T-test and Analysis of Variance (ANOVA) - Revision history

Sje025: /* More in-depth on the theoretical background */

2023-02-07T10:59:55Z

More in-depth on the theoretical background

← Older revision		Revision as of 10:59, 7 February 2023
Line 11:		Line 11:

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field, 2018; Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell, 2013; Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell, 2013; Ch. 6, 7, 8).

Sje025: /* More in-depth on the theoretical background */

2023-02-07T10:59:33Z

More in-depth on the theoretical background

← Older revision		Revision as of 10:59, 7 February 2023
Line 12:		Line 12:
	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell, 2013; Ch. 6, 7, 8).

Sje025 at 10:58, 7 February 2023

2023-02-07T10:58:05Z

← Older revision		Revision as of 10:58, 7 February 2023
Line 1:		Line 1:
	=Using jamovi=		=Using jamovi=
	~~The~~ [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|lecture]] ~~briefly~~ introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). ~~The~~ Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).		t-tests are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf\|second part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|another lecture]] covers multivariate analyses. It first introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). Then, the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, it will be described how several kinds of the ANOVA can be carried out in jamovi, starting with a simple One-Way ANOVA, extending it into a factorial ANOVA, adding continuous covariates (ANCOVA) and ending with a repeated-measures ANOVA.

	For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&index=30 video introduction] by Barton Poulson from datalab.cc.		For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&index=30 video introduction] by Barton Poulson from datalab.cc.

Sje025 at 17:51, 6 February 2023

2023-02-06T17:51:10Z

← Older revision		Revision as of 17:51, 6 February 2023
Line 1:		Line 1:
	=Using jamovi=		=Using jamovi=
	The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).		The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).

			For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&index=30 video introduction] by Barton Poulson from datalab.cc.

	=Using SPSS=		=Using SPSS=

Sje025 at 17:47, 6 February 2023

2023-02-06T17:47:39Z

← Older revision		Revision as of 17:47, 6 February 2023
Line 6:		Line 6:
	The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:~~DataFiles~~.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.		In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:~~AnalysisOfVariance_ExamplesMATLAB~~.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

Sje025 at 17:45, 6 February 2023

2023-02-06T17:45:43Z

← Older revision		Revision as of 17:45, 6 February 2023
Line 6:		Line 6:
	The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:~~Analysis_of_Variance_-_Assignment~~.pdf\|additional assignments]] and ~~the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.~~		In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	~~Finally, there are~~ two ZIP-files: [[Media:DataFiles.zip\|~~One~~]] ~~with~~ the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|~~another~~]] ~~containing~~ SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

Sje025 at 17:43, 6 February 2023

2023-02-06T17:43:37Z

← Older revision		Revision as of 17:43, 6 February 2023
Line 1:		Line 1:
	=Using jamovi=		=Using jamovi=
	~~TBA~~		The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).
	~~<!--~~
	#The [[Media:~~Correlation_and_regression_analysis_-_Lecture~~.pdf\|lecture]] ~~begins with a basic introduction (what are typical research questions, what kind of variables are~~ used, what assumptions and ~~requirements need to~~ be ~~met~~ to ~~apply the method~~)~~, continues~~ with ~~an overview over fundamental equations (incl.~~ some do~~-it-yourself~~ in Excel), ~~introduces then major regression types~~ (~~standard~~, ~~sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.~~).
	~~-->~~

	=Using SPSS=		=Using SPSS=
	The [[Media:~~Analysis_of_Variance_-_Lecture~~.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The ~~the~~ Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), ~~followd~~ by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).<br>		The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).<br>
	The [[Media:~~Analysis_of_Variance_-_PC-exercise~~.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with an brief introduction on the preparation of ~~ones~~ data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with an univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:Analysis_of_Variance_-_Assignment.pdf\|additional assignments]] and the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.		In addition, there is a file with [[Media:Analysis_of_Variance_-_Assignment.pdf\|additional assignments]] and the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.

	Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, ~~another~~ [[Media:~~Analysis_of_Variance_-_SyntaxOutput~~.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.		Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:~~Analysis_of_Variance_-_Step~~-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:~~ExamplesMATLAB~~.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

Sje025 at 10:47, 22 March 2021

2021-03-22T10:47:52Z

← Older revision		Revision as of 10:47, 22 March 2021
Line 1:		Line 1:
	=~~Theoretical~~ introduction=		=Using jamovi=
			TBA
			<!--
			#The [[Media:Correlation_and_regression_analysis_-_Lecture.pdf\|lecture]] begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.).
			-->

	The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).		=Using SPSS=
			The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).<br>
	The lecture includes practical examples for calculation: A [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand, as well as a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

	~~=Practical exercises using SPSS=~~
	The [[Media:Analysis_of_Variance_-_PC-exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with an brief introduction on the preparation of ones data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with an univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:Analysis_of_Variance_-_PC-exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with an brief introduction on the preparation of ones data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with an univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

Line 11:		Line 12:

	Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, another [[Media:Analysis_of_Variance_-_SyntaxOutput.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.		Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, another [[Media:Analysis_of_Variance_-_SyntaxOutput.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

			=More in-depth on the theoretical background=
			Both lecture slides include practical examples for calculation: A [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
			The slides on SPSS further contain a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

Sje025 at 17:05, 4 June 2019

2019-06-04T17:05:42Z

← Older revision		Revision as of 17:05, 4 June 2019
Line 3:		Line 3:
	The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).		The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).

	The lecture includes practical examples for calculation: An [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand, as well as a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The lecture includes practical examples for calculation: A [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand, as well as a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

	=Practical exercises using SPSS=		=Practical exercises using SPSS=

Sje025 at 17:05, 4 June 2019

2019-06-04T17:05:20Z

← Older revision		Revision as of 17:05, 4 June 2019
Line 3:		Line 3:
	The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).		The [[Media:Analysis_of_Variance_-_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followd by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).

	The lecture includes to practical examples for calculation: An [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand, as well as a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The lecture includes practical examples for calculation: An [[Media:Analysis_of_Variance_-_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand, as well as a [[Media:ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

	=Practical exercises using SPSS=		=Practical exercises using SPSS=

← Older revision		Revision as of 17:47, 6 February 2023
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	The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:~~DataFiles~~.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.		In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:~~AnalysisOfVariance_ExamplesMATLAB~~.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

← Older revision		Revision as of 17:45, 6 February 2023
Line 6:		Line 6:
	The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:~~Analysis_of_Variance_-_Assignment~~.pdf\|additional assignments]] and ~~the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.~~		In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf\|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles.zip\|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	~~Finally, there are~~ two ZIP-files: [[Media:DataFiles.zip\|~~One~~]] ~~with~~ the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|~~another~~]] ~~containing~~ SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).

← Older revision		Revision as of 17:43, 6 February 2023
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	=Using jamovi=		=Using jamovi=
	~~TBA~~		The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).
	~~<!--~~
	#The [[Media:~~Correlation_and_regression_analysis_-_Lecture~~.pdf\|lecture]] ~~begins with a basic introduction (what are typical research questions, what kind of variables are~~ used, what assumptions and ~~requirements need to~~ be ~~met~~ to ~~apply the method~~)~~, continues~~ with ~~an overview over fundamental equations (incl.~~ some do~~-it-yourself~~ in Excel), ~~introduces then major regression types~~ (~~standard~~, ~~sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.~~).
	~~-->~~

	=Using SPSS=		=Using SPSS=
	The [[Media:~~Analysis_of_Variance_-_Lecture~~.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The ~~the~~ Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), ~~followd~~ by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).<br>		The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf\|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).<br>
	The [[Media:~~Analysis_of_Variance_-_PC-exercise~~.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with an brief introduction on the preparation of ~~ones~~ data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with an univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.		The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf\|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.

	In addition, there is a file with [[Media:Analysis_of_Variance_-_Assignment.pdf\|additional assignments]] and the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.		In addition, there is a file with [[Media:Analysis_of_Variance_-_Assignment.pdf\|additional assignments]] and the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf\|solutions]] to it.

	Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, ~~another~~ [[Media:~~Analysis_of_Variance_-_SyntaxOutput~~.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.		Finally, there are two ZIP-files: [[Media:DataFiles.zip\|One]] with the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip\|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.

	=More in-depth on the theoretical background=		=More in-depth on the theoretical background=
	Both lecture slides include practical examples for calculation: A [[Media:~~Analysis_of_Variance_-_Step~~-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>		Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods\|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.<br>
	The slides on SPSS further contain a [[Media:~~ExamplesMATLAB~~.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).		The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip\|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik & Fidell (2013), Ch. 6, 7, 8).