Forecasting in the Presence of Special Events

Hi,

In this lesson I learnt how can I determine whether specific factors influence the amount of a dependent variable, for example customers traffic in a airport or in a fun fair; how can I evaluate forecast accuracy, by determining the point of outliers, and finally how can Icheck whether my forecast errors are randon.





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BCE report

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Ratio-to-Moving-Average Forecast Method

Hello,

In this lesson I've learnt how we can reckon a forecast by coming up with good forecast of quarterly seasonal index. A lot of companies can have seasonal patterns which explains the behavior of the variable we are analyzing, for instance revenues, cost of supplies...; consequently, if we have a method that breaks down in different index which it allows us to understand this pattern; our forecast will be accurate, and we could make our forecast with more precision.


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Winters's Method: Smoothing allows forecasting easy

Hi,

In this leason I've learnt how to manage in other to predict future values of a time series, such as monthly cost or monthly product revenues. This is usually difficult because the characteristics of any time series are constantly changing. Smoothing or adaptive mothods are usually best suited for forecasting furere values of a times series.

The file that you can look at below, you'll find one description the most powerful smoothing method: Winters's method.

To help you understand how Winters's method works, we use several examples where you could see all details of the reckonings needed to get truethly forecast.


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Randomized Block and Two-Way ANOVA

Hi,

In this chapter I learnt to use the Excel tool Two-Way ANOVA in order to analize when two factors might influence a dependent variable, if any of the two factors have a significant influence on the dependent variable. With two-way ANOVA, you can also determine whether two factors exhibit a significance interaction.


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Analysis of Variace: One-Way ANOVA

Hello,

Data analysis often have data about several different groups of people or items and want to determine whether the data about the groups differs significantly.

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Modeling Nonlinearities and Interactions

Hi,

When we analize data with representents groups of data or variables, we find that changes in the INDEPENDANT VARIABLE often influences a DEPENDANT VARIABLE throu a nonliniear relationship. That means when we yields a shift in the dependant variable caused by a unit of change in the independant variable, the ratio of this change in not constant.


You could see more details of this calculation by clicking here.
 

Incorporating Qualitative Factors into Multiple Regression

Hi,

In this lesson I learnt: how can I predict quarterly U.S. auto sales?

Suppose we want to predict quarterly U.S. auto sales to determine whether the quarter of the year impacts auto sales. We'll use the data in the file you could click below, where sales are listed in thousands of cars, and GNP is in billions of dollars.

Click here to see how I made the analysis.

Introducing to Multiple Regression

Hi,

In this lesson I learnt the meaning of the parameters (Coeficients, p-vauleu, R2, Standard error...) that could influence in a multiple regression, how I can trust in the forecast made from the equation build with the coeficients, how much accurate we'll be our predictions...


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Using Correlations to Summarize Relationships

Hello,


In this chapter I learnt to read this statistic tool: correlation, to know the degree of relation between two variables, that means by using this took we are able to know how much is the shift behavior of each other.


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The Power Curve: a curve where takes place production and learning by doing

Hi everybody,

The Power Curve (y = Ax^b) is a shape where it fits the dates from production cost as a function of units produced (frequently b>1), or dates from sales as a function of advertising expenditures (usually -1
You could see some examples by clicking here 

Forecasting by using Straight Line Relationships

Hi again,

Every business analyst should have the ability to estimate the relationship between important business variables. The trend curve, which I discuss in this Excel fileif often helpful in determining the relationship between two variables. The variable that analyst try to predict is called the dependent variable. The variable we use for prediction is called the independant variable.

It is nice to see as we could forecast the behavior of the independant variable throughtout our decisions in the dependant variable. We could see how it's apply in the Excell file presented below.



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Summarizing Data with Database Statistical Functions

Dear alls,

Dear friends

This chapter I learnt to get specific data from a database summarizing and sorted by using some EXCEL BDFUNCTIONS. As we know a database is made up off fields where it contains data, we could get these data classified and sorted by summarizing, counting, averaging... following the approaches we defined.


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Using Pivot Tables and Slicers to Describe Data

Pivot tables are useful to describe data, it is a Excel tool which allows to grup data, classifying, filtering and arranging data acording with different approaches.


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