**NURS 8200 Assignment 2: Descriptive Statistics**

**NURS 8200 Assignment 2: Descriptive Statistics**

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