**Descriptive Summary Paper**

**Age of respondent**

Statistical Package for the Social Sciences (SPSS) was used to provide summary statistics for the variable age of respondents at the time of the interview. The average age of respondents in the dataset consisting of N=1000 participants was 36.6 years (SD +/- 6.2). The standard deviation is slightly small, indicating that most respondents’ ages were either 6.2 years below or above the mean. Respondents’ age at the time of the interview ranged between 19.4 and 49.4 years old, i.e., the youngest individual in the sample was 19.4 years old, whereas the oldest was 49.4 years. Skewness statistic = -3.74, implying the sample data was moderately skewed to the left.

**Highest School grade completed. **

In a sample of N=989, the mean of the highest school grade completed by respondents was found to be 11.28 (SD=+/- 1.6). A standard deviation of 1.6 shows the majority of respondents’ highest grade completed was between 1.6 grades lower or higher than the average of 11.28. The results ranged from 1 to 16, meaning the lowest and highest grade completed by the participants were 1 and 16, respectively, in the sample. Skewness statistic was -0.727, which means the data is slightly skewed to the left and not normally distributed.

**Race & Ethnicity **

This section presents the race and ethnicity summary of the sample population. In terms of respondents’ ethnicity, in a sample of N=1000 participants, the black (not Hispanic) ethnic group was the largest in the sample, with a total number of 803 participants constituting 80.5% of the sample population. Respondents of Hispanic ethnicity were the second largest in the sample, with the total number being 128, which constituted 12.8 percent of all the respondents included in the sample. Individuals of White ethnicity were 53 in number, constituting 5.3 percent of the total sample, while other ethnicity constituted 1.4 percent of the total sample population.

**Employment Status**

A descriptive summary of the sample data by employment status revealed that most of the respondents were not employed, with a total of 546 out of 1000 participants indicating they were not employed at the time of interview; this constituted 54.7 percent. On the other hand, 452 participants (45.3 percent) indicated that they were employed. Two individuals in the sample did not indicate their employment status.

**Part II**

A histogram is used to assess if the distribution of a continuous variable follows a normal distribution, in which case we expect symmetry in the histogram with mean, median, and mode approximately equal. In the figure below, respondents’ age at the time of the interview seems to be slightly skewed to the left.

The histogram for the highest education reached almost formed a bell shape, meaning normally distributed. However, a keen look at the graph shows the peakness (Kurtosis) of the curve seems very high.

**Part III**

**Family Income**

With regard to family income in the prior month to the interview, in a dataset comprising of 895 participants, the average family income was $1,172.59 (SD +/- 26.34). This means that among the respondents, most families reported income 26.34 higher or lower than the average income. Monthly income ranged from $0 to $6,923, meaning the lowest income observed in the sample was $0, and the highest was $6,923. In the population from which the sample is drawn, the monthly income in most families was $788.153, above or below the average income of 1,172.59 dollars. The skewness statistic was 2.030 (sd +/- 0.082), implying the income data is skewed to the right. This is also clearly observable from the histogram as the tail is longer towards the right.

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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 â€œreveal characteristics of the sample and to describe study variablesâ€ (Gray & Grove, 2020). This allows the researcher to present data in a more meaningful and simplified way.

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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 Groveâ€™s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

To Prepare:

â€¢ Review the Week 4 Descriptive Statistics SPSS Output provided in this weekâ€™s Learning Resources.

â€¢ Review the Learning Resources on how to interpret descriptive statistics, including how to interpret research outcomes.

â€¢ 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: (2â€“3 pages)

â€¢ Summarize your interpretation of the frequency data provided in the output for respondentâ€™s age, highest school grade completed, and family income from prior month.

â€¢ 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.

â€¢ Summarize your interpretation of the descriptive statistics provided in the output for respondentâ€™s age, highest school grade completed, race and ethnicity, currently employed, and family income from prior month.

â€¢ 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