Homework SourseDescriptive Statistics Mean Std Deviation N X22 Satisfactio
Descriptive Statistics
Mean
Std. Deviation
N
X22 -- Satisfaction
5.28
1.326
349
X24 -- Likely to Recommend
4.87
1.531
349
Correlations
X22 -- Satisfaction
X24 -- Likely to Recommend
X22 -- Satisfaction
Pearson Correlation
1
.273**
Sig. (2-tailed)
.000
N
349
349
X24 -- Likely to Recommend
Pearson Correlation
.273**
1
Sig. (2-tailed)
.000
N
349
349
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
X22 -- Satisfaction
X24 -- Likely to Recommend
Kendall\'s tau_b
X22 -- Satisfaction
Correlation Coefficient
1.000
.236**
Sig. (2-tailed)
.
.000
N
349
349
X24 -- Likely to Recommend
Correlation Coefficient
.236**
1.000
Sig. (2-tailed)
.000
.
N
349
349
Spearman\'s rho
X22 -- Satisfaction
Correlation Coefficient
1.000
.277**
Sig. (2-tailed)
.
.000
N
349
349
X24 -- Likely to Recommend
Correlation Coefficient
.277**
1.000
Sig. (2-tailed)
.000
.
N
349
349
**. Correlation is significant at the 0.01 level (2-tailed).
3. Explain fully the concept of correlation between variables. Based on the questionnaire implemented and the SPSS outputs, does the Pearson Correlation reveal that there is a high or low correlation between the level of satisfaction and the likelihood to recommend? What was the Pearson Correlation computed to be .4, .6, .8, or 1.0? Don\'t guess. Explain fully.
| Descriptive Statistics | |||
| Mean | Std. Deviation | N | |
| X22 -- Satisfaction | 5.28 | 1.326 | 349 |
| X24 -- Likely to Recommend | 4.87 | 1.531 | 349 |
Solution
Correlation is any sort of relationship or connection that exists between variables. It shows the degree of relationship variables can have with each other. It ranges from 0-1 where 0 is no correlation and 1 means exactly the same like 100% correlation. There are many tyoes of correlation like pearson correlation, kendall\'s tau, spearsman correlation etc. The most famous and most widely used is Pearson.
Over here we see there are two variables, X22 satisfaction and X24 Likely to recommend. We are trying to establish correlation between them. The second table shows the pearson correlation between the two variables. The correlation between them is .273 which is in percentage terms just 27.3%. Which means the the mutual relationship between this two variables can be justifies till 27.3 % It is not a high correlation as to come into this category correlation should be more tha 70%.Hence we justify it to be low correlation.
The correlation coefficient of 1.00 means a perfect correlation & 0 means no-correlation as explained earlier. Pearson correlation from 0.4, 0.6, 0.8 to 1.0, indicates that as it increases, the correlation between the variable becomes higher.
