Belépés címtáras azonosítással
magyar nyelvű adatlap
angol nyelvű adatlap
Trend Analysis and Visualization
A tantárgy neve magyarul / Name of the subject in Hungarian: Trendelemzés és vizualizáció
Last updated: 2017. június 23.
Business Information Systems MSc.
Specialization Analytical Business
Knowledge of statistics, finances, and business administration
Objectives, learning outcomes and obtained knowledge:
Predictive Ananlysis of time series. Mapping problems in predictive analytics, solutions in practice. Support by standardized tools. Show and understand the surplus of visualization, and turn it back to the data preparation and modeling phases
Modul_1.: Visual analytics
Introduction to Predictive Analytics and Visualization, visual analytics
Analytical reasoning techniques,
Data representations and transformations
Visual representations and interaction techniques.
Generalized multidimensional scaling
Business Decision Mapping (BDM)
Practice in Laboratory 1: Visualization
Approaching a forecasting problem
Components of a time series; Judging the quality of data; Understanding data;
Looking at residuals; How to start making a forecast; Forecasting models.
Defining parameters, Analysis of data sources; Choosing alternative
projection techniques Preliminary
Forecasting with exponential smoothing models
moving averages; Single exponential smoothing; Compare exponential smoothing
with moving averages; Exponential smoothing for trending data
laboratory 2. Exponential smoothing;
Software programs and visualization.
Trend and seasonality modeling and analysis;
Contribution of trend/seasonal effects;
Analysis of residuals.
laboratory 3: Trend and seasonality; Software programs and visualization
Preparing the data for modeling;
linearity; Achieving normality; Dealing with outliers
Practice in laboratory 4: Outliers; Software
programs and visualization.
Regression modeling and analysis
regression models: The regression curve; A simple linear model; The method of least-squares; Normal
regression assumptions; Comparing estimation techniques; Interpreting regression output: The R-squared
statistic; The t-statistic; The F-Statistic; The D-W Statistic; Assessing
forecast precision, Looking at regression residuals.
laboratory 5: Regression example; Software programs and visualization.
Insuring against unusual values
The need for
robustness in correlation and regression analysis Seasonal adjustment;
Ratio-to-moving-average-method. Seasonal adjustment with resistant smoothers
laboratory 6: with seasonality analysis;
Software programs and visualization
Differences of foresight and forecasting
Non measurable trend analysis: qualitative description, success factors
Topic definition, starting position Ongoing projects, expected development
Visualization of trends through drawing, pictures (like cicles, hype)
Visioning a usage area
definition, summary of the situation Driver analysis estimation of effects,
uncertainty Scenario making, alternative scenarios, illustrations Visualization
and illustration of the visions
Technology radar for foresight Flow of news, scanning news, practice for
selections Professional blogging, technology radar Virtual community to build up Games for
Strategy making based on backward scenarios
Choosing objectives, freedom of choices, views Influencing drivers, costs
and risks Strategy forming through
backward scenario analysis
laboratory 7: Foresight presentations in of the students on a preliminary given
Usability of predictive analysis, foresight and
Method of instruction :
Lectures and 6 practices in laboratory
a. In the class period there is 1
in-class test (ZH) from the topics of modul1 and modul2
and presented homework from the topic
b. In the examination period: written
examination and it could be extended orally,
c. Preliminary examination opportunity exists
d. Condition for the signature is the pass mark of ZH test minimum 4
points from the maximum 10 points. Another condition for the signature is at
least successfull attendances the laboratory exercises. One practice in
laboratory can be missing.
There is one possibility to repeat the test in the teaching period. In the
rectification period(repeat period) there is another (final) possibility to
rewrite the in-class test (ZH).
Only two of practices in laboratory can be repeated in an appointed time
with the instructor.
The homework presentation can be repeated int he recap period in a given data,
with paying the recap fee.
Preliminary appointing with instructors or after the lectures
References, textbooks and resources:
Syllabus prepared by: