Data Visualization in AM Statistical Software Assignment Help

Introduction to Data Visualization in AM Statistical Software

AM is a statistical software tool for evaluating data from large-scale surveys and complex samples.

Another feature of large-scale assessments has widened the scope of AM's application: they virtually always take a sample from a complicated design. Using a Taylor-series approximation, AM automatically generates acceptable standard errors for complicated data. Even when new procedures are added to the software, this happens automatically. The software has evolved to include several non-MML statistics, such as regression, probit, logit, cross-tabs, and other statistics that are helpful for survey data in general.

The American Institutes for Research is committed to maintaining AM available to the research community as a free and developing tool. For more information, updates, and technical help, go to this website.

AM provides advanced statistics with a simple drag-and-drop interface and an integrated help system that explains both the data and how to utilize the system.
AM contains statistical approaches for assessing assessment and survey data, such as marginal maximum likelihood models (MML). Tests can't pinpoint proficiency, thus MML techniques define a probability distribution over the proficiency scale instead. AM will also look into the "plausible values" that are utilized in tests like the NAEP.
Procedures for assessing non-assessment survey data are also included in AM.
For complicated samples, all of AM's processes automatically provide acceptable standard errors. For the standard errors, all processes have a Taylor-series approximation, and a few provide the option of using a jackknife or other replication approach.
AM is a free program that can be shared and copied. It was made possible, in part, by the National Center for Education Statistics.

The Program Begins

Simply double-click the AM software icon to start the program. The AM program contains three windows and a primary menu bar:

You may examine and control the variables in your data file using the Variable List, which shows on the left and side of the screen.

In the bottom right quadrant, there is a Run Queue. Statistical models that you're working on will appear here until they're ready to run.

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The Completed Run Queue is used to store statistical runs that have been completed. By right-clicking icons in the completed run queue, you can do post-doc analysis in most statistical models.

Getting data into the application is the first step in using it. There are six ways to get data into the system right now:

Import a data set in ASCII format.
Open a previously saved data set.
Data can be extracted from an existing AM data file.
Import data from more than 100 different file formats, including SAS and SPSS.
SPSS is used to import data.
Importing data from a SAS Transport file is inefficient at the moment, and it's recommended to use the normal import/export function instead.

You can recode your variables using the capabilities indicated under "Manipulating Data," many of which are available on the Variable Menu, once the dataset has been accessed.

When you're ready, go to the "Statistics" option on the main menu bar and choose the statistical models you want to run. To get statistics help, select the statistical procedure you're interested in and press F1.

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