Applied Statistics in Tourism
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Course informations
| Study program level |
Undergraduate |
| Study program |
Management |
| Study program direction |
Management of rural tourism |
| Course year |
1. |
| Course semester |
II |
| Course status |
Core |
| ECTS |
5 |
| Lectures (h) |
30 |
| Excercises (h) |
30 |
| Seminars (h) |
- |
Course objectives
- Students will apply the fundamental methods and procedures of statistical analysis necessary for an independent analysis of cases from actual business practice. They will also interpret the calculated parameters and make decisions based on the statistical analysis.
Course outcomes
Name of the set of learning outcomes: Grouping, charting, and graphing of statistical data
Level: 6
- Adopt the concept and task of statistics
- Identify and distinguish statistical features
- Make preparation for independent research
- Evaluate in which situation data grouping (table and graphic) is necessary.
- Determine the difference between absolute and relative frequencies.
- Tabulate the default data and evaluate the values obtained.
- Display the data and interpret them by the appropriate graph.
Name of the set of learning outcomes: Basic indicators of descriptive statistics.
Level: 6
- Determine the meanings of mean values, dispersion measures, asymmetry and roundness.
- Calculate and explain quantizes (quartiles, deciles, centiles).
- Assess which measures are most appropriate for a given data set.
Name of the set of learning outcomes: Correlation and regression analysis.
Level: 6
- Determine the coefficient of correlation (Pearson's linear correlation coefficient and Spearman’s rank correlation coefficient).
- Determine the equation of the regression model (linear, exponential, double logarithmic), interpret parameters and evaluate the representativeness of the model obtained.
- Based on the most representative model, evaluate the value of the dependent variables for the given value of an independent variable.
Name of the set of learning outcomes: Analysis of time series in statistics
Level: 6
- Determine and graphically display chain and base indices.
- Determine the equation of the predictive trend model (linear and exponential), interpret the parameters and evaluate the representativeness of the model.
- Predict the value of observed variables for one or more upcoming time periods based on the predictive trend model.
Course content
Concept and task 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, quartile, decile, and percentile. Dispersions: variation range, variance, standard deviation, interquartile, coefficient of variation, quartile deviation coefficients. Standardized character, Chebyshev Rule. Measures of asymmetry and roundness. The basics of combinatorial. 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.
