NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics

NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics

Walden University NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics-Step-By-Step Guide

 

This guide will demonstrate how to complete the Walden University  NURS 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and Descriptive Statistics

 

Whether one passes or fails an academic assignment such as the Walden University   NURS 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and Descriptive Statistics

 

The introduction for the Walden University   NURS 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and Descriptive Statistics 

 

After the introduction, move into the main part of the  NURS 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and 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 8201 Week 4 Assignment: Frequency and Descriptive Statistics

There are many purposes for frequency and descriptive statistics in data analysis. Some of the most common uses include exploring data, understanding relationships between variables, and making predictions. Frequency statistics can be used to understand how often certain values occur in a data set. This can be helpful in identifying patterns or outliers. Descriptive statistics can be used to summarize a data set and calculate measures of central tendency (such as the mean or median) and dispersion (such as the standard deviation). These summary measures can give you a good overview of your data, which can be helpful in further analyses (Grove et al., 2020). Both frequency and descriptive statistics are important tools for data analysis. The choice of which statistic to use depends on the specific question and the type of data. The purpose of this assignment is to provide the interpretation of the descriptive statistics of the data from the SPSS output given.

Determining variables in the research process is necessary in ensuring accuracy in the interpretation of the descriptive statistics. Some of the variables in this case include respondent’s age, highest school grade completed, race and ethnicity, currently employed, and family income from prior month. Answer: When it comes to descriptive statistics, one of the most important things is to make sure that all the variables are appropriately defined (Grove et al., 2020). This includes making sure that all the data is measured in the same way, and that there is a clear definition for each variable. If certain variables are not properly defined, it can lead to inaccurate results and potentially flawed conclusions. So it is crucial to take the time to define all the variables before beginning any kind of statistical analysis.

Part I

Table 1: Respondent’s Age

Table 1 indicates the descriptive statistics for the respondent’s age. A total of 1000 respondents too part in the study. The minimum age of the respondents was 19.378 years while the maximum age was 49.43 years. The average age of the respondents was 36.64 years. The standard deviation from the mean was 6.1987.

Table 2: Highest School Grade Completed

Out of the 1000 respondents interviewed, 11 individuals did not provide the data on the highest school grade completed. However, for the respondents who provided this data, the minimum school grade completed is 1 while the maximum grade is 16. The mean school grade completed was 11.2 with a standard deviation of 1.561.

Sample Answer for NURS 8201 Week 4 Assignment: Frequency and 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

Sample Answer 2 for NURS 8201 Week 4 Assignment: Frequency and 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

NURS 8201 Week 4 Assignment: Frequency and Descriptive Statistics

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.

Photo Credit: Getty Images

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.}

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). All papers submitted must use this formatting.

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• Click the Week 4 Assignment Rubric to review the Grading Criteria for the Assignment.
• Click the Week 4 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.
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• Click on the Submit button to complete your submission.

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Also Check Out:  NUR 8100 Discussion: Selecting a Policy Analysis Framework

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What’s Coming Up in Module 3?

Photo Credit: [BrianAJackson]/[iStock / Getty Images Plus]/Getty Images

In the next module, you will continue your exploration of quantitative research and data analysis. You will look more closely at additional techniques and methods of conducting quantitative data analysis and interpretation.

Looking Ahead: Assignment: CITI Program Training

As a doctorally prepared nurse, you may be able to participate in research activities in your practice. The Collaborative Institutional Training Initiative (CITI Program) educates people about human subject protection. The CITI Program is the training module used by the majority of research institutions in the United States. As a result, as part of this course, you must successfully complete the CITI Program training by Day 7 of Week 9.

Name: NURS_8201_Week4_Assignment_Rubric

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		Excellent	Good	Fair	Poor
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.		32 (32%) – 35 (35%) The response accurately and clearly explains, in detail, a summary of the frequency distributions for the variables presented. The response accurately and clearly explains, in detail, the number of times the value occurs in the data. The response accurately and clearly explains, in detail, the appearance of the data, the range of data values, and an explanation of extreme values in describing intervals that sufficiently provides an analysis that fully supports the categorization of each variable value. The response includes relevant, specific, and appropriate examples that fully support the explanations provided for each of the areas described.	28 (28%) – 31 (31%) The response accurately summarizes the frequency distributions for the variables presented. The response accurately explains the number of times the value occurs in the data. The response accurately explains the appearance of the data, the range of data values, and explains extreme values in describing intervals that provides an analysis which supports the categorization of each variable value. The response includes relevant, specific, and accurate examples that support the explanations provided for each of the areas described.	25 (25%) – 27 (27%) The response inaccurately or vaguely summarizes the frequency distributions for the variables presented. The response inaccurately or vaguely explains the number of times the value occurs in the data. The response inaccurately or vaguely explains the appearance of the data, the range of data values, and inaccurately or vaguely explains extreme values. An analysis that may support the categorization of each variable value is inaccurate or vague. The response includes inaccurate and irrelevant examples that may support the explanations provided for each of the areas described.	0 (0%) – 24 (24%) The response inaccurately and vaguely summarizes the frequency distributions for the variables presented, or it is missing. The response inaccurately and vaguely explains the number of times the value occurs in the data, or it is missing. The response inaccurately and vaguely explains the appearance of the data, the range of data values, and an explanation of extreme values, or it is missing. An analysis that does not support the categorization of each variable values is provided, or it is missing. The response includes inaccurate and vague examples that do not support the explanations provided for each of the areas described, or it is missing.
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.		45 (45%) – 50 (50%) The response accurately and clearly summarizes in detail the interpretation of the descriptive statistics provided. The response accurately and clearly evaluates in detail each of the variables presented, including an accurate and complete description of the sample size, the mean, the median, standard deviation, and the size and spread of the data.	40 (40%) – 44 (44%) The response accurately summarizes the interpretation of the descriptive statistics provided. The response accurately explains evaluates each of the variables presented, including an accurate description of the sample size, the mean, the median, standard deviation, and the size and spread of the data.	35 (35%) – 39 (39%) The response inaccurately or vaguely summarizes the interpretation of the descriptive statistics provided. The response inaccurately or vaguely evaluates each of the variables presented, including an inaccurate or vague description of the sample size, the mean, the median, the standard deviation, and the size and spread of the data.	0 (0%) – 34 (34%) The response inaccurately and vaguely summarizes the interpretation of the descriptive statistics provided, or it is missing. The response inaccurately and vaguely evaluates each of the variables presented, including an inaccurate and vague description of the sample size, the mean, the median, the standard deviation, and the size and spread of the data, 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.		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.	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.	3 (3%) – 3 (3%) 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.	0 (0%) – 2 (2%) 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		5 (5%) – 5 (5%) Uses correct grammar, spelling, and punctuation with no errors.	4 (4%) – 4 (4%) Contains a few (1 or 2) grammar, spelling, and punctuation errors.	3 (3%) – 3 (3%) Contains several (3 or 4) grammar, spelling, and punctuation errors.	0 (0%) – 2 (2%) 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.		5 (5%) – 5 (5%) Uses correct APA format with no errors.	4 (4%) – 4 (4%) Contains a few (1 or 2) APA format errors.	3 (3%) – 3 (3%) Contains several (3 or 4) APA format errors.	0 (0%) – 2 (2%) Contains many (≥ 5) APA format errors.
Total Points: 100

Name: NURS_8201_Week4_Assignment_Rubric