ANANALYSIS PLAN: INFERENTIAL STATISTICS
InstitutionAffiliated:
Dateof submission:
RegressionAnalysis
Regression Statistics 

Multiple R 
0.659105426 
R Square 
0.534419963 
Adjusted R Square 
0.72555083 
Standard Error 
3.415419192 
Observations 
10 
Rsquared (R²)
Inthe regression statistic, the R square (R²) tests the goodness offit of the model, in this case, it means that 53.4% of the variationsin GDP growth rate are explained by variations in vaccinationcoverage in the 10 states, both top five and bottom five. 46.6% isexplained by other factors that are not incorporated in the model[ CITATION Rox15 l 1033 ].
AdjustedR squared (R̃²)
Variationsin children healthcare are explained up to 72.55% by the model with27.45% explained by other exogenous factors that are not in themodel.
Standarderror (SE)
Thestandard error (SE) is a measure of the magnitude of errors ofprediction. It measures the variation around the line of best fit.SE= 3.415isthe error of predicting the value of the efficiency of PPACA policiesin the control of MMR in children using regression analysis. Itdenotes the standard error of the regression analysis conducted onthe data obtained.
TStatistics
Itdenotes how a variable varies or differentiate from the mean. Thelarger the value, the more the variable varies from the data’s meanhence resulting in more error chances.
ANOVAAnalysis
ANOVA 

  
df 
SS 
MS 
F 
Significance F 
Regression 
5 
35.83964697 
7.167929393 
0.614477082 
0.036997375 
Residual 
4 
46.66035303 
11.66508826 

Total 
9 
82.5 
  
  
  
ANOVAis used to determine the usefulness of the overall model testing itif its
Letthe null and alternative hypotheses be such that:
H_{o}:no impact
H_{a}:impact to increase immunization.
Sincethe p value or significance F of (0.037) is less than thesignificance level (0.05), therefore, we reject the null hypothesisin favour of the alternative hypothesis, that is 0.037 <0.05
Decision:Reject H_{o} meaning that there is sufficient evidence to show that the model isuseful[CITATION Jen08 l 1033 ].
ChiSquareAnalysis
Chisquareanalysis cannot be conducted in such data as there has to be a set ofdata of both actual results of immunization and vaccination of theuninsured people, as well as the expected outcome. It requirescomparison of two sets of data. It can only be applicable if thecomparison is between the top five and the bottom five.
Inthe case of comparing between the top and bottom five, assuming thebottom five to the actual data and top five the expected, thechisquare value is 2.50899. If the value equals or is more than thecomputed chisquare, it means there is a relationship between thevariables at hand[ CITATION DRe11 l 1033 ].
Calculatingchisquare is through the determination of degree of freedom. Formulais df = (No of rows – 1) x (No of columns – 1) = (51) * (51).It will be 4*4 = 16. In this case, calculating was conducted with a pvalue of 0.05.
References
Barton, J. P. (2008). Medical Statistics: A guide to Data Analysis and Critical Appraisal. Massachusetts, USA: John Wiley & Sons.
D. Remenyi, D. R. (2011). An Introduction to Statistics Using Microsoft Excel. UK: Academic Conferences Limited.
Roxy Peck, C. O. (2015). Introduction to Statistics and Data Anlaysis. Boston, USA: Cengage Learning.