Business Statistics
Back
Course informations
| Study program level |
Undergraduate |
| Study program |
Management |
| Study program direction |
Informatics management |
| Course year |
2. |
| Course semester |
IV |
| Course status |
Core |
| ECTS |
6 |
| Lectures (h) |
30 |
| Excercises (h) |
45 |
| Seminars (h) |
- |
Course objectives
Students will apply the basic methods and procedures of statistical analysis required for independent operational statistical analysis of real business cases.
Course outcomes
- Determine the characteristics of statistics as a scientific discipline.
- Apply data editing methods.
- Apply methods of graphical display of data.
- Interpret the characteristics of observed phenomena based on their graphical analysis.
- Compute and interpret numeric indicators of descriptive statistics
- Calculate, analyze and interpret using MS Excel functions numeric indicators of descriptive statistics.
- Apply the definition of probability a priori and a posteriori when solving tasks
- distinguishes discrete and continual random variables
- solves tasks by applying formula for expected value, variation, standard deviation, coefficient of variation
- Distinguishes probability distributions (Binomial, Poisson, Normal)
- Solves tasks by applying probability distribution formulas (Binomial, Poisson, Normal) calculate, analyze and interpret by using MS Excel functions numeric indicators of descriptive statistics.
- Justify the selection of regression and correlation analysis in real-time analysis.
- Justifying the selection and using a regression model for predicting the value of a variable based on the value of another variable (to determine the causal link between the observed phenomena).
- Determine the degree of correlation between the observed phenomena.
- Interpret the obtained numerical indicators in terms of the nature of the correlation between observed variables
- Calculate, analyze and interpret using MS Excel functions for numeric indicators of descriptive statistics.
- Apply dynamic indicators in time series analysis.
- Apply a graphical method of analyzing the dynamics of a occurrence in a time period.
- Use a trend model to evaluate the movement of the observed phenomenon over the past period and assess the representativeness of the model
- Predict the value of the observed variable for the future period based on the trend model
- Interpret the calculated time scale analysis indicators
- Calculate, analyze and interpret using MS Excel functions numeric indicators of descriptive statistics.
- Determine the features of inferential statistics.
- Justify the choice of method for estimating the arithmetic mean, total and proportions of the basic set.
- Assess the parameters of the base set based on the sample.
- Interpret the calculated parameters of the base set.
Course content
Concept and goal of statistics. Statistical features: concept, types and characteristics. Observation and data collection. Defining data. Graphical and table representation of data. Mean values: arithmetic mean, geometric mean, harmonic medium, mod, median, and quartile. Dispersion: Variation range, variance, standard deviation. Measures of asymmetry and roundness. Probability, theoretical distribution. Sample method. Correlation: linear correlation, rank correlation. Regression: Single linear regression, coefficient rating, deviation. Analysis of time series. Graphic representation. Individual and aggregate indices. Average values. Linear trend.
