Essay on Analyzing Statistical Methods: A Critique of a Survey on Newspaper Readability in the Digital Age

Introduction

Surveys constitute critical studies that intend to prove a hypothesis by presenting elaborate and practical research on a subject. Some of the vital models of survey include estimation and statistical inferences which apply data from a sample size of the targeted population. From the sample size, estimations are made about a population. Sample surveys are concerned with collecting data and constitutes mail, telephone, and face to face interviews. Furthermore, the data is collected through questionnaires that are appropriately phrased, arranged correctly, and grouped to capture the intended information. This work will analyze a survey published online concerning the readability of Newspapers in the Digital Age. It was written by Dr. Fouzia Naz.

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The surveyed focused on the way people think about newspapers and their effects on leadership, particularly in the new era. Moreover, the survey studies people’s perceptions and habits that impact their reading routines (Naz, 2015). The survey undertook its study on a sample size of 464 participants recruited based on non-probability convenience of residence of various parts of Karachi. The study noted that the average time that men spend on Newspapers is more than women and larger percentage of the readers come from the people working for the government and private organizations (Naz, 2015). The author found that these individuals have a higher trust for the information printed in the papers.

Statistical methods Used in the Survey

The survey applied various statistical methods in its data analysis to find a pattern on the subject. Under its methodology, the survey outlined the sources of data as primary and involved an empirical analysis. The data was collected from five places in Karachi and involved both genders in business, employment, government, private sector, scholars and learner. Moreover, the instruments of data collection applied in the material were structured questionnaires presented to the participants. The method ensured accuracy, reliability and ease of data analysis.

The sampling of the participants was 464 and composed the residences of the area of interest. The sample was collected to represent the entire population through the use of a controllable number of people. Moreover, data collection tools are vital to statistical surveys. Thus, the author used both questionnaires and the interviews to reach majority of the respondents and record the data. The data was tabulated in percentages for easier presentations and inputting into the statistical software for further processing. Moreover, concerning the data analysis the survey applied percentages for all of its processing where an item is compared with the rest of the items captured in the survey.

In the original context of the survey, sample involves a subset of the population for the study. Thus for the study on the readability of newspapers the sample represented the larger population but owing to the data for processing (Agha, 2018). The grouping of the samples is either probability or nonprobability based on which the presented survey adhered to such a classification. It was a nonprobability sample. Thus, the probability type is based on the probability mechanism which allows the use of statistical inferences. The sampling error describes the margin of variance between the estimated value and true value (Agha, 2018). However, the nonprobability allows data analysis which is based on additional assumptions to attain results.

The overwhelming data calls for more analysis of the data using statistical methods such as mean, variance, regression, standard deviation, pitfall and sample determination (Bhatti, 2016). By the method of mean, the original analysis constitutes the average of the total responses divided by the number of the participants which in our case it was 464. The statistical model is both easy and fast to calculate. A pitfall is a tool used to complement the mean closely related to the mode and median. Thus, for a large dataset with skewed distribution, the mean does not offer reliable information.

Moreover, the standard deviation is among the advanced tools for data analysis in the original survey that describes the spread of the collected data from the average value (Edjabou, 2017). Consequently, a larger value of standard deviation indicates that data are spread widely away from the mean otherwise it is closer to the mean. The tool is significant for quick determination of data dispersion which was not reflected in the survey above.

Furthermore, the published survey lacked the regression tool of analysis, which relates the dependent and independent variables and majorly shown on a scatterplot (Agha, 2018). The regression approach describes how dependent and independent data are either strong or weak according to time. Moreover, the survey does not show the t-test which otherwise known as hypothesis testing. Also, the published survey indicated that is a descriptive type of statistical work. However, the material lacked summarizing datasets using various statistical quantities. The probability aspect of the survey lack originality with the absence of chances of events that governed the probabilities of events. The absence of statistical software for analysis such as Excel and SPSS reduces its classification of the survey as statistical. Original surveys use such applications for large data, fast and accurate processing.

References

Agha, G. a. (2018). A survey of statistical model checking. ACM Transactions on Modeling and Computer Simulation (TOMACS), 28(1), 1-39.

Bhatti, Y. a. (2016). News reporting of opinion polls: Journalism and statistical noise. International Journal of Public Opinion Research, 28(1), 129-141.

Edjabou, M. E. (2017). Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation, and correlation coefficients. Waste Management, 69, 13-23.

Naz, F. (2015). A Survey about Readership of Newspapers in the Digital Age. International Journal of Innovative Science, Engineering & Technology, 2(1), 251-258.