Introduction to module 12 and 13

data-editing Data editing is the process through which one examines data to detect omissions and errors to rectify the. Through this process one ensures that their information is complete, legible, accurate and consistent. A response that can be applied in Jemma’s case is by finding errors in formulation of the questionnaire. The first step to take is evaluating whether the questionnaire respondent was consistent with the questions the answered. Editing of the questionnaire can be done through field editing and central editing. Through field editing Jenna may review the reporting for foot translating or completing. Central editing is carried out to correct obvious errors and inappropriate replies. Through coding, one assigns alphabetical orders or numbers to answers options so that the responses are collected in limited categories (Stuckey, 2015). Proper coding ensures that classes are relevant to the research question being studied. This process is very significant in effective data analysis. Making effective coding decisions during the design stage, simplifies the process of tabulation. Through exploratory data analysis is data is analyzed through visual methods to explore and summarize its main characteristics. Graphical techniques used in process the method mainly include histograms, run charts, scatter plots and odds ratio. With this information as the background information, this assignment attempts to discuss statistical questions based on a management case study of an arts festival marketing (Sall, 2017).


Assignment Questions

Jemma should have noticed some obvious problems in with how the questions had been coded. Some issues with the how questions were coded are lack prerecords of data in the first question, respondents answering to more than one question in question five and six, there existed no code for ‘none’ in the seventh question and question eight could be interpreted as two questions in one. In question nine one cannot tell the events being referred to by the respondents, the data in question ten was also not prerecorded and question three was unclear on which circle a respondent on the range age of 31-34 could have responded to.

In the survey design stage, these problems could be overcome in several ways. In question one, prerecording or listing events for the respondent would rectify the error. Question three could be reworded for easier understanding. Question five and six needed to be clarified further through a brief explanation. The code for ‘none’ was needed for question seven while question eight could have been made to be two separate questions. Question nine needed to be event specific hence rewording would be recommended (Quinlan, 2019). Question ten problem could be overcome by creating a hierarchal coding scheme and adding “leave blank for coding” space.

Jemma’s’ research had questions that had a very high likelihood of being asked. Determining the important questions could be done in through the 3 aspects she is most interested in. The three important aspects include the socio- economic state of the attendees, the level to which sponsors associate with the audience as well as the role played by media in determining the events. As per the three categories, it is clear that the sixth question could have been useful in evaluating association of sponsors and audiences while the fifth question could have been useful in evaluating the socio economic status of those in attendance. There existed no questions that fit to evaluate the third aspect.

Jenna could have minimized the impact in coding of her questions through a variety of strategies. For instance, she could have used multiple response method or multiple dichotomy method to code responses to problems associated with the fifth and sixth question. In either of the queries, it would have been important to recode where possible to existing variables and codes. New codes and variables would have to be generated if the “other” large number was apparent. Multiple response method would have worked much better if there were a significant number variables and new codes.

Despite there being only two questions that are relevant to the introduction case that has 3 aspects, there are other questions that might be useful. Generally, the ninth and eighth questions are very limited and unsuitable to use. Pie chart mode could be recommended for use in the third question to indicate the common age band and the proportions per age band. Bar and table charts could be used in the fifth question to indicate the percentages or number of people through classifications per economic activity. Bar and table charts could also indicate the percentage or people that associate to certain organizations to the festival. Additionally, chi square tests and cross tabulations would be possible foot the third and fifth questions against the sixth and seventh question. Cross tabulations and Chi squares would be great measure of important differences.

The scatter plot interprets the relationship between the ease of booking a ticket to the age. There exist two observation points on each coordinate in the graph. The X coordinate and the Y coordinate. The intersection of the two coordinates forms observation points in form of dots. This is also called a correlation, which is visual representation of the relationship between the two variables (Chambers, 2017). The graphical presentation has two properties which are direction and strength. This graph has a positive correlation that has determined its direction. Both variables in this graph seemingly move in similar direction. This means that if one variable decreases the other one decrease as well and if a variable increases, the other does the same. There are strong variations that show a lot of strength intersection points as well as weak intersection points showing weaker strength.
From observation of the scatter graph, the ease of booking at ticket is at a younger age is very high and lowers at an older age. The younger the age, the higher the ease of booking a ticket while the older the age, the lower the ease of booking a ticket. A great example is the highest point in the graph that indicates easiness to book a ticket which is between ages of 18 and 19. The lowest point to easiness of buying a book is indicated to be over the age of 60. Points of intersection also heavily concentrated at the ages of 19 to 45. The points of intersections show that that people in this age group were highest in the study compared to people aged below 19 years or above 60 years.


This statistical research answers important questions on processes Jemma should take in the process of Coding. Some issues that she should notice in the questionnaires are lack of prerecords and lack of clarity in the questions. Some questions in the research also have more significance than others. The pie chart mode and tables were the most suitable for the third and fifth question. An analysis of the scatter plot also gives a deeper understanding of the data presented.


Chambers, J. M. (2017). Graphical methods for data analysis: 0. Chapman and Hall/CRC.
Quinlan, C., Babin, B., Carr, J., & Griffin, M. (2019). Business research methods. South Western Cengage.
Sall, J., Stephens, M. L., Lehman, A., & Loring, S. (2017). JMP start statistics: a guide to statistics and data analysis using JMP. Sas Institute.
Stuckey, H. L. (2015). The second step in data analysis: Coding qualitative research data. Journal of Social Health and Diabetes, 3(01), 007-010.

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