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1) Correlation Analysis:Perform assumption checks for linearity, normality, homogeneity, and homoscedasticity.

  • Perform data screening making sure to check for accuracy, missing, outliers.
  • Capture a Correlation Matrix and Visual to express the relationship between each of the variables in the iris dataset.  
  • What is the correlated effect? Provide an interpretation . Support your response with results captured from the correlation analysis.  
  • Calculate the Variance. What does it tell us?
  • Calculate the Covariance. What does it tell us?

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    Assumptions_Check.PNG





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    Correlation amid the variables.PNGCorrelation amid the variables Visualization..PNG




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    Variance....PNG

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    Covariance.PNG



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8 Attachments
Assumptions_Check.PNG
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Correlation amid the variables Visualization..PNG
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Correlation amid the variables.PNG
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Covariance.PNG
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Data Screening..PNG
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Data Screening.There are no missing values..PNG
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Iris_data set set-up.PNG
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Variance....PNG
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