Business Statistics
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Course informations
| Study program level |
Undergraduate |
| Study program |
Entrepreneurship |
| Study program direction |
Entrepreneurship |
| Course year |
1. |
| Course semester |
II |
| 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, and will interpret calculated parameters and make statistical decisions based on statistical analysis.
Course outcomes
The name of the learning outcomes set: Descriptive statistics
Level: 6
- 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.
The name of the learning outcomes set: Probability distributions
Level: 6
- 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.
The name of the learning outcomes set: Bivariate statistical analysis
Level: 6
- 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.
The name of the learning outcomes set: The analysis of time sequences
Level: 6
- 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.
The name of the learning outcomes set: Inferring the characteristics of the base set from a sample
Level: 6
- 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.
