Use of Excel Descriptive Statistics for Data Analysis Research - Essay Exampe

Descriptive statistics can be used for data analysis in research to induce various inferences about a set of data. In research or business operations, the collection of data is indispensable since it helps analysts decipher critical information such as forecasts or trends. However, data is not useful if it is not converted into a form that can influence decision-making or support propositions (Fisher & Marshall, 2009). Therefore, descriptive analysis helps convert numbers into meaningful information that one can use to understand and make inferences about a phenomenon (Fisher & Marshall, 2009). Notably, excel descriptive analysis is a vital tool that reveals the mean, sum, range, count, mode, median, standard deviation, mode, kurtosis, and skewness. During research, a person may have a set of data that may be cumbersome to use to produce meaningful results (Fisher & Marshall, 2009). In such cases, descriptive statistics are utilized to describe the larger population. Noticeably, measures of central tendency—mean, median, & mode—are used to represent a set of data using a single value. For example, in the data set provided, I used descriptive analysis to determine the average mean age of the participants, which was 36.2. In this case, a researcher can conclude that most people who undertook the study were about 36. 2 years.

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Additionally, descriptive statistics can be used to determine the sum of a set of data easily. In most cases, adding up the sum of a range of values can be hectic and time-consuming especially if one is researching within a limited period. Fortunately, MS Excel descriptive analysis easily provides the sum of selected data minimizing the time that could have been used to calculate manually (McHugh & HudsonBarr, 2003). The count is also a significant component of descriptive analysis which gives the number of items in a row or a column (Fisher & Marshall, 2009). The count function can be utilized in data analysis to provide an accurate number of values that are present in a set of data. For example, while carrying out a research study on the number of diabetics in the community, the count function can be used to readily show the number of participants who participated in the study.

Moreover, the standard deviation can be used to show the dispersion of a set of data from its mean. In research, standard deviation and sample variance are important functions to show how the data is distributed within a set (McHugh & HudsonBarr, 2003). If the standard deviation is higher, an analyst can identify that there is a higher deviation in the data set. For instance, while analyzing the math anxiety of the study participants, the high standard deviation in the "cringe" column shows that participants' scores in the element are dispersed more compared to those in the "uneasy" column.

Noticeably, my experience running descriptive statistics was amazing, since I deduced more information from the data set the analysis. For instance, by looking at the raw data in columns, one cannot identify what is the dominant type of math anxiety across all age groups. Nevertheless, after carrying out a descriptive statistic, the mean can reveal that being uneasy is the most common type of anxiety followed by fear, cringe, understanding, and worrying respectively. Such an analysis would aid a researcher or a teacher in prioritizing the challenges while trying to develop a solution.

Plan for Learning Excel and its Benefits in Future Research Analysis

I plan to learn more about Excel because it is an indispensable tool during analysis. Throughout my studies, I will engage in a rigorous pursuit of knowledge regarding the software to enhance my skills. Noticeably, the software has a plethora of functions that one can leverage during research and data analysis. I will use tutorial videos explaining how one can use specific functions and formulas to analyze data readily. Additionally, I will practice extensively using past research data to try and deduce more inferences from a set of raw data.

The information gained from this exercise is critical in enhancing my research skills. Notably, most researchers are faced with time constraints as they try to complete their studies according to their schedule. Manually analyzing a huge dataset while under time pressure may lead to poor result presentation and conclusion. Fortunately, with the Excel software, an individual easily analyze raw data through various functions present in the system, enhancing the credibility, integrity, and accuracy of a study result (Carr, 2008).

Additionally, Excel software is vital in presenting data in a format that is easily comprehendible to everyone. For example, a large piece of raw data in tables may be cumbersome while trying to give quick inferences about a phenomenon. However, using visual statistical data representation methods such as graphs, histograms, or pie charts, one can easily see the various trends in a dataset (Carr, 2008). A visual presentation helps display information in a meaningful form that allows a researcher to conclusions through observation.

Moreover, the software is useful in collecting and storage of data in an organized and easily retrievable form. Therefore, the software will help me in future studies while collecting data concerning study participants and results from various tests. Notably, with Excel, one does not need to export the data from an external source to carry out an analysis, which saves time and money.

References

Carr, N. T. (2008). Using Microsoft Excel® to calculate descriptive statistics and create graphs. Language Assessment Quarterly, 5(1), 43-62. https://doi.org/10.1080/15434300701776336

Fisher, M. J., & Marshall, A. P. (2009). Understanding descriptive statistics. Australian Critical Care, 22(2), 93-97. https://doi.org/10.1016/j.aucc.2008.11.003

McHugh, M. L., & HudsonBarr, D. (2003). Descriptive statistics, part II: Most commonly used descriptive statistics. Journal for Specialists in Pediatric Nursing, 8(3), 111-116. https://doi.org/10.1111/j.1088-145X.2003.00111.x