Using the Excel Sheet and Descriptive Statistics
Descriptive statistics are methods of describing characteristics of a data set by generating summaries about the data sample. Descriptive statistics are often depicted as a summary of data demonstrated that explains the contents of data. According to Kaliyadan and Kulkarni (2019), descriptive statistics consist of three basic categories of measures, namely measures of central tendency, measures of variability, and frequency distribution.
Measures of central tendency describe the center of the data set and include mean, mode, and median (Kaliyadan & Kulkarni, 2019). The mean is the average, while the mode of a data set is the value that appears most often. On the other hand, the median is the figure situated in the middle of the data set. The measures of variability explore the dispersion of a data set and include variance and standard deviation. Finally, measures of frequency describe the occurrence of data within a data set.
Data analysis is a critical component of research as it repurposes large quantities of data into meaningful information. Several data analysis software exist, including IBM SPSS and Microsoft Excel. Understanding how to use this software is crucial as it correlates to the accuracy of the analysis. Microsoft Excel descriptive statistics can be used to summarize the characteristics of a data set.
The table below represents the results of data analysis of math anxiety for 20 students with study variables (cringe, uneasy, afraid, worried, and understanding). The math anxiety score ranged from 1 to 5, reflecting the lowest to highest scores. Data analysis with Excel revealed a median and average age of 33.5 and 36. 2 years for the participants, respectively.
The descriptive statistics revealed a mean anxiety score of 3.25, 3.70, 3.55, 2.60, and 3.05 for cringe, uneasy, afraid, worried, and understand, respectively. Additionally, the average amount of variability within the data set was 1.37, 1.30, 1.15, 1.19, and 1.36 for cringe, uneasy, afraid, worried, and understand, respectively.
Microsoft Excel provides an excellent user-centered and interactive interface for carrying out descriptive statistics (Divisi et al., 2018). It also provides quick and easier data storage and retrieval. Similarly, data entry is much easier. Consequently, Excel descriptive statistics is an effective, efficient, quick, and easier way of summarizing characteristics of a data set into useful information.
Navigating through this program reveals several statistical functions which can’t be learned in a single setting. In addition, understanding these statistical functions is central to future nursing practice, which consists of research and evidence-based practice (Taylor et al., 2020). As a researcher, understanding data analysis with Excel gives an added advantage as it may shorten the duration of research by decreasing the usually lengthy and time-consuming data analysis section (Taylor et al., 2020).
Also, comprehensively understanding data analysis with Excel enormously stretches the accuracy of data analysis and hence the reliability and validity of the findings. Similarly, understanding these statistical functions empowers one with skills and expertise that can be income-generating. Consequently, to enhance my knowledge and skills in Excel, I intend to learn more about excel by watching videos and reading manuals and handbooks while simultaneously putting into practice and rehearsing on Excel. Finally, I will enroll in a part-time course for this computer package.
Graphical presentation of data is necessary as it provides a pictorial summary of the data sets. Additionally, it makes the results section visually appealing to stakeholders and saves time. Below are graphs for the math anxiety analysis.
Histogram for Cringe
Bar graph for standard deviation and Variance
Divisi, D., Di Leonardo, G., Zaccagna, G., & Crisci, R. (2018). Basic statistics with Microsoft Excel: a review. Journal of Thoracic Disease, 9(6), 1734–1740. https://doi.org/10.21037/jtd.2017.05.81
Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian Dermatology Online Journal, 10(1), 82–86. https://doi.org/10.4103/idoj.IDOJ_468_18
Taylor, D. M., Hodkinson, P. W., Khan, A. S., & Simon, E. L. (2020). Research skills and the data spreadsheet: A research primer for low- and middle-income countries. African Journal of Emergency Medicine: Revue Africaine de La Medecine d’urgence, 10(Suppl 2), S140–S144. https://doi.org/10.1016/j.afjem.2020.05.003
Summary and Descriptive Statistics
There is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education. Using the data on the \"National Cancer Institute Data\" Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the topic Resources, as needed, for assistance in with creating Excel formulas. Provide the following descriptive statistics: Measures of Central Tendency: Mean, Median, and Mode Measures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range). Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups. APA style is not required, but solid academic writingâ€¯is expected. THE LINK FOR THE NATIONAL CANCER INSTITUTE DATA https://halo.gcu.edu/resource/eec7513e-9ae4-41db-b42d-9b14213c8741?nestedResourceId=59e8551a-40a3-4438-8026-66b15d950b5c rubrics Rubric Criteria Measures of Central Tendency 25 points Measures of Variation 25 points Analysis of Descriptive Statistics 25 points Excel Formulas 20 points Mechanics of Writing 5 points