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# Case Study on SPSS Assignment

Added on - 17 Feb 2021

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Case Study SPSS
INTRODUCTIONThere are different principle that are needed to be followed in order to analyse the data andextract valuable output within SPSS tool. Therefore, it is very important to consider someprinciples that are statistical methods must enable data to answer scientific question, statisticalanalysis is just more than a set of computations, provide assessment of variability and keep itsimple, check assumption properly and make analysis reproducible. In order to better, understandthe topic various question has been answered in this project report.QUESTION 11 Do people who are married have different pain medical outcome scores one month after MIthan those who are not?In order to determine the output to the question that is are married people have various painmedical outcome score one month after myocardial infraction as compared to those who are notmarried. It is observed that null hypothesis which is H0 and the values are positive on the otherside alternative hypothesis is H1 that is shows the negative value and output are not true.Between-Subjects FactorsValue LabelNMARRIED/NOT.00UNMARRIED311.00MARRIED166Descriptive StatisticsMARRIED/NOTMeanStd. DeviationNAGEUNMARRIED59.299.78531MARRIED55.668.484166Total56.238.776197MEDICAL OUTCOMESSCORE: PAINUNMARRIED65.564529.9910431MARRIED69.593424.85916166Total68.959425.69187197Multivariate Testsa1
EffectValueFHypothesisdfError dfSig.Partial EtaSquaredNoncent.ParameterObservedPowercInterceptPillai's Trace.9612403.659b2.000194.000.000.9614807.3181.000Wilks'Lambda.0392403.659b2.000194.000.000.9614807.3181.000Hotelling'sTrace24.7802403.659b2.000194.000.000.9614807.3181.000Roy'sLargest Root24.7802403.659b2.000194.000.000.9614807.3181.000maritalPillai's Trace.0292.929b2.000194.000.056.0295.857.566Wilks'Lambda.9712.929b2.000194.000.056.0295.857.566Hotelling'sTrace.0302.929b2.000194.000.056.0295.857.566Roy'sLargest Root.0302.929b2.000194.000.056.0295.857.566a. Design: Intercept + maritalb. Exact statisticc. Computed using alpha = .05MARRIED/NOTDependent VariableMARRIED/NOTMeanStd. Error95% Confidence IntervalLower BoundUpper BoundAGEUNMARRIED59.2901.56256.21062.371MARRIED55.657.67554.32556.988MEDICAL OUTCOMESSCORE: PAINUNMARRIED65.5654.61956.45674.673MARRIED69.5931.99665.65773.5302