Posted: March 16th, 2022

A quantitative study is a study where the researcher collects and analyzes

Mayelin Ruiz
10 hours ago, at 10:15 PM
A quantitative study is a study where the researcher collects and analyzes quantifiable data. The study uses statistical techniques to analyze numerical data. Descriptive statistics are used in quantitative studies to present the data collected in a more meaningful way to facilitate easy interpretation (Mishra et al., 2019). The relevance of descriptive statistics is to simplify large data volume and make it more understandable to the viewer.
There are three measures used to assess central tendencies, which include mean, median, and mode (Mishra et al., 2019). The mean is the value that gives an average of the data set and is determined by summation of the values divided by number of values. The median is determined by selecting the value in the middle, when the data set is listed in a certain order, either descending or ascending (Mishra et al., 2019). The mode is determined by identifying the value that appears more frequently in a data set.
The levels of measurement identify the relationship among the values assigned to the attributes of the study variables. They include nominal, ordinal, ratio, and interval (Dalati, 2018). Nominal measurement is used to name the data that can be categorized, such as jersey numbers. Ordinal measurement is used to name the data that can be categorized and ranked, such as education level. Interval measurement is used on evenly spaced data that can be categorized and ranked, such as distance. Ratio measurement is used on data with a natural zero and can be ranked, categorized, and is evenly spaced. Parametric tests are tests that make assumptions on the parameters of normally distributed population data, while non-parametric tests do not make assumptions and are independent of the distribution of data.
A quantitative test would be used to measure the reduction in the incidence of breast cancer in menopausal patients, which is the dependent variable. The test would be used to determine whether the study would confirm the hypothesis of the study, which defines the expected outcome (Guetterman, 2019). The expected outcome is that the use of nursing education would reduce the incidence of breast cancer in menopausal patients.
References
Dalati, S. (2018). Measurement and measurement scales. In Modernizing the Academic Teaching and Research Environment (pp. 79-96). Springer, Cham. https://doi.org/10.1007/978-3-319-74173-4_5
Guetterman, T. C. (2019). Basics of statistics for primary care research. Family Medicine and Community Health, 7(2), e000067. https://doi.org/10.1136/fmch-2018-000067
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://doi.org/10.4103/aca.ACA_157_18
Manuel Ariel Garcia Periu
Quantitative Evaluations
A quantitative study systematically investigates phenomena by collecting quantifiable data and performing relevant mathematical or statistical techniques. It emphasizes objective measurements and numerical analysis using surveys, questionnaires, manipulation of pre-existing data, and other available tools. Descriptive statistics is the summative presentation of research findings in a meaningful way to identify patterns easily (Kapoor, 2020). These statistics only interpret available data and do not arrive at conclusions beyond what data analysis can provide. They help users have a simpler interpretation of data, highlight relationships between variables, and provide basic information about the variables used in a dataset.
Central tendencies are measured using the mode, median, and mean to obtain the central position from the lowest to the highest value. There are four measurement levels: “nominal, ordinal, interval, and ratio” (Thompson, 2019, p .300). There is an increasing level of complexity and precision from nominal to ration levels. The nominal level only categorizes data without ranking. In contrast, the ordinal levels classify and rank data in a given dataset using a particular order. The interval level is a cumulative of the nominal and ordinal levels as it can categorize, rank, and deduce equal intervals between adjacent data points. Lastly, the ratio level, which is the highest, organizes, ranks, infers equal intervals between data points and establishes a true zero point. Parametric tests are premised on assumptions related to population distribution because information about distribution is known and has fixed parameters (Sedgwick, 2015). Nonparametric tests evaluate the hypothesis for the population because nothing is known about population distribution.
It will be necessary to use quantitative tests to gauge the effectiveness of opioid addiction health promotion. The tests will mark areas with a more urgent need for intervention, track progress, and identify the population’s needs. Some tests will capture risk factors, demographic data such as ethnicity and race, education attainment, and income, and all these details help identify healthy behaviors and necessary healthcare policies.
References
Kapoor, R. (2020). Statistics corner: Reporting descriptive statistics. Journal of Postgraduate Medicine, Education and Research, 54(2), 66–68. https://doi.org/10.5005/jp-journals-10028-1364
Sedgwick, P. (2015). A comparison of parametric and non-parametric statistical tests. BMJ, 350(apr17 1). https://doi.org/10.1136/bmj.h2053
Thompson, W. J., Clark, A. K., & Nash, B. (2019). Measuring the reliability of diagnostic mastery classifications at multiple levels of reporting. Applied Measurement in Education, 32(4), 298–309. https://doi.org/10.1080/08957347.2019.1660345

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