Microsoft Excel – Data Analysis and Statistic Calculations

Kód kurzu: MSEXDS

Tato část není lokalizována

At the course participants meet advanced data analysis methods. All standard statistical – analytic functions are discussed especially the Analysis ToolPack Add-Inn which is used for demanding statistical analyses. Listeners learn how to work with tools such as a descriptive statistics, a properties correlation, a values prediction and a work with time series. The course also focuses on clear interpretation of found results.

Odborní
certifikovaní lektoři

Mezinárodně
uznávané certifikace

Široká nabídka technických
a soft skills kurzů

Skvělý zákaznický
servis

Přizpůsobení kurzů
přesně na míru

Termíny kurzu

Počáteční datum: Individuální

Forma: Individuální

Délka kurzu: 2 dny

Jazyk: cz

Cena bez DPH: 8 000 Kč

Registrovat

Počáteční
datum
Místo
konání
Forma Délka
kurzu
Jazyk Cena bez DPH
Individuální Individuální 2 dny cz 8 000 Kč Registrovat
G Garantovaný kurz

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Kontakt

Popis kurzu

Tato část není lokalizována

At the course participants meet advanced data analysis methods. All standard statistical – analytic functions are discussed especially the Analysis ToolPack Add-Inn which is used for demanding statistical analyses. Listeners learn how to work with tools such as a descriptive statistics, a properties correlation, a values prediction and a work with time series. The course also focuses on clear interpretation of found results.

Struktura kurzu

Tato část není lokalizována

Analysis of extensive data volumes by helping PivotTable (PT) and PivotTable Chart Report.

  • PT creation principles
  • Total functions in PT
  • Build-in functions for different data views in PT
  • Calculated fields and items
  • Data analysis and data understanding in PT

Basic data analysis

  • Frequency analysis
  • Histogram – frequency chart
  • Level characteristics (Mean, Median, Mode, Quantity)
  • Variable characteristics (Variance, Deviation)
  • Shape allocation characteristics (Kurtosis, Skewness)

Dependence analysis

  • Correlation
  • Regression analysis (appropriate regression model, comparison of two different alternatives, judgment of regression model quality, estimates based on chosen regression model
  • Graphic dependence analysis
  • Multi regression (more independent variables)

Time series analysis

  • Time series characteristics
  • Basic time series description (differences, growth speed – chain, indexes)
  • Time series modeling
  • Time series decomposition (trend, seasonal, cyclic, random item of time series)
  • Time series purge of seasonal component (moving average)
  • Estimates based on time series model
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