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Video Academy | Environmental area

The statistical analysis techniques presented in these videos are applicable to all subject areas, specifically focusing onexamplesof typeenvironmental.

Custom tables and graphs

You have toto analyzealarge amount of data and variables, but did you realize that spreadsheets have limitations because they require a long and laborious process?

In this video we see the main features of custom tables and graphs to move from data to information quickly and easily with the solutionStatistics for Data Analysispowered bySPSS


We show apractical example, thanks to which we will see at workthe previewfrom thetables, Thatwe will customizein real time,switching from a selection of data to the graph.

We will drawthen some godsmain graphs, including histogram and pie, which we will be able toexportin PowerPoint, Word, Excel and more.

see Tables module

How to choose a statistical Test (webinar in English)

When statistical analysis havesample dataas a starting point,statistical testsare of fundamental importance in order toextendthe results to a largerpopulation.


How to navigate the choice of the most appropriate statistical test to maximize the probability ofhighlightingin particulareffectand understanding whether it is actually present in the population?


thegoalof the presentation will be to show, throughpractical examples with Statistics for Data Analysis power by SPSS, techniques for choosing the most appropriate statistical test, based on the data at hand.


 These are thetopicswe will cover during the presentation:

  • Parametric tests

  • Non-parametric tests

  • Comparison between parametric and non-parametric tests

Discover Statistics Base module

The t-test

During this video, after an overview on the topic ofstatistical inference, let's take a closer look at one of the most popular tests:the t-test (or Student's test).

The T-test is one of the best known because it serves for compare equality statisticsmiddle school of two populations or of the same population with respect to a certain reference value.


Target of this presentation is to understand when, in which cases and what are the restrictions to be able tousethis kind ofparametric test. 



  • Summary of the rules for theverification of statistical inference

  • Notes on differences between parametric and non-parametric tests

  • Hiring of the t-test

  • Criteria to decide when to use the parametric test versus a non-parametric procedure

  • Practical exampleon a monitoring of the radioactivity present on mosses after the Chernobiyl disaster

The t-test is found inBasic module

Statistics for Data Analysis vs. Spreadsheets


During this presentation we show the main onesdifferencesAndpotentialin useof Statistics for Data Analysis powered by SPSSto analyze data against a spreadsheet.

Through practical examples we show that Statistics for Data Analysis isusefulboth to those who dostatistical analysisboth to those who carry out activities ofreporting, automating the creation oftablesand decreasing the possible calculation errors compared to Excel.


  • Introductionto the tools included in the solution (App Statistics for Data Analysis, LaunchBox, dedicated support, etc.)

  • Comparisonin organizing data in SPSS Statistics and in Excel

  • Preparationsome data

  • Overview ofAnalyze menuby SPSS Statistics

  • Practical exampleon a data set of contaminated sites
    in the United States

Look at the features of the moduleStatistics Base

The Analysis of Variance for Environmental Data

In the world we live in, the link between statistical analysis and environmental and health protection is increasingly evident.

Indeed, it is the result of statistical research, which has provided incontrovertible proof of the damage that climate change, atmospheric and noise pollution cause not only to man, but also to the entire environment.


By virtue of the increasing importance that statistics is assuming in this area, during this presentation we are showing a general overview of some statistical synthesis and survey techniques that can be used in the analysis of environmental data, such as for example the Analysis of Variance (ANOVA) .


  • Individualizationof outliers

  • Checkof the data

  • Explorationof the dataset

  • Introductionto the analysis of variance

  • Practical exampleon an air monitoring dataset

Look at the features of the moduleStatistics Base

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