Correlation Application and Interpretation
QUESTION
Assessment 2 Instructions: Correlation Application and Interpretation
Complete an SPSS data analysis report to analyze correlation for assigned variables.
Exploring the associations between some variables in the courseroom using correlations might provide some important information about learner success. You’ll need to pay attention to both magnitude, which is the strength of the association, and directionality, which is the direction (positive or negative) of the association. During this assessment, you’ll start learning about how to best approach correlational analyses like these and start getting some answers. You’ll explore the relationships that may or may not exist in your courseroom data.
In this assessment, you’ll get a chance to run and interpret your first inferential statistics analysis: correlations. Your readings and the Course Study Guide will help you in your efforts.
Correlation Application and Interpretation
ANSWER
Correlation Application and Interpretation
Learner Name
Capella University
Due date
Data Analysis Plan
Variable Definition Measure
Quiz 1 number of correct answers Count
GPA Previous grade point average continuous
Total Total number of points earned in class Continuous
Final Final exam: number of correct answers Count
Research question.
Is there significant linear relationship between the variables quqiz1, GPA, Total and Final.
Hypothesis
H0: There is linear relationship between the variables quqiz1, GPA, Total and Final.
H1: There is no linear relationship between the variables quqiz1, GPA, Total and Final
Testing Assumptions
Descriptive Statistics
N Mean Std. Deviation Variance Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error
final 105 61.84 7.635 58.291 -.341 .236 -.277 .467
gpa 105 2.8622 .71266 .508 -.220 .236 -.688 .467
quiz1 105 7.47 2.481 6.155 -.851 .236 .162 .467
total 105 100.09 13.427 180.291 -.757 .236 1.146 .467
Valid N (listwise) 105
From the skewness and kurtosis section of the table, all the data except the kurtosis of totals are less than +1 and therefore are within the range of normality. The distribution of final, GPA and quiz1can be considered to come from a normal distribution.
Results and Interpretation
Correlations
quiz1 total final gpa
quiz1 Pearson Correlation 1 .797** .499** .152
Sig. (2-tailed) .000 .000 .121
N 105 105 105 105
total Pearson Correlation .797** 1 .875** .318**
Sig. (2-tailed) .000 .000 .001
N 105 105 105 105
final Pearson Correlation .499** .875** 1 .379**
Sig. (2-tailed) .000 .000 .000
N 105 105 105 105
gpa Pearson Correlation .152 .318** .379** 1
Sig. (2-tailed) .121 .001 .000
N 105 105 105 105
**. Correlation is significant at the 0.01 level (2-tailed).
There is a minimal positive correlation between GPA and the score in Quiz1, r(105)= .152, p>0.01(two tailed).
There is a statistically significant, strong positive correlation between the final score and the total score, r(105)= .875, p<0.01(two tailed).
There is statistically significant, moderate positive correlation between GPA and the final score, r(105)= .1379, p>0.01(two tailed).
In light of the above findings, there is a significant evidence to accept the null hypothesis and confirm that there exists a linear relationship between the GPA, final score, total score and the score for Quiz1.
Limitations of correlation analysis
Correlation can only give the nature and magnitude of two variables, by doing so ignoring all the other factors that may affect the relationship. It is also true to say correlation does not show the cause or effect of the relationship between the variables being studied.
Correlation on the other hand can only describe linear relationship.
Application
Correlation shows the direction and strength of correlation between two variables, (Chapman, 2012). In the medical field, it can be used to investigate the effect of a given drug against the symptoms of a disease.
When investigating the effect of a blood pressure medication against the blood pressure of a patient. Where the blood pressure number will be the dependent variable depending on the medication or dosage being administered which will be the independent variable.
Studying correlation is important in the field of medical research since it gives the relationships between two variables which is very important during drug testing.
References
Chapman, N. (Ed.). (2012). Correlation analysis in chemistry: recent advances.
Correlation Application and Interpretation