Understanding Correlations Assignment Paper

Understanding Correlations Assignment Paper

Need Help Writing an Essay?

Tell us about your assignment and we will find the best writer for your paper

Write My Essay For Me

Answer the following questions using the Week 6 Correlations Exercises SPSS Output provided in this week’s Learning Resources.

What is the strongest correlation in the matrix? (Provide the correlation value and the names of variables)
What is the weakest correlation in the matrix? (Provide the correlation value and the names of variables)
How many original correlations are present on the matrix?
What does the entry of 1.00 indicate on the diagonal of the matrix? Understanding Correlations Assignment Paper
Indicate the strength and direction of the relationship between body mass index (BMI) and physical health component subscale.
Which variable is most strongly correlated with BMI? What is the correlational coefficient? What is the sample size for this relationship?
What is the mean and standard deviation for BMI and doctor visits?
What is the mean and standard deviation for weight and BMI?
Describe the strength and direction of the relationship between weight and BMI.
Describe the scatterplot. What information does it provide to a researcher? Understanding Correlations Assignment Paper

ORDER A PLAGIARISM-FREE PAPER HERE

Correlations

Introduction

Statistical analysis is a crucial skill for nurses. The care process entails gathering data to assess patient condition so as to establish the most effective modality to use. Statistical packages such as SPSS greatly help with the data analysis part. Notably, care providers need to understand how to interpret the results of data analysis so that they can make informed decisions. As such, this paper looks into understanding correlations and measures of central tendency as shown in an SPSS output matrix.

Responses

Q1. The correlation value between variables can range between -1 and +1. The more the value tends to +/- 1, the stronger the relationship. The strongest correlation in the matrix is between physical health and the number of doctor visits in the past 12 months. This is indicated by the correlation value of -0.316. It is worth noting that strength of correlation depends on the magnitude of the value and not directionality (Leech, 2021)Understanding Correlations Assignment Paper.

Q2. Weakness of correlation is indicated by how much the correlation value tends to zero (Almquist et al, 2020). A value of zero indicates a linear relationship of zero. The weakest correlation in the matrix is between mental health and body mass index (BMI) as indicated by the correlation value of -0.078. As noted, it is the absolute value that is considered and not its directionality.

Q3. Correlates are variables with a connection of any type between them (Pallant, 2020). As such, the number of original correlates in the matrix is six. They are between: number of doctor visits and BMI, number of doctor visits and physical health, number of doctor visits and mental health, BMI and physical health, BMI and mental health, and physical health and mental health.

Q4. The entry of 1.00 in the diagonal of the matrix indicates existence of perfect correlation (Pallant, 2020)Understanding Correlations Assignment Paper. This is impossible with two different variables and only occurs when a variable is correlated with itself, essentially resulting in a singularity denoted by the value of 1.00.

Q5. The relationship between BMI and physical health is weak and of inverse nature. Relationship between variables is considered strong when the correlation value is greater than 0.7 (Abu-Bader, 2021). With a correlation value of -0.134, the relationship can be surmised to be weak. The negative value indicates an inverse relationship, implying that increasing BMI indicates declining physical health.

Q6. Physical health is the variable most strongly correlated with BMI. This is indicated by the correlation coefficient of -0.134. The sample size for establishing this relationship is 866 as shown in the N-value intersection between BMI and physical health in the matrix.

Q7. The mean for BMI is 29.2226. The mean for number of doctor visits in the past 12 months is 6.80. The standard deviation for BMI is 7.37893. The standard deviation for number of doctor visits in the past 12 months is 12.720.

Q8. The mean for BMI is 29.2226. The mean for weight is 171.4624 pounds. The standard deviation for BMI is 7.37893. The standard deviation for weight is 45.44083.

Q9. There is very strong relationship between weight and BMI. This is indicated by the value of 0.937 in the scatter-plot’s matrix. The correlation value is positive indicating direct relationship between the two variables, essentially implying that an increase in weight relates to an increase in BMI (Kim et al, 2020)Understanding Correlations Assignment Paper.

Q10. A scatter-plot is a two-axes graphical illustration of the relationship between two variables. All points are plotted on the graph revealing the presence or absence of correlation and dispersion of values. The values in the shown scatter-plot are tightly clustered along a linear line, indicating strong relationship and low variance between weight and BMI (Kim et al, 2020).

Conclusion

The work above indicates my interpretation of values for correlation coefficients, matrices, test variables, measures of central tendency and scatter plots. It is my hope that this paper demonstrates good understanding of statistical analysis and interpreting SPSS output tables.

References

Abu-Bader, S. H. (2021). Using statistical methods in social science research: With a

complete SPSS guide. Oxford University Press, USA.

Almquist, Y. B., Kvart, S., & Brännström, L. (2020). A practical guide to quantitative

methods with SPSS.

ORDER TODAY

Kim, M., Mallory, C., & Valerio, T. (2020). Statistics for evidence-based practice in nursing.

Jones & Bartlett Publishers.

Leech, N. L. (2021). Introduction to SPSS for Mixed Analysis. In The Routledge Reviewer’s

Guide to Mixed Methods Analysis (pp. 355-376). Routledge.

Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM

SPSS. Routledge. Understanding Correlations Assignment Paper