Correlational Research Paper

Correlational Research Paper

Introduction

An analysis was carried out using the Statistical Package for the Social Sciences (SPSS) to assess the relationship between the number of visits participants made to the doctor in the last twelve months, body mass index (BMI), standardized physical health component, and standardized mental health component. The summary statistics and person correlation were used to investigate the relationship between the variables. Results obtained from the analysis were as discussed in the following sections.

Descriptive Summary

The number of visits to the doctor in the last twelve months was recorded from a total of N=997 participants. The mean number of visits made to the doctor in a year was 6.8 times (SD+/- 12.7), implying that the number of visits made to the doctor for most participants was 12.7 times above or below 6.8 times a year. The body mass index (BMI) was obtained from a total of N=970. The mean body mass index (BMI) was found to be 29.22, with most participants BMI values lying either 7.37 units above or below the mean. The average standardized physical health component score from N=839 was found to be 45.11, with most scores either 10.84 above or below the mean. Standardized scores for mental health were also obtained from N=893 participants, and the mean score on mental health was found to be 46.83 (SD+/- 10.81).

Correlation Results

In the interpretation of the correlation coefficient, the closer the value to a positive or negative one, the stronger the association between two variables (Schober et al., 2018). Some studies suggest that correlation ranging from 0.1-0.3 is weak, 0.31-0.5 is moderate, and a strong correlation is above 0.5 (Akoglu, 2018). While interpreting the correlation coefficient, the p-value helps identify if the relationship is significant or not significant.

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Table 1: Correlation Results

		Number of doctor visits, past 12 mo	Body Mass Index	Physical Health Component Score, standardized	Mental Health Component Score, standardized
Number of doctor visits, past 12 mo	PC	1	0.131	-0.316	-0.133
	P-val		0.000	0.000	0.000
Body Mass Index	PC		1	-0.134	-0.078
	P-val			0.000	0.022
Physical Health Component Score, standardized	PC			1	0.168
	P-val				0.000
Mental Health Component Score, standardized	PC				1
	P-val

 

The number of doctor visits in the past 12 months was found to have a significant positive correlation with body mass index (r=0.13, p<0.000). As the body mass index increases, the number of doctor visits also increases. This correlation was, however, weak.

The correlation between the number of doctor visits in the past 12 months was found to be negatively correlated to the physical health component score (r= -0.316, p<0.000). As physical health score increases, the number of doctor visits in a year reduces. Similarly, the correlation between the number of doctor visits and mental health component score was negative (r= -0.133, p<0.000), the number of doctor visits reduces as the mental health component score increases.

Body mass index was found to have a weak negative relationship with both the physical health component score (r= -0.134, p<0.000) and the mental health component score (r= -0.076, p=0.022). As the physical or mental health component increases, the body mass index decreases. Physical and mental health components had a weak positive relationship, though significant (r=0.168, p<0.000).

Scatter Plot

Another analysis was carried out to assess the relationship between body mass index and weight in pounds. The mean weight in pounds for N=971 participants was 171.46 (SD+/- 45.44). The correlation between body mass index and weight in pounds was found to be a strong positive relationship (r=0.937, p<0.000). As body weight increases, the body mass index also increases significantly. The strong positive relationship can also be clearly observed in the scatter plot below, exhibiting a linear pattern.

References

Akoglu H. (2018). User’s guide to correlation coefficients. Turkish Journal Of Emergency Medicine, 18(3), 91–93. https://doi.org/10.1016/j.tjem.2018.08.001

Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation Coefficients. Anaesthesia & Analgesia, 126(5), 1763–1768. doi:10.1213/ANE.0000000000002864

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Week Six Assignment
Assignment: Correlations
Is there a connection between caffeine and headaches? Is there an association between hospital wait times and patient care? Is there a relationship between antibiotic use and weight gain?
Correlation statistics all begin with a research question, and these research questions all seek to determine relationships between variables. Correlational analysis clarifies relationships, but there are many ways to formulate a correlation. Therefore, the strength of a correlation relies on the variables used and the interpretation of the results that may signify a statistically relevant association or relationship.

Photo Credit: [triloks]/[E+]/Getty Image
For this Assignment, you will examine how to interpret results obtained through a correlational analysis. You will evaluate the correlation results provided in the Week 6 Correlations Exercises SPSS output and will reflect on the meaning of the results for the variables examined.
To Prepare:
• Review the Week 6 Correlations Exercises SPSS Output provided in this week’s Learning Resources.
• Review the Learning Resources on how to interpret correlation results to determine the relationship between variables.
• Consider the results presented in the SPSS output and reflect on how you might interpret the results presented.
The Assignment: (2–3 pages)
Answer the following questions using the Week 6 Correlations Exercises SPSS Output provided in this week’s Learning Resources.
1. What is the strongest correlation in the matrix? (Provide the correlation value and the names of variables)
2. the names of variables)
3. How many original correlations are present on the matrix?
4. What does the entry of 1.00 indicate on the diagonal of the matrix?
5. Indicate the strength and direction of the relationship between body mass index (BMI) and physical health component subscale.
6. Which variable is most strongly correlated with BMI? What is the correlational coefficient? What is the sample size for this relationship?
7. What is the mean and standard deviation for BMI and doctor visits?
8. What is the mean and standard deviation for weight and BMI?
9. Describe the strength and direction of the relationship between weight and BMI.
10. Describe the scatterplot. What information does it provide to a researcher?
Reminder: The College of Nursing requires that all papers submitted include a title page, introduction, summary, and references. The Sample Paper provided at the Walden Writing Center provides an example of those required elements (available at https://academicguides.waldenu.edu/writingcenter/templates/general#s-lg-box-20293632). All papers submitted must use this formatting.

Describe the strongest and weakest correlation in the matrix. Provide the correlation value and the names of variables.–
Excellent 14 (14%) – 15 (15%)
The response accurately and clearly describes in detail the strongest and weakest correlation in the matrix.

The response includes an accurate and clear correlation value and the names of variables for both the strongest and weakest correlation in the matrix.
Good 12 (12%) – 13 (13%)
The response accurately describes the strongest and weakest correlation in the matrix.

The response includes an accurate correlation value and the names of variables for both the strongest and weakest correlation in the matrix.
Fair 11 (11%) – 11 (11%)
The response inaccurately or vaguely describes the strongest and weakest correlation in the matrix.

OR

The response omits either the strongest or weakest correlation.

The response includes inaccurate or vague correlation value and the names of variables for both the strongest and weakest correlation in the matrix.

OR

The response omits the correlation value and/or the names of variables for either the strongest or weakest correlation.
Poor 0 (0%) – 10 (10%)
The response inaccurately and vaguely describes the strongest and weakest correlation in the matrix, or it is missing.

The response includes an inaccurate and vague correlation value and the names of variables for both the strongest and weakest correlation in the matrix, or it is missing.
Explain how many original correlations are present in the matrix.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly explains, in detail, how many original correlations are present in the matrix.
Good 8 (8%) – 8 (8%)
The response accurately explains how many original correlations are present in the matrix.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely explains how many original correlations are present in the matrix.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely explains how many original correlations are present in the matrix, or it is missing.
Explain what the entry of 1.00 indicates on the diagonal of the matrix.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly explains in detail what the entry of 1.00 indicates on the diagonal of the matrix.
Good 8 (8%) – 8 (8%)
The response accurately explains what the entry of 1.00 indicates on the diagonal of the matrix.
Fair 7 (7%) – 7 (7%)

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The response inaccurately or vaguely explains what the entry of 1.00 indicates on the diagonal of the matrix.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely explains what the entry of 1.00 indicates on the diagonal of the matrix, or it is missing.
Indicate the strength and direction of the relationship between body mass index and physical component subscale.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly indicates, in detail, the strength and direction of the relationship between body mass index and physical component subscale.
Good 8 (8%) – 8 (8%)
The response accurately indicates the strength and direction of the relationship between body mass index and physical component subscale.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely indicates the strength and direction of the relationship between body mass index and physical component subscale.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely indicates the strength and direction of the relationship between body mass index and physical component subscale, or it is missing.
Explain which variable is most strongly correlated with BMI. Explain the correlational coefficient and the sample size for this relationship.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly explains in detail which variable is most strongly corrected with BMI.

The response accurately and clearly explains in detail the correlational coefficient and the sample size for this relationship.
Good 8 (8%) – 8 (8%)
The response accurately explains which variable is most strongly corrected with BMI.

The response accurately explains the correlational coefficient and the sample size for this relationship.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely explains which variable is most strongly corrected with BMI.

The response inaccurately or vaguely explains the correlational coefficient and the sample size for this relationship.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely explains which variable is most strongly corrected with BMI, or it is missing.

The response inaccurately and vaguely explains the correlational coefficient and the sample size for this relationship, or it is missing.
Explain the mean and standard deviation for BMI and doctor visits.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly explains in detail the mean and standard deviation for BMI and doctor visits.
Good 8 (8%) – 8 (8%)
The response accurately explains the mean and standard deviation for BMI and doctor visits.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely explains the mean and standard deviation for BMI and doctor visits.

OR

The response omits the mean or standard deviation for BMI and doctor visits.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely explains the mean and standard deviation for BMI and doctor visits, or it is missing.
Explain the mean and standard deviation for weight and BMI. Describe the strength and direction of the relationship between weight and BMI.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly explains, in detail, the mean and standard deviation for weight and BMI.

The response accurately and clearly explains, in detail, the strength and direction of the relationship between weight and BMI.
Good 8 (8%) – 8 (8%)
The response accurately explains the mean and standard deviation for weight and BMI.

The response accurately explains the strength and direction of the relationship between weight and BMI.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely explains the mean and standard deviation for weight and BMI.

OR

The response omits weight or BMI.

OR

The response omits the mean or standard deviation.

The response inaccurately or vaguely explains the strength and direction of the relationship between weight and BMI.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely explains the mean and standard deviation for weight and BMI, or it is missing.

The response inaccurately and vaguely explains the strength and direction of the relationship between weight and BMI, or it is missing.
Describe the scatterplot. Explain what information it provides to the researcher.–
Excellent 9 (9%) – 10 (10%)
The response accurately and clearly describes the scatterplot in detail.

The response accurately and clearly explains, in detail, what information the scatterplot provides to the researcher.
Good 8 (8%) – 8 (8%)
The response accurately describes the scatterplot.

The response accurately explains what information the scatterplot provides to the researcher.
Fair 7 (7%) – 7 (7%)
The response inaccurately or vaguely describes the scatterplot.

The response inaccurately or vaguely explains what information the scatterplot provides to the researcher.
Poor 0 (0%) – 6 (6%)
The response inaccurately and vaguely describes the scatterplot, or it is missing.

The response inaccurately and vaguely explains what information the scatterplot provides to the researcher, or it is missing.
Written Expression and Formatting – Paragraph Development and Organization: Paragraphs make clear points that support well-developed ideas, flow logically, and demonstrate continuity of ideas. Sentences are carefully focused—neither long and rambling nor short and lacking substance. A clear and comprehensive purpose statement and introduction is provided which delineates all required criteria.–
Excellent 5 (5%) – 5 (5%)
Paragraphs and sentences follow writing standards for flow, continuity, and clarity.

A clear and comprehensive purpose statement, introduction, and conclusion is provided which delineates all required criteria.
Good 4 (4%) – 4 (4%)
Paragraphs and sentences follow writing standards for flow, continuity, and clarity 80% of the time.

Purpose, introduction, and conclusion of the assignment is stated, yet is brief and not descriptive.
Fair 3.5 (3.5%) – 3.5 (3.5%)
Paragraphs and sentences follow writing standards for flow, continuity, and clarity 60%–79% of the time.

Purpose, introduction, and conclusion of the assignment is vague or off topic.
Poor 0 (0%) – 3 (3%)
Paragraphs and sentences follow writing standards for flow, continuity, and clarity < 60% of the time.

No purpose statement, introduction, or conclusion was provided.
Written Expression and Formatting – English writing standards: Correct grammar, mechanics, and proper punctuation–
Excellent 5 (5%) – 5 (5%)
Uses correct grammar, spelling, and punctuation with no errors.
Good 4 (4%) – 4 (4%)
Contains a few (1 or 2) grammar, spelling, and punctuation errors.
Fair 3.5 (3.5%) – 3.5 (3.5%)
Contains several (3 or 4) grammar, spelling, and punctuation errors.
Poor 0 (0%) – 3 (3%)
Contains many (≥ 5) grammar, spelling, and punctuation errors that interfere with the reader’s understanding.
Written Expression and Formatting – The paper follows correct APA format for title page, headings, font, spacing, margins, indentations, page numbers, parenthetical/in-text citations, and reference list.–
Excellent 5 (5%) – 5 (5%)
Uses correct APA format with no errors.
Good 4 (4%) – 4 (4%)
Contains a few (1 or 2) APA format errors.
Fair 3.5 (3.5%) – 3.5 (3.5%)
Contains several (3 or 4) APA format errors.
Poor 0 (0%) – 3 (3%)
Contains many (≥ 5) APA format errors.
Total Points: 100
Name: NURS_8201_Week6_Assignment_Rubric