forecasts.
| Class | Topic |
|---|---|
| Class 1 | Introduction to business statistics by examples. The frequency distribution. The relative frequency distribution. The histogram and polygon. Cumulative distributions and cumulative polygons. Measures of central tendency. Measures of dispersion. Other descriptive measures. Shapes of distributions. Five-number summary and box-and-whisker plot. Approximating measures of central tendency and variation |
| Class 2 | Basic probability concepts. Simple and joint probability. Addition rule. Conditional probability. Multiplication rule. Bayes’ theorem. Discrete probability distributions. Mathematical expectation and the expected monetary value. Applications in finance. |
| Class 3 | Binomial and Poisson probability distributions. Continuous random variables. The normal distribution. Characteristics of the normal distribution. Normal approximation to the binomial distribution. |
| Class 4 | Sampling designs and sampling errors. Sample statistics. Sampling distribution of the mean. Sampling distribution of the proportion |
| Class 5 | Point and confidence interval estimates. Confidence interval estimation for the mean. Confidence interval estimation for the proportion. Determining the size of a sample. Sample midterm exam problems. |
| Class 6 | The hypothesis-testing procedure. Type I and type II errors. Test of hypothesis for the mean when the population standard deviation is known. One-tailed and two-tailed tests. Power of a test. The p–value approach to hypothesis testing. Sample midterm exam problems. |
| Class 7 | Midterm exam |
| Class 8 | Test of hypothesis for the mean when the population standard deviation is unknown. Test of hypothesis for a proportion. F test for differences in two variances. |
| Class 9 | Test for the difference between two means. Test for the difference between two population proportions. Chi-square tests. Types of regression models, the simple linear regression equation. Standard error of the estimate. Measures of variation in regression and correlation. |
| Class 10 | Regression diagnostics. Nonlinear relations. Confidence interval estimates. Applications. |
| Class 11 | Multiple regression models. Applications of multiple regression. Analysis of variance. |
| Class 12 | Decision making. Quality control. Review. Sample final exam problems. |
| Class 13 | Case presentations. Introduction to multivariate statistics. |
| Class 14 | Final exam. |
Course is priced at 750 Eur + VAT
Requirements to receive the certificate:
- 80% attendance
- active participation in classes that includes discussions, group and individual work.