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Vorteile:

kostenfrei,

übersichtlich / intuitiv nutzbar

Nachteile: I

Installation
(problemlos, schnell)

Datenimport über csv-Dateien

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deutsch, 6 min

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JASP 0.1.0 First View - Erster Blick. Der SPSS-Killer?

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Vorteile:

keine Installation;

schlägt situativ Test vor

enthält Umfragefrageplattform

viele YouTube-Anleitungen

Nachteil: kostet 19,- Euro für 1 Monat (Preisstufen bis 49,- für ganzes Jahr)

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Vorteile

oft in Wissenschaft und Wirtschaft genutzt
gut zur Vorbereitung auf Beruf

Datenimport aus Excel

viele YouTube-Tutorials

umfangreiche Literatur

Nachteile

kostenpflichtig

umfangreiche Installation

Arbeit in mehreren parallelen Dateien nötig

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englisch, 5 min

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Datenanalyse mit DATAtab - Online Statistik Rechner

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IBM restricts Grad Pack licenses to 2 activations to be used on 2 separate machines (1 activation per machine) provided you are the only user of the license on both machines. Once activated your license cannot be deactivated, suspended, paused or transferred to another machine. De-activations and transferability are features limited to more expensive Commercial licenses which are $1000's per annum.

Upon installation, SPSS extracts your machine's "lock-code" (a unique identifier for your machine) which it uses to activate your license. In the event of computer hardware changes (e.g. reformatting or replacing your hard drive) or updates to your operating system (i.e. updating Mac OSX), a new lock-code may be created by your machine. For your SPSS license to work with your new lock-code an additional activation is required.

If one of your activations remains unused, you can use it to license SPSS on your machine. Otherwise, you will need to purchase a new license.

To activate SPSS you will need to open the License Authorization Wizard following the instructions below:
Windows users
At a very high level...
SPSS Statistics Base is useful for learning basic statistics. If non-linear regression, GLM, MANOVA or other more advanced functions are required, students should purchase SPSS Standard at a minimum. Students who need to perform missing values analysis or categories will require SPSS Premium.

Amos is required to perform structural equation modelling. Purchasing Amos alone does not provide access to SPSS Statistics software.

For v28

Base Grad Packs now include bootstrapping and data preparation capabilities
Standard Grad Packs include bootstrapping, data preparation and custom tables functions

If you are unsure we recommend checking with your university or college, or if you don't know which Statistics functions you need, purchase SPSS Statistics Premium which contains all the stats modules. For more detail on the specific functionality, check out the detailed guide.
Click here for a Detailed Guide to SPSS Grad Pack Features (PDF)
During Checkout

We recommend using your university or academic Institution issued email address because this is the fastest way to get your SPSS Grad Pack license code and download link, usually within 10 minutes.

After Purchase

We send you an email confirming your purchase, which is followed by a second email with the download link to your SPSS Grad Pack, please allow 10 minutes for this process to occur, and also check your spam/junk folder as sometimes our second email sneaks into there.

Note

If using a generic email such as Gmail or Hotmail during Checkout you will be emailed a link to a form to upload your student proof and once approved we release your license code.

A Grad Pack is exclusively for a student who is currently enrolled in an higher educational institution, to obtain a degree or participate in a continuing education program. Once purchased, the student must only use the SPSS Grad Pack for non-commercial academic research, such as completing assignments and university research.

v28 is the more recent release (mid 2021) and better suited to recent operating systems. The v28 Base edition and v28 Standard edition now include some features which are only available in the Premium edition of v26. To check which version suits your machine use "System Requirements" link.

Click here for a pdf of new features in SPSS v28.

Purchase v26 only if you have been instructed by your course coordinator or if your Windows operating system does not support 64-bit programs. Click here to view and purchase v26 Grad Pack options

SPSS Grad Packs run for a fixed amount of time and cannot be renewed as such. If you are still a student and need access to SPSS again, you simply purchase a new Grad Pack for the required amount of time (6 months, 12 months or 2 years). If you buy the same version (eg version 26) you will not need to re-install the software - just run the License Authorization Wizard and use the new code. If you have any issues, click here for more FAQ's

Still need help? Check out our comprehensive frequently asked questions

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SPSS Grad Pack for Students v28 Selection

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IBM restricts Grad Pack licenses to 2 activations to be used on 2 separate machines (1 activation per machine) provided you are the only user of the license on both machines. Once activated your license cannot be deactivated, suspended, paused or transferred to another machine.

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Vorteile:

i.d.R. schon verfügbar

viele YouTube-Tutorials,

umfangreiche Literatur

Nachteile:

statistische Funktionen begrenzt

keine nichtparametrischen Tests

Aktivieren des Datenanalysetools
(s. Post unten)

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... macht wichtige Verfahren verfügbar, z. B. multiple Regression, Varianzanalyse,  Histogramme ...

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Schätzung des nötigen Umfangs der Stichprobe für signifikante Ergebnisse

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Schweitzer (2003): Statistik mit Excel. Tricks und Hinweise für einen wirkungsvollen Einsatz ... für Statistiken und deren Interpretationen.
https://katalog.slub-dresden.de/id/0-364672692/

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17 March 2020 - Release 3.1.9.7

Windows

Changed the behavior of the "X-Y plot for a range of values" which allowed plotting graphs after changing input parameters in the main window without hitting the "Calculate" button which, however, is required to update the "X-Y plot for a range of values" with the new input parameters from the main dialog.

21 February 2020 - Release 3.1.9.6

Mac and Windows

Fixed a bug in z tests: Generic z test: Analysis: Criterion: Compute alpha: The critical z was calculated incorrectly.

Fixed a bug in t tests: Linear bivariate regression: One group, size of slope: |sy/sx| was sometimes calculated inccorrecty.

14 January 2020 - Release 3.1.9.5

Mac

Fixed a bug that caused the "Options" button (which is available for some tests in the main window) to disappear when "Hide distributions & control" was selected.

6 February 2019 - Release 3.1.9.4

Mac and Windows

Fixed a bug in t tests: Linear bivariate regression: One group, size of slope. Negative effect directions, that is, slope|H1 < slope|H0, were not always handled correclty. Furthermore, the restriction (|slope| < |sy/sx|) on the effect size, which was previously ignored, is now checked.

7 July 2017 - Release 3.1.9.3

Mac

Fixed a bug that could cause crashes.

28 March 2014 - Release 3.1.9.2

Mac

Fixed a bug in the χ² tests: Goodness-of-fit tests: Contingency tables module which prevented the computed effect size from appearing in the effect size drawer.

Windows

Fixed a bug that could occur under very specific circumstances when transferring an effect size from the effect size drawer to the main window.

10 March 2014 - Release 3.1.9.1

Mac

Now includes the calculator that previously has been included only in the Windows version.

4 February 2014 - Release 3.1.9

Mac and Windows

Fixed a bug in the sign test's sensitivity analysis which led to an offset of -0.5 in the reported effect size.
Changed the behaviour of all tests based on the binomial distribution. The upper and lower limits are now always within the range [0,n] instead of [-1,n+1]. This change may lead to alpha values larger than the requested alpha values, but now we have the advantage that the upper and lower limits correspond to actual decision boundaries. For instance, in a two-sided test H0 is rejected if, for the observed number x of successes, it holds that x <= lower limit or x >= upper limit. Note, however, that the change affects the results only when N is very small.

31 January 2014 - Release 3.1.8

Mac and Windows

Improvements in the logistic regression module: (1) improved numerical stability (in particular for lognormal distributed covariates); (2) additional validity checks for input parameters (this applies also to the poisson regression module); (3) in sensitivity analyses the handling of cases in which the power does not increase monotonically with effect size is improved: an additional Actual power output field has been added; a deviation of this actual power value from the one requested on the input side indicates such cases; it is recommended that you check how the power depends on the effect size in the plot window.

19 April 2013 - Release 3.1.7

Mac and Windows

Fixed a problem in the exact test of Proportions: Inequality, two independent groups (uncontional). The problem only occurred when p1 > p2.

18 Frebruary 2013 - Release 3.1.6

Mac and Windows

Fixed a problem in the sensitivity analysis of the logistic regression. The problem only occurred when p2 >= p1.

Mac

Fixed a problem in Fisher's exact test.

12 September 2012 - Release 3.1.5.1

Mac

Fixed a problem with the effect size drawers of ANOVA: Fixed effects. The drawers now appear correctly after clicking on the Determine button.

20 August 2012 - Release 3.1.5

Mac and Windows

Fixed a problem in the test of equality of two variances. The problem did not occur when both sample sizes were identical.
Fixed a problem in calculating the effect size from variances in the repeated measures ANOVA.

3 July 2012 - Release 3.1.4

Mac and Windows

Added an options dialog to the repeated-measures ANOVA which allows a more flexible specification of effect sizes.
Fixed a problem in calculating the sample size for Fisher's exact test. The problem did not occur with post hoc analyses.

22 June 2011 - Release 3.1.3

Mac and Windows

Fixed a bug in the ANCOVA module. Changing the number of covariates now correctly leads to the appropriate change in the denominator degrees of freedom.

5 January 2010 - Release 3.1.2

Mac and Windows

Renamed the Repetitions parameter in repeated measures procedures to Number of measurements (Repetitions was misleading because it incorrectly suggested that the first measurement would not be counted).
Fixed a problem in the sensitivity analysis of the logistic regression procedure: There was an error if Odds ratio was chosen as the effect size. The problem did not occur when the effect size was specified in terms of Two probabilities.

Mac

The Window menu now contains the option to hide the distributions plot and the protocol section ( Hide distributions & protocol menu item) so that G*Power can be accommodated to small screens. This option has been available for some time in the Windows version (see View menu).

16 December 2009 - Release 3.1

Mac

Added procedures to analyze the power of tests for single correlations based on the tetrachoric model, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression.

08 December 2009 - Release 3.1.1

Windows

Re-enabled options dialog for Correlation: Bivariate normal model.

29 June 2009 - Release 3.1

Windows

Added procedures to analyze the power of tests referring to single correlations based on the tetrachoric model, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression.

24 January 2008 - Release 3.0.10

Mac and Windows

Fixed a problem in the X-Y plot for a range of values for Generic F tests. The degrees of freedom were not properly set in the graph, leading to erroneous plot values.

22 January 2008 - Release 3.0.9

Mac

Eliminated the brushed metal look for better readability under Mac OS X 10.5.

Windows

Fixed some minor GUI problems (buttons had German titles; button in file dialog named "open" instead of "save").
Fixed problems with distribution plots (plots were sometimes not appropriately clipped when copied or saved as metafile; drawing glitches with some very steep curves).
The file dialog shown when saving graphs or protocols now uses the user's home directory (myDocuments) as defaults directory.

10 October 2007 - Release 3.0.8

Mac and Windows

Fixed a serious bug in the CDF routine of the noncentral t distribution introduced in the bugfix release 3.0.7. Please update immediately if you installed version 3.0.7.

8 October 2007 - Release 3.0.7

Mac and Windows

Fixed a bug in the function calculating the CDF of the noncentral t-distribution that occasionally led to (obviously) wrong values when p was very close to 1. All power routines based on the t distribution were affected by this bug.

14 August 2007 - Release 3.0.6

Mac

Fixed a bug in the routine that draws the central and noncentral t distributions for two-tailed tests. When alpha was very small, this bug could cause G*Power to crash.

03 July 2007 - Release 3.0.5

Mac and Windows

Fixed a bug in the Power Plot (opened using the X-Y-plot for a range of values button) for F tests, MANOVA: Global effects and F Tests, MANOVA: Special effects and interactions. Sometimes some of the variables were not correctly set in the plot procedure which led to erroneous values in the graphs and the associated tables.

26 June 2007 - Release 3.0.4

Mac and Windows

Fixed a bug in the Power Plot (opened using the X-Y-plot for a range of values button) for F Tests, Multiple Regression: Special (R2 increase). The numerator df value was not always correctly determined in the plot procedure which led to erroneous values in the graphs and the associated tables.
Fixed some minor problems with t tests. G*Power now checkes for invalid null effect sizes in a priori analyses. The t distribution PDF routine is now more robust for very large degrees of freedom by explicitly using a normal approximation in these cases.
When the Power Plot window was first opened by pressing the X-Y plot for a range of values button, the default was to show 4 plots simultaneously. The default has been changed to 1 plot.
Corrected some parsing errors in the calculator (in the Mac version, this only concerns text input in normal input fields).
Corrected a label in the effect size drawer for ANOVA: Fixed effects, omnibus, one-way. In the From variance input mode, the Variance within group field was erroneously labeled Error variance.

Windows

Fixed a problem with moving the main window when the effect size drawer is open. Sometimes the mouse pointer appeared to be "glued" to the window and the movement could not be stopped properly.

1 March 2007 - Release 3.0.3

Mac and Windows:

Fixed a bug in the X-Y plots for a range of values for F Tests, ANOVA: Fixed effects, special, main effects and interactions. The df1 value was not always correctly determined in the plot procedure which led to erroneous values in the plots.
Fixed the problem in the plot procedure that (due to rounding errors) the last point on the x-axis was sometimes not included in the plot.

28 February 2007 - Release 3.0.2

Mac and Windows

Fixed a probem with tooltips for effect size conventions which were not always shown.

Windows

Added options mainly intended to make G*Power usable with low resolution displays (800 x 600 pixels)
The distribution/protocol view and the test/analysis selection view in the main window can be hidden temporarily to save space. To hide/show these sub-views press F4 (plot/protocol) and F5 (test/analysis), respectively, while the main window is active. There are also corresponding entries in the View menu.
The Graph window can now be made resizable. To do this choose "Resizable Window" in the View menu of the Graph window. Besides enabling (restricted) resizability this option initially shrinks the window to a size that fits into a 800 x 600 screen. Deselecting the option restores the Graph window to the fixed size for which G*Power was optimized.

Mac

Fixed a cosmetic problem when drawing "extreme" central and non-central distributions.

15 January 2007 - Release 3.0.1

Windows

Effect size calculation for t Tests, Difference between two indepent means (two groups), case n1 = n2: The wrong means-those of case n1 ≠ n2-were used to calcultate the effect size. This problem has been fixed.
Minor cosmetic changes.
New Readme file.
Updated installation instruction.

12.01.2007 - First release of version 3.0.0

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17 March 2020 - Release 3.1.9.7 Windows Changed the behavior of the "X-Y plot for a range of values" which allowed plotting graphs after changing input parameters in the main window without hitting the "Calculate" button which, however, is required to update the "X-Y plot for a range of values" with the new input parameters from the main dialog.

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G*Power - eine Einführung zur Berechnung der Stichprobengröße

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Konfidenzniveau der Stichprobe: Ein Prozentsatz, der angibt, wie sicher Sie sich sein können, dass die Population eine Antwort in einem bestimmten Bereich auswählen würde. Beispielsweise bedeutet ein Konfidenzniveau von 95 %, dass Sie zu 95 % sicher sein können, dass die Ergebnisse zwischen den Zahlen X und Y liegen.

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berechnung der mindestgröße einer stichprobe

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Konfidenzniveau der Stichprobe: Ein Prozentsatz, der angibt, wie sicher Sie sich sein können, dass die Population eine Antwort in einem bestimmten Bereich auswählen würde. Beispielsweise bedeutet ein Konfidenzniveau von 95 %, dass Sie zu 95 % sicher sein können, dass die Ergebnisse zwischen den Zahlen X und Y liegen.

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Vor- und Nachteile

Einführungsvideos

Downloadseite

Preise

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JASP - Free and User-Friendly Statistical Software

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Entirely for free, no strings attached.
Windows 64bit

The pre-installed version can be used if you cannot install JASP with the msi installer. Please note that Microsoft (and thus JASP) supports only Windows 10 and higher.

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Download JASP - JASP - Free and User-Friendly Statistical Software

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Download JASP Entirely for free, no strings attached. Windows Windows 64bit The pre-installed version can be used if you cannot install JASP with the msi installer. Please note that Microsoft (and thus JASP) supports only Windows 10 and higher. ... Continue reading →

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(Excel-Edition)
in SLUB kostenlos als E-Book
https://katalog.slub-dresden.de/id/0-1657939103/#detail

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ähnlich JASP

bessere Grafiken

mehr möglich bei Datenaufbereitung

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Welcome to the jamovi user-guide. This contains everything you need to know about getting up and running for jamovi. Note that there are also video tutorials available from , and the learning statistics with jamovi textbook for those who prefer those formats.

Installation

Windows

jamovi is available for Windows Vista (64-bit) and above. Installation on windows is quite straight-forward, and should be familiar to anyone who has installed software on Windows before. Download the latest version from the download page, and double-click the icon.

At some institutions (particularly universities), the "normal" approach to installing software is blocked by IT security policies. In this case, you can download our .zip version. To use this, simply download, unzip to a location on the computer, and naviagate to the bin folder. Double-clicking jamovi.exe will begin jamovi. It's possible that additional security restrictions prevent jamovi from working in this way, in which case it would be worth raising the issue with your IT staff.

macOS

The 1.6 series of jamovi (and newer) are available for macOS 10.13 (High Sierra) and newer. The 1.2 series is available for macOS 10.11 (El-Capitan) and newer. The 1.1 series is available for 10.9 (Mavericks) and newer. Note that .omv files written using a newer series are often not able to be opened by an older series. The minimum versions reflect the requirements of the corresponding R version which ships with each version.

To install jamovi on macOS, download the .dmg file ( downloads here), and double-click the downloaded file. This will present you with a "file view", and you can install jamovi by "dragging-and-dropping" the jamovi application to the Applications folder (in the usual way). After this, jamovi will appear in your applications, and can be started like any other installed application.

jamovi for macOS has an auto-update mechanism, and can alert you to when new versions are available. You can update your version of jamovi from the app menu (the three dots at the top right of the window). Note that this will only update you to the latest solid version.

Linux and Chromebooks

jamovi is currently available for Linux, (for all 'flatpak participating linux distributions' - which is most of them), and Chromebooks, from flathub.

Note: Some Chromebooks experience a blank screen issue when starting up jamovi. If you encounter this, there are instructions on how to fix this a little further down.

If you're new to flatpak/flathub, you'll need to follow the setup guide on our flathub page.

If you're an old hand at flatpak, you can install jamovi with the command:

flatpak install flathub org.jamovi.jamovi

and later, you can update your version of jamovi with:

Text not appearing in plots under linux

On some linux machines, the flatpak font cache is not up-to-date, resulting in plots in jamovi not displaying text correctly. To remedy this, you can run the following command at the terminal:

flatpak run --command=fc-cache org.jamovi.jamovi -f -v

This appears to be an issue with flatpaks, and we're working with the flatpak community to get to the bottom of it.

Blank screen at startup on Chromebooks

Some Chromebooks experience a blank screen when starting up jamovi. The cause of this issue is not completely clear at this time, however it can be fixed by disabling "Crostini GPU support".

Enter chrome://flags/ into the ChromeOS address bar. This will bring up "Experiments". Search for Crostini GPU Support and set it to disabled. After restarting your Chromebook the issue will be fixed. (Special thanks to @mulderc)

Getting Started

When first starting jamovi, you will be presented with a user interface which looks something like this.

To the left is the spreadsheet view, and to the right is where the results of statistical tests appear. Down the middle is a bar separating these two regions, and this can be dragged to the left or the right to change their sizes.

It is possible to simply begin typing values into the jamovi spreadsheet as you would any other spreadsheet software. Alternatively, existing data sets in a range of formats (CSV, SPSS, Stata, SAS) can be opened in jamovi. Additionally, there are a number of example data sets available in jamovi. To open a file, select the File tab at the top left hand corner, select 'Open' and then 'Examples' or 'This PC', depending on whether you want to open an example, or a file stored on your computer.

If jamovi does not open a CSV file correctly, do file an issue (bug report) in our GitHub issue tracker. We are keen to make our importer as robust as possible.

Analyses

Analyses can be selected from the analyses ribbon or menu along the top. Selecting an analysis will present an 'options panel' for that particular analysis, allowing you to assign different variables to different parts of the analysis, and select different options. At the same time, the results for the analysis will appear in the right 'Results panel', and will update as you make changes to the options.

When you have the analysis set up correctly, you can dismiss the analysis options by clicking the arrow to the top right of the optional panel. If you wish to return to these options, you can click on the results that were produced. In this way, you can return to any analysis that you (or say, a colleague) created earlier.

If you decide you no longer need a particular analysis, you can remove it with the results context menu. Right-clicking on the analysis results will bring up a menu, and by selecting 'Analysis', and then 'Remove', the analysis can be removed.

The Spreadsheet

In jamovi, data is represented in a spreadsheet, with each column representing a 'variable'.

Data Variables

The most commonly used variables in jamovi are 'Data Variables', these variables simply contain data either loaded from a data file, or 'typed in' by the user. Data variables can be one three data types:

and one of four measure types:

Nominal

Ordinal

Continuous

ID

The measure types are designated by the symbol in the header of the variable's column. Note that some combinations of data-type and measure-type don't make sense, and jamovi won't let you choose these.

Nominal and Ordinal are, predictably, for nominal and ordinal variables. Continuous is for variables with numeric values which are considered to be Interval or Ratio scales (Equivalent to Scale in SPSS). The ID measure type is, unlike the others, unique to jamovi. It's intended for variables that contain identifiers that you would almost never want to analyse. For example, a persons name, or a participant ID. The advantage of IDs, is that jamovi does not need to maintain a list of levels internally, which can improve performance when interacting with very large data sets.

When starting with a blank spreadsheet and typing values in, the data and measure types will change automatically depending on the data you enter. This is a good way to get a feel for which variable types go with which sorts of data. Similarly, when opening a data file, jamovi will infer the variable type from the data in each column. In both cases, this automatic approach may not be correct, and it may be necessary to manually specify the data and measure type with the variable editor.

The variable editor can be invoked by selecting 'Setup' from the data tab, double-clicking on the column header, or by pressing F3. The variable editor allows you to change the name of the variable, and (for data variables) the data type, the measure type, the order of the levels, and the label displayed for each level. The variable editor can be dismissed by clicking the close arrow, or by pressing F3 again.

New variables can be inserted or appended to the data set using the 'add' button from the data ribbon. The 'add' button also allows the addition of Computed variables.

Computed Variables

Computed Variables are those which take their value by performing a computation on other Variables. Computed Variables can be used for a range of purposes, including log transforms, z-scores, sum-scores, negative scoring and means.

Computed variable s can be added to the data set, with the 'add' button available on the data tab. This will produce a formula box where you can specify the formula. The usual arithmetic operators are available. Some examples of formulas are:

A + B LOG10(len) MEAN(A, B) (dose - VMEAN(dose)) / VSTDEV(dose) Z(dose)

In order, these are the sum of A and B, a log (base 10) transform of len, the mean of A and B, and the z-score of dose (twice).

There are many more functions available.

V-functions

A number of functions appear in pairs, one prefixed with a V and the other not. V functions perform their calculation on a variable as a whole, where as non- V functions perform their calculation row by row. For example, MEAN(A, B) will produce the mean of A and B for each row. Where as VMEAN(A) gives the mean of all the values in A.

Additionally V functions support a group_by argument (in 0.9.6 and up). When a group_by variable is specified, a separate value is calculated for each level of the group_by variable. In the following example:

VMEAN(len, group_by=dose)

A separate mean is calculated for each level of dose, and each value in the computed variable will be the mean corresponding to it's row's value of dose.

Recoded Variables

Transformed and recoded variables are also available. See this blog post for details.

Filters

Filters in jamovi allow you to filter out rows that you don't want included in your analysis. For example, you might want to only include people's survey responses if they explicitly consented to having their data used, or you might want to exclude all left-handed people, or perhaps people who score 'below chance' in an experimental task. In some cases you just want to exclude extreme scores, for example those that score more than 3 standard deviations from the mean.

The filters in jamovi are build on top of jamovi's computed variable formula system, which allows the building of arbitrarily complex formulas.

More details about filters are covered in this blog post

Updating data

Once a data set is set up with filters, computed variables, transforms and analyses, sometimes you may want to update the data. This may be for a number of reasons - It might be that you have a new data set, that you want to apply the analyses you performed earlier to it, or you may be conducting an experiment where you're tesing a number of participants, and you now have an additional participant's data to analyse. By importing into an existing data set you can re-run your analyses without having to re-perform all of your data cleaning and analysis steps (making your jamovi files behave a bit like scripts).

For a video introduction to import and templates in jamovi, see this blog post.

Single-file Import

Import is available from the file menu (☰) at the top left of jamovi. When you import a file into an existing data set, the following operations are performed.

1. All the rows of the existing data set are deleted.

2. All the (original) names of the existing columns are matched to the names of the columns from the new data set.

3. The new values are imported to the existing columns, keeping the data and measure types from the existing data set.

4. The new columns which did not match names in the original data set are appended to the right of the data set.

If no new column matches the column names in the existing data set, then those columns are left blank.

Following a file import, all the filters, computed variables, transforms and analyses update.

Multi-file Import

It is also possible to import multiple files at once. This can be useful when you are combining multiple data sets, for example, where each file represents a participant. The process is the same as the single-file import detailed above, except that you select multiple files when performing the import. You can do this by holding down control or shift when selecting data files, or with the 'multi-select' button at the top of the import dialog.

When importing multiple files like this, they are combined vertically with the rows of the second file appearing below the first, the rows of the third file appearing below the second, and so on. An additional column called source is created detailing which file each row has come from. This can be useful when you need to 'split-by' or 'group-by' each participant. This column can be particularly useful to use with the group_by argument to V-functions described above.

At present, there is no way to combine files horizontally in jamovi.

Templates

Templates in jamovi are special data sets that are analagous to script files in more traditional statistical environments. They are a way to specify data types, computations, filters, transforms, and analyses in advance. Once the data becomes available, it can be imported into the template, and the template will update accordingly. The nice thing about jamovi templates is that they are entirely specified with the familiar user interface, and do not require working with a 'syntax' or code.

To save a data set as a template, select 'Export' from the file menu, and select 'jamovi template' from the file type box. When opening a template, you'll see it contains columns but no rows, and that all the analysis results are blank. To use the template, import a new data set (or data sets) using the file import described above. The data will update, followed by the filters, computed variables, and finally the analysis results.

jamovi templates are also a great way to provide analyses to less capable students or colleagues.

Copy and Paste

jamovi produces nice APA formatted tables, and attractive plots. It is often useful to be able to copy and paste these, perhaps into a Word document, or into an email to a colleague. To copy results, right click on the object of interest, and from the menu select exactly what you want to copy. The menu allows you to choose to copy, say only the image, or the entire analysis. Selecting copy, copies the content to the clipboard, and can be pasted into the other program in the usual way.

Syntax Mode

jamovi also provides an "R Syntax Mode", in this mode, jamovi produces equivalent R code for each analysis. To change to syntax mode, select the Application menu to the top right of jamovi (a button with three dots), and check the "Syntax mode" checkbox there. It is possible to leave syntax mode by clicking this a second time.

In syntax mode, analyses continue to operate as before, but now they produce R syntax, and 'ascii output' like an R session. Like all results objects in jamovi, you can right click on these items (including the R syntax) and copy and paste them, for example, into an R session.

At present, the provided R syntax does not include the data import step, and this must be performed manually. There are many resources explaining how to import data into R, and we recommend you take a look at these (Most analyses in jamovi require data as a data frame).

Another R feature that may be of interest is the Rj module, which allows you to use R code to analyse data directly in jamovi.

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Welcome to the jamovi user-guide. This contains everything you need to know about getting up and running for jamovi. Note that there are also video tutorials available from , and the learning statistics with jamovi textbook for those who prefer those formats. Windows jamovi is available for Windows Vista (64-bit) and above.

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Vorteile:

arbeitet in Excel als Add-In

kein Datenex- bzw. import

Beispieldatensätzen verfügbar

Nachteile:

kostenpflichtig

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Wählen Sie Ihren Arbeitsgebiet

Dieses leistungsfähige und zugleich flexible Add-on zur statistischen Datenerfassung ermöglicht es Ihnen, Ihre Ergebnisse in Excel zu analysieren, zu personalisieren und mit anderen zu teilen. Nach der XLSTAT-Testversion ist eine kostenlose lebenslange limitierte Version erhältlich.

Mit diesem intuitiven Excel-Add-On können Sie Risikoanaylsen in unterschiedlichsten Bereichen durchführen und Antworten auf ein breites Spektrum an Fragen finden.

Mit diesem extrem leistungsstarkem Optimierungs-Solver für Microsoft Excel finden Sie in kürzester Zeit Lösungen und erhöhen Ihre Produktivität beim Prozess der Entscheidungsfindung.

Kreieren Sie wirkungsvolle Grafiken, indem sie verschiedene Grafikebenen übereinanderlegen (Histogramme, Streudiagramme, Liniendiagramme, Balkendiagramme, etc.). Exportieren Sie ihre Darstellungen im .PNG- oder .SVG-Format.

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Wählen Sie Ihren Arbeitsgebiet Dieses leistungsfähige und zugleich flexible Add-on zur statistischen Datenerfassung ermöglicht es Ihnen, Ihre Ergebnisse in Excel zu analysieren, zu personalisieren und mit anderen zu teilen. Nach der XLSTAT-Testversion ist eine kostenlose lebenslange limitierte Version erhältlich. Mit diesem intuitiven Excel-Add-On können Sie Risikoanaylsen in unterschiedlichsten Bereichen durchführen und Antworten auf ein breites Spektrum an Fragen finden.

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zu Videos

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zu Webseiten

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englisch, 49 min

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JASP vs. Jamovi 2020 || An In-Depth Comparison

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Hearne-Software GmbH

H.-Heine-Uni Düsseldorf

Jesussek, Mathias (AT)

Marsmann et al.
Universität Amsterdam  (NL)

Walther, Björn

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letzte Aktualisierung: 21.05.2021
letzte Revision: 11.04.2021