Difference between revisions of "Whitepapers"
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Significance testing using t-statistics is a critical component of the analysis of survey research data. mTAB enables the survey analyst to conveniently perform significance testing including the ability to colorize the results of significantly different observations within mTAB's spreadsheet report view. | Significance testing using t-statistics is a critical component of the analysis of survey research data. mTAB enables the survey analyst to conveniently perform significance testing including the ability to colorize the results of significantly different observations within mTAB's spreadsheet report view. | ||
| − | :[ | + | :[http://wikisupport.mtabsurveyanalysis.com/images/3/35/MTAB_WP_TSTAT_Statistics.pdf|Generating Independent Sample T-Stats - Whitepaper] |
:[http://support.mtabsurveyanalysis.com/sites/default/files/pdf_files/mTAB_WP_TSTAT_Statistics.pdf PDF: Generating Independent Sample T-Stats - Whitepaper] | :[http://support.mtabsurveyanalysis.com/sites/default/files/pdf_files/mTAB_WP_TSTAT_Statistics.pdf PDF: Generating Independent Sample T-Stats - Whitepaper] | ||
Revision as of 17:52, 26 August 2013
Generating Independent Sample t-statistics with mTAB in comparison to SPSS
Significance testing using t-statistics is a critical component of the analysis of survey research data. mTAB enables the survey analyst to conveniently perform significance testing including the ability to colorize the results of significantly different observations within mTAB's spreadsheet report view.
