NURS 8200 Assignment 2: Descriptive Statistics
Walden University NURS 8200 Assignment 2: Descriptive Statistics-Step-By-Step Guide
This guide will demonstrate how to complete the Walden University NURS 8200 Assignment 2: Descriptive Statistics assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.
How to Research and Prepare for NURS 8200 Assignment 2: Descriptive Statistics
Whether one passes or fails an academic assignment such as the Walden University NURS 8200 Assignment 2: Descriptive Statistics depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.
After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.
How to Write the Introduction for NURS 8200 Assignment 2: Descriptive Statistics
The introduction for the Walden University NURS 8200 Assignment 2: Descriptive Statistics is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.
How to Write the Body for NURS 8200 Assignment 2: Descriptive Statistics
After the introduction, move into the main part of the NURS 8200 Assignment 2: Descriptive Statistics assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.
Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.
How to Write the Conclusion for NURS 8200 Assignment 2: Descriptive Statistics
After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.
How to Format the References List for NURS 8200 Assignment 2: Descriptive Statistics
The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.
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Sample Answer for NURS 8200 Assignment 2: Descriptive Statistics
Part I
Descriptive statistics is commonly applied in the process of data analysis to show the attributes of different variables applied in the study (Vetter, 2017). Descriptive statistics can also a summary statistic that summarizes and describes features from a collection of information or dataset (Kaur et al., 2018). Descriptive statistics can be distinguished from the inferential statistics by its aim to summarize the sample data (Kaliyadan & Kulkarni, 2019). Descriptive statistics, unlike the inferential statistics, is not based on the non-parametric tests as well as the probability theory (Mishra et al., 2019). Some examples of descriptive statistics include measures of central tendency including mean, median, mode, and standard deviation, also, frequencies can be considered as one of the descriptive statistics (Finkelstein, 2019).
Table 1. Demographic Data (N = 30)
n % M (SD)
Age (in years) 929 19.6803(3.78497)
Highest School Grade Completed 989 11.28(1.561)
Race and Ethnicity
Black, Not Hispanic 803 (80.3)
Hispanic 128 (12.8)
White, Not Hispanic 53 (5.3)
Other 14 (1.4)
Currently Employed
Yes 452 (45.3)
No 546 (54.7)
Note. Differences in sample size are due to missing data.
Table 1 shows the demographic data for the variables, age and the highest school grade completed. From the information provided in the table, the mean age of the participants was 19.6803 years while the mean for the highest grade obtained was 11.28. The frequency distribution indicates that there were more Black, not Hispanic participants in the study. The total number of black participants were 803 constitutiing 80.3%. On the other hand, the total number of Hispanic participants were 128, contituting 12.8%. The least number of participants were Whites, Not Hispanics with 53 participants constituting 5.3%. Other participants were 14 constituting 1.4%.
Part II
Assignment: Using the data obtained when you ran the descriptives and the histograms, determine whether the data skewed. If so, is it a positive, negative or neutral skew?
- ______________Negative________ skew
- ______________Neutral________ skew
Part III
- What is the mean income in this sample?
The mean income in the sample is $1,172.59
- What is the standard deviation (SD)?
The standard deviation of the sample is $788.153
- What is the standard error of the mean?
The standard error of the mean is 0.082
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- Compute a 95% confidence interval around the mean. (Use 1.96 for the 95% CI and get the standard error from the descriptive statistics table). You should get a range (2 numbers) for the salary. The formula is as follows:
95% CI = [mean ± (1.96 ´ SE)] (Du Prel et al., 2019)
= 1,172.59 ± 1.96 ´ 0.082
= 1,172.59 ± 0.16072
= (1,172.42928, 1,172.75072)
- Compute a 99% confidence interval around the mean. (Use 2.58 for the 99% CI and get the standard error from the descriptive statistics table). You should get a range (2 numbers) for the salary. The formula is as follows:
99% CI = [mean ± (2.58 ´ SE)]
= 1,172.59 ± 2.58 ´ 0.082
= 1,172.59 ± 0.21156
= (1,172.37844, 1,172.80156)
- Which interval is wider? Explain.
99% interval is wider than 95% confidence interval because, for the researcher to be more confident, there is the need to allow for more potential values within the interval (Hazra, 2017).
References
Finkelstein, M. O. (2019). Confidence. In Basic Concepts of Probability and Statistics in the Law (pp. 81-87). Springer, New York, NY. https://link.springer.com/chapter/10.1007/b105519_6
Hazra, A. (2017). Using the confidence interval confidently. Journal of thoracic disease, 9(10), 4125. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723800/
Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian dermatology online journal, 10(1), 82. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362742/
Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60. https://www.ijam-web.org/article.asp?issn=2455-5568;year=2018;volume=4;issue=1;spage=60;epage=63;aulast=Kaur
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. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350423/
Vetter, T. R. (2017). Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who, What, Why, When, Where, and a Sixth, So What?. Anesthesia & Analgesia, 125(5), 1797-1802. https://www.ingentaconnect.com/content/wk/ane/2017/00000125/00000005/art00048
Sample Answer 2 for NURS 8200 Assignment 2: Descriptive Statistics
Measures of Central Tendency
| Table 1: American Indian / Alaska Native (includes Hispanic) | |
| Mean | 43.275 |
| Standard Error | 1.31622883 |
| Median | 43.85 |
| Mode | #N/A |
| Standard Deviation | 5.264915321 |
| Sample Variance | 27.71933333 |
| Kurtosis | -0.136660029 |
| Skewness | -0.383344382 |
| Range | 19.7 |
| Minimum | 32 |
| Maximum | 51.7 |
| Sum | 692.4 |
| Count | 16 |
| Confidence Level(95.0%) | 2.805475342 |
In data analysis, measures of central tendency are essential when it comes to the understanding of different attributes of the dataset (Weaver 17). In most cases, it reveals the characteristics of the study participants or respondents, their mean, mode, the median, maximum and minimum numbers. The following tables indicate the descriptive statistics for the National Cancer Institute 2018.
| Table 2: Asian / Pacific Islander (includes Hispanic) | |
| Mean | 38.5125 |
| Standard Error | 0.595810023 |
| Median | 38.9 |
| Mode | 36.6 |
| Standard Deviation | 2.383240091 |
| Sample Variance | 5.679833333 |
| Kurtosis | -0.712232536 |
| Skewness | -0.555307749 |
| Range | 7.8 |
| Minimum | 34 |
| Maximum | 41.8 |
| Sum | 616.2 |
| Count | 16 |
| Table 3: Black (includes Hispanic) | |
| Mean | 70.06875 |
| Standard Error | 1.685025191 |
| Median | 71.4 |
| Mode | #N/A |
| Standard Deviation | 6.740100766 |
| Sample Variance | 45.42895833 |
| Kurtosis | -0.949652546 |
| Skewness | -0.507960145 |
| Range | 21.6 |
| Minimum | 57.4 |
| Maximum | 79 |
| Sum | 1121.1 |
| Count | 16 |
| Table 4: Hispanic (any race) | |
| Mean | 31.49375 |
| Standard Error | 0.724538287 |
| Median | 32.1 |
| Mode | 34.1 |
| Standard Deviation | 2.898153148 |
| Sample Variance | 8.399291667 |
| Kurtosis | -0.88797923 |
| Skewness | -0.611418136 |
| Range | 9 |
| Minimum | 26 |
| Maximum | 35 |
| Sum | 503.9 |
| Count | 16 |
| Table 5: White (includes Hispanic) | |
| Mean | 62.725 |
| Standard Error | 1.278720063 |
| Median | 64.55 |
| Mode | 65.8 |
| Standard Deviation | 5.114880253 |
| Sample Variance | 26.162 |
| Kurtosis | -1.087933179 |
| Skewness | -0.55685628 |
| Range | 15.6 |
| Minimum | 53.2 |
| Maximum | 68.8 |
| Sum | 1003.6 |
| Count | 16 |
Table 1, 2, 3, 4, and 5 indicate the rate of cancer in the American Indian, Asian, Black, Hispanic and whites races per 100,000 people respectively. The black community has the highest rate of cancer infection, followed by whites, including Hispanics (Merola et al. 32). The Hispanic race has the lowest rate of cancer prevalence per 100, 000 people. The data was recorded for 16 successive years from the year 2000 to 2015. Among the American Indian participants, the highest rate per 100, 000 people was 51.7 while the lowest rate was 32; this was recorded in the year 2004 (Bilimoria et al. 13). On the other hand, for the Asian participants, the maximum rate was 41.8 while the minimum rate was 34 as recorded in the year 2000 and 2014, respectively. For the blacks, Hispanics and whites, the maximum rates of infections were 79, 35, and 68.8 respectively. The means rate for the American Indians, Asians, Blacks, Hispanics, and Whites who participated in the research was 43.275, 38.5125, 70.06875, 31.49375, and 62.725 respectively.
Table 6: Measures of Variation
| Ethnicity/Race | American Indian / Alaska Native (includes Hispanic) | Asian / Pacific Islander (includes Hispanic) | Black (includes Hispanic) | Hispanic (any race) | White (includes Hispanic) |
| Variance | 27.71933 | 5.6798 | 45.429 | 8.399 | 26.162 |
| Standard Deviation | 5.265 | 2.383 | 6.740 | 2.8981 | 5.115 |
| Maximum | 51.7 | 41.8 | 79 | 35 | 68.8 |
| Minimum | 32 | 34 | 57.4 | 26 | 53.2 |
| Range | 19.7 | 7.8 | 21.6 | 9 | 15.6 |
Table 6 indicates measures of variation for the National Cancer Institute of 2018. From the table, a high rate of variation was recorded among the black race. In other words, the black participants had the highest rate of cancer infection per 100,000 people with high variation. Data for the Asian/Pacific Islander showed the least variation with 5.6798. The variations represented the deviation from the means for the rate of cancer infection per 100, 000 people. The range for the American Indians, Asian, Blacks, Hispanics, and whites were recorded as 19.7, 7.8, 21.6, 9, and 15.6 respectively.
Works Cited
Bilimoria, Karl Y., et al. “The National Cancer Data Base: a powerful initiative to improve cancer care in the United States.” Annals of surgical oncology 15.3 (2008): 683-690.
Merola, Roberta, et al. “PCA3 in prostate cancer and tumor aggressiveness detection on 407 high-risk patients: a National Cancer Institute experience.” Journal of Experimental & Clinical Cancer Research 34.1 (2015): 15.
Weaver, Kathleen F. An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences. , 2017. Print.
Sample Answer 3 for NURS 8200 Assignment 2: Descriptive Statistics
Statistical analysis is important in research as it helps in the analysis of the collected data to give important results and reveal important trends, which then helps answer research questions and draw conclusions. One of the aspects is frequency and descriptive statistics which are used in describing the main features of a dataset. Therefore, it is important for researchers to have adequate knowledge regarding data analysis using relevant statistical approaches and interpret the analyzed data to support decisions such as clinical decisions (Grey & Grove, 2020). Therefore, the purpose of this assignment is to review a provided descriptive statistics SPSS output. In addition, a summary of the interpretation of the frequency data provided for the respondent’s age, highest school grade completed, and family income will be given.
Participants’ Age
In terms of the participant’s age, the number of observations (N) is 1000. Therefore, this number of observations is adequate to represent the distribution of data since 20 observations are often considered sufficient. The maximum value is 49.43, and the minimum is 19.38. The observation is large enough to offer more precise estimates as part of the analysis and results (Mishra et al.,2019). The mean age of the respondents is 36.64, which shows that the average age of the respondents in the sample was approximately 37 years.
It is also important to explore the measures of variance. As such, the standard deviation of the respondents’ age is 6.20, which implies that the majority of the observations are spread within the standard deviations of either side of the mean (Kaliyadan & Kulkarni, 2019). The respondents’ age data is also left skewed as the value observed is -0.374. The implication is that it is slightly left-skewed. As observed from the histogram, the respondent’s age is left-skewed since most of the values fall on the left side of the histogram.
Highest High School Grade Completed
It is also important to explore the descriptive statistics for the highest grade completed. The observations observed (N) for this parameter is 989, which also implies that the values are sufficient for reporting. The mean value for the highest grade completed is 11.28, which is a measure of the average grade attended by the respondents. The measure of variance (standard deviation) observed for the highest grade completed is 1.56, which shows some variability. In addition, with normal data, the majority of the observations are spread within 0.75 standard deviations on either side of the mean. While a lower standard deviation shows a lower spread in the sampled data, a higher standard deviation shows a bigger spread in the sampled data (McGrath et al.,2020).
In terms of skewness, the data was again left skewed as the observed value was -0.73, which is lower than -1.0. This observation is supported by the shaper of the histogram on the high school grade completed, as the majority of the values fall on the left side of the histogram.
Family Income
Another analysis is on the family income. Therefore, it is also important to consider the descriptive statistics. The number of observations in the case of family income is 895. While the maximum value in terms of earnings per family is $6,593, the lowest or minimum earning is 0. The mean value for family income is $1,172.59. In terms of the measure of variance, the standard deviation value is $26.34, which is an indication of some variability in the family income. The skewness for family income is 2.03, which indicates that the family income values are positively skewed, pointing to a positively skewed distribution (Orcan et al.,2020). Indeed, this observation has been supported by the shape of the histogram on the family income, which shows the majority of the observations falling on the right side of the histogram, which is a further indication of right skewness.
Race and Ethnicity
Another important aspect of the data and analysis shown in the output is race and ethnicity. While those who identified themselves as blacks, not Hispanic, were 80.3%, Hispanics formed 12.8%. In addition, Whites, not Hispanics, were 5.3%, while those who identified themselves as other races were 1.4%. This analysis shows that most of those who gave their details were blacks; as such, conclusions made from this set of data would point more to what is happening with blacks than other races.
The other important aspect of data is the number or percentage of those who are currently employed. From the analysis, a total of 546 respondents who participated in the yes or no question to confirm their employment status confirmed that they were not employed, constituting 54.6%. The remaining 45.2%, or 452, are currently employed. Even though the number of those employed was lower than the unemployed, the difference was slight, which implies a smaller variation.
Conclusion
Descriptive statistics and frequency can play an important role in the analysis of a set of raw data to help gain a deeper insight into the data under consideration. As such, a summary of such analysis can reveal important sample features. Therefore, this analysis has focused on various data aspects such as the respondent’s age, the highest school grade completed, race and ethnicity, and employment status, that is, whether an individual is currently employed or not.
References
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
Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian Dermatology Online Journal, 10(1), 82. https://dx.doi.org/10.4103%2Fidoj.IDOJ_468_18
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. https://dx.doi.org/10.4103%2Faca.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