Statistical Analysis

[Name of the Institute]

Statistical Analysis

Question 1

Correlations

 

 

Delivery Reliability

Production Satisfaction

Technical Support

Sales Force

Overall Satisfaction in January

Overall Satisfaction in June

Delivery Reliability

Pearson Correlation

1

-0.19

0.058

0.042

0.068

0.065

 

Sig. (2-tailed)

 

0.17

0.675

0.764

0.627

0.642

 

N

50

50

50

50

50

50

Production Satisfaction

Pearson Correlation

-0.19

1

0.019

-0.152

0.266

0.201

 

Sig. (2-tailed)

0.17

 

0.891

0.274

0.052

0.145

 

N

50

50

50

50

50

50

Technical Support

Pearson Correlation

0.058

0.019

1

-0.022

0.031

-0.036

 

Sig. (2-tailed)

0.675

0.891

 

0.873

0.826

0.794

 

N

50

50

50

50

50

50

Sales Force

Pearson Correlation

0.042

-0.152

-0.022

1

0.09

0.057

 

Sig. (2-tailed)

0.764

0.274

0.873

 

0.516

0.684

 

N

50

50

50

50

50

50

Overall Satisfaction in January

Pearson Correlation

0.068

0.266

0.031

0.09

1

0.058

 

Sig. (2-tailed)

0.627

0.052

0.826

0.516

 

0.679

 

N

50

50

50

50

50

50

Overall Satisfaction in June

Pearson Correlation

0.065

0.201

-0.036

0.057

0.058

1

 

Sig. (2-tailed)

0.642

0.145

0.794

0.684

0.679

 

 

N

50

50

50

50

50

50

 

 

 

 

 

 

 

 

As it can be seen in the table above, all the scale variables has been tested to see the amount of variance, which they explain for each other respectively. Through the values of coefficient of correlation, we can deduce that these variables are not connected to each other significantly and they don't explain variance amongst them. Similar can be deduced through the p ...