NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics

NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics

Data collection and subsequent statistical analysis form an integral part of research and help researchers understand research aspects such as observed trends and interpretation of such trends to make meaning and draw conclusions. An example of important statistical analysis applied in the description of the dataset features is the frequency and descriptive statistics. Appropriate use of such statistical methods and strategies requires individuals to possess sufficient knowledge of data analysis and the right statistical tools to use in the analysis. For example, healthcare professionals can use the same to support clinical decisions, which is key to patient treatment and outcomes (Gray & Grove, 2021). As such, the purpose of this assignment is to explore the provided SPSS output and summarize the interpretation of the frequency data.

The Respondents’ Age

This is one of the observations presented in the output. The total number of observations (N) made for this parameter is 1000, indicating adequacy in representing the data distribution, as 20 observations are usually the threshold of adequacy or sufficiency. Based on the respondents’ age, the maximum and the minimum values were observed to be 49.43 and 19.38, respectively. As part of the descriptive statistics, it is also important to include the mean (Mishra et al.,2019). Therefore, the mean age of the participants has been observed to be 36.64.  It is vital to explore the measure of variance in the output provided. The standard deviation of the participant’s age is 6.20, an observation which means that the majority of the observations are spread within the standard deviation of either side of the mean. It is also observable that the participants’ age is left screwed as indicated by the value, -0.374, an indication of slight left-skewness and that most of the values are on the left side of the histogram (Chattamvelli & Shanmugam, 2023)

Highest School Grade Completed

            The highest school grade completed is another parameter to explore. The total number of observations (N) for this parameter is 989. As in the previous case, the observations are sufficient as they are more than the threshold of twenty. The average grade attended by the participants is reflected in the mean. Therefore, the mean value for the highest grade completed is 11.28. It is also vital to explore the measure of variance such as standard deviation. As such the standard deviation for the highest grade completed is 1.56, showing a variability. Most of the observations made also spread within 0.75 standard deviations on either sides of the mean. Higher standard deviations usually indicate a bigger spread in the sampled data, while lower standard deviations reflect a lower spread in the sampled data (McGrath et al.,2020).

As observed, this data is also skewed to the left, with a value of -0.73 observed. This value is further supported by the shape of the obtained histogram, which shows that most of the values are on the left-hand side. The minimum and maximum values observed for the highest school grade completed are 1 and 16, respectively.

Family Income

            Family income is also among the data collected from the respondents, as such, this section explores its descriptive statistics. The total numbers of observations (N) recorded for family income is 895. As part of the description, it is important to explore minimum and maximum values. Therefore, the minimum and maximum family income recorded are 0 and $6,593, respectively. The mean value for the family income was observed to be $1,172.59. It is also vital to explore the measure of variance by looking at the standard deviation. From the output tables, the standard deviation is $26.34, which shows that there was variability in the family income category. The other measure is skewness. The skewness observed in the family income is  2.03, indicating that the family income data has a positive skewness and an indication of a positively skewed distribution (Orcan, 2020). The observation is also in line with the shape of the family income histogram, which shows that most of the observations can be found on the right side of the histogram.

Race and Ethnicity, and Currently Employed

            The next data parameters to be explored from the data output are race and ethnicity and current employment status. From the output tables. 80.3% of the respondents identified themselves as blacks, not Hispanic. 5.3 % identified themselves as whites, not Hispanics while 12.8% identified themselves as Hispanics. In addition, those who identified themselves as other races were 1.4%. Therefore, it can be conceived that the majority of the participants in this dataset were blacks, an indication that the data summary, observations, interpretations, and conclusions point more to what is happening in the black race.

It is also important to describe the employment status by exploring the percentage or number of those currently employed. From the provided data, the total number of observations made (N) was 546. Therefore, these are the numbers who revealed their employment status. 54.6 % of the participants indicated that they are currently not employed. On the other hand, the number of those in employment constituted 45.3%, which indicates a slight variation.

Conclusion

This assignment has focused on frequency and descriptive statistics with various data sets described. The respondents’ age and education level have been explored. Besides, the respondents’ income and ethnicity were also explored and described.

References

Chattamvelli, R., & Shanmugam, R. (2023). Skewness. In Descriptive Statistics for Scientists and Engineers: Applications in R (pp. 91-110). Cham: Springer Nature Switzerland. Doi: 10.1007/978-3-031-32330-0_4

Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

McGrath, S., Zhao, X., Steele, R., Thombs, B. D., Benedetti, A., & DEPRESsion Screening Data (DEPRESSD) Collaboration. (2020). Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Statistical Methods In Medical Research, 29(9), 2520–2537. https://doi.org/10.1177/0962280219889080

Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67-72. Doi: 10.4103/aca.ACA_157_18

Orcan, F. (2020). Parametric or non-parametric: Skewness to test normality for mean comparison. International Journal of Assessment Tools in Education, 7(2), 255–265. https://doi.org/10.21449/ijate.656077

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Imagine that you have collected data from 100 patients. You have carefully compiled vitals, pain scores, and medications for each of the patients. However, what does all of this data mean? Is your work now done?

How do we make data meaningful? Why must we move beyond the raw data to ensure that data is purposeful?
Descriptive analysis is the analysis of the data to develop meaning. Descriptive analysis provides meaning through showing, describing, and summarizing the data compiled to “reveal characteristics of the sample and to describe study variables” (Gray & Grove, 2020). This allows the researcher to present data in a more meaningful and simplified way.

For this Assignment, summarize your interpretation of the descriptive statistics provided to you in the Week 4 Descriptive Statistics SPSS Output document. You will evaluate each variable in your analysis.

Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

Resources

Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.

WEEKLY RESOURCES

Week 4: Learning Resources

Required Readings

• Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

• • Chapter 21, “Introduction to Statistical Analysis” (pp. 635–651)
  • Chapter 22, “Using Statistics to Describe Variables” (pp. 652–662)
  • Chapter 26, “Interpreting Research Outcomes” (pp. 699–716)
• Gholami, S., Mojen, L. K., Rassouli, M., Pahlavanzade, B., & Farahani, A. S. (2020). The predictors of postoperative pain among children based on the theory of unpleasant symptoms: A descriptive-correlational study

• Links to an external site.. Journal of Pediatric Nursing, 55, 141–146. doi:10.1016/j.pedn.2020.08.006
• Huang, J., Qi, H., Lv, K., Chen, X., Zhuang, Y., & Yang, L. (2020). Emergence delirium in elderly patients as a potential predictor of subsequent postoperative delirium: A descriptive correlational study
• Links to an external site.. Journal of PeriAnesthesia Nursing, 35(5), 478–483. doi:10.1016/j.jopan.2019.11.009
• Document: Week 4 Descriptive Statistics SPSS Output
• Download Week 4 Descriptive Statistics SPSS Output (PDF)
• Document: CITI Program Learner Registration Guide

• Download CITI Program Learner Registration Guide (PDF)

To Prepare:

• Review the Week 4 Descriptive Statistics SPSS Output provided in this week’s Learning Resources.
• Review the Learning Resources on how to interpret descriptive statistics, including how to interpret research outcomes.
• Consider the results presented in the SPSS output and reflect on how you might interpret the frequency distributions and the descriptive statistics presented.

The Assignment: (2–3 pages)

• Summarize your interpretation of the frequency data provided in the output for respondent’s age, highest school grade completed, and family income from prior month.

• Note: A frequency analysis is way of summarizing data by depicting the number of times a data value occurs in the data table or output. It is used to analyze the data set including where the data are concentrated or clustered, the range of values, observation of extreme values, and to determine intervals for analysis that could make sense in categorizing your variable values.

• Summarize your interpretation of the descriptive statistics provided in the output for respondent’s age, highest school grade completed, race and ethnicity, currently employed, and family income from prior month.

• Note: The descriptive analysis includes N (size of your sample), the mean, the median, the standard deviation, the size and spread of your data to determine the variability/variance in your data.

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

Links to an external site.). All papers submitted must use this formatting.

By Day 7

Submit your Assignment by Day 7 of Week 4.

submission information

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Rubric

NURS_8201_Week4_Assignment_Rubric