About Course
This course focuses on analyzing data in Excel rather than just learning buttons and menus. Accordingly, this is a way to learn how to use ready-made Excel functionality and add-ins for modeling, forecasting over time, and finding optimal solutions for business problems.
An opportunity even for humanists to master this advanced functionality of Excel: the course does NOT contain a clutter of complex formulas and functions, macros, languages (DAX, M) – You will work mainly with the user interface and program windows.
Everything is explained in simple and understandable language “at your fingertips”:
The course teaches how to work with a set of functionality and Excel add-ins to fully solve application cases and problems.
The course is focused not just on demonstrating the screen and buttons during lectures, but on the practical development of functionality and add-ons. Therefore, the course is full of practical tasks (more than 35 TASKS!), which perfectly work out the lecture material, while being simple and easy to understand
In addition to working with Excel functionality, the course includes conceptual and subject-specific lectures that explain the basic concepts and categories from subject areas (management, statistics and probability theory, time series), knowledge of which is necessary for the effective and correct use of the Excel add-ins discussed in the course
What Will You Learn?
- What-If modeling to solve business problems (and more)
- Selection of parameters for formulas (formulas work “from the opposite”: selection of values based on the result you need)
- Simulation of multiple scenarios (for example, realistic, pessimistic and optimistic scenarios for the project, budget, balance sheet, etc.)
- Using substitution tables: modeling calculation results for different values of 1 or 2 variables (for example, what will be the income for different % discount options and different volumes of purchased goods)
- Automatic search for the most optimal solution for business problems among hundreds and thousands of possible alternatives
- Optimization tasks by selecting the most optimal option from a variety (for example, delivery of materials from different warehouses/suppliers based on the distance from them to the production site)
- Drawing up forecast sheets with possible “corridors” of deviations; working with time series (days, months, quarters, years...)
- Data analysis for making management decisions using statistical methods (data-driven decisions) - can discovered patterns or differences in a group/sample of data be extended to the general population (all clients, employees, representatives of the profession, and other groups)
- Descriptive statistics (frequencies, means, medians, modes, percentiles, quartiles, measures of variability, etc.) etc.) and their visualization in the form of a histogram and a "box with a mustache"
- Finding hidden relationships between variables (correlations and covariances) - for example, is satisfaction with the range of products, price, service, etc. related? with a generalized assessment of customer satisfaction with a point of sale
- Regression analysis to predict the values of a specific variable based on the values of other variables (for example, how much customer loyalty will drop if the quality of service decreases by 5 points)
- Search for differences between groups/samples (group comparison) - for example, are there differences in the choice of goods of different colors between men and women, pensioners and youth, housewives and private entrepreneurs, etc.
Course Content
Introduction
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From the author
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How will we learn
Modeling conditions: what-if analysis”
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What is it used for
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Parameter selection
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Finance
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Formula on formula…
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Data table for 1st variable
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% in the bank
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Discounts, volumes
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Data table for 2 variables
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Again loans
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Discount with sales volume at the same time
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Script Manager
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Different scenarios
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A guide to practice with the Script Manager
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Director and screenwriter
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Section results
Optimization problems: search for solutions
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What kind of search for solutions?
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How to connect add-ons
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Check add-ons – and connect if necessary
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Importance of model (domain) before using solution search
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Comprehensive overview of the add-in, search for solutions using an example
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Finding solutions in production
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Search for solutions in logistics
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Finding solutions in advertising purchasing
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Finding solutions for the transfer of drilling crews
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Finding solutions in a reorganization project
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Section results
Finding Hidden Patterns: Data Analysis
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Purpose of the add-on
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Data array
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Sample and population
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Retrieve selections from an array
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The main thing from the stat. Theories: hypotheses, probability of error, level of significance
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Let’s consolidate knowledge of conceptual material
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Descriptive Statistics
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Sample output of descriptive statistics
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Percentiles (percentiles)
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Let’s calculate the percentile
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Case with percentiles
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Visualization of quantity and %: histogram
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A histogram is also just a diagram
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Visualization of mean, quartiles, min and max: box with whiskers
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Mustachioed Box
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3 main tasks of analytics
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Key limitation of the Data Analysis add-on”
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Comparison of groups (samples): basic concepts
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Comparison of paired (related) groups/samples: t-test
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Before after
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Comparison of independent groups (samples): t-test
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Horse hunters
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Another option for comparing independent samples/groups: z-test.
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Comparison of several groups (samples): one-way analysis of variance
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One-factor
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Comparison of multiple groups/samples: two-way analysis of variance
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Two-factor
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Relationships between variables
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Correlation and covariance
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Svyaznoy
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Regression analysis
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Regression forecast
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Section results
Basics of forecasting over time/periods, time series
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15 minutes: introduction, purpose and subject area disclaimers
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The main pitfall of forecasting over time
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Main tasks of time series analysis
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Time series components: trend, seasonality, cycle, burst
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Concept Mastery
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Trend line
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Trendovik
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Ready-made functions for forecasting
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Functionary
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Manual search and consideration of seasonality in the forecast
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Seasonal
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The most popular calculation method for seasonality
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Testing the seasonality method
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Forecast calibration using index factors
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Factorization
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Upper and lower ceilings (forecast corridor)
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Resting on the ceiling….
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Forecast sheet (excel 2016 and higher only!)
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Forecast sheet
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What if there is no visible trend line?
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Moving average
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Slip
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Exponential smoothing
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Smoothness of the exponential…
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Relationship between time series
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Importance of the model for time series analysis
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Not everything is so simple… Or “understanding is in the model!”!”
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Section results
Afterword
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About the course learned in 2 minutes
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A story about 3 mega-add-ons of the power family
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Bonus lecture