The main objective of my article is to review the content of the data provided based on the scientific research method approach. Since the statistical analysis of research data is meant to communicate to users, I will give a personal insight into data and information provided as my last remarks. We can define Hypothesis testing a procedure that involves the use of statistical tests on sample data to determine the credibility of a specified claim. The researcher's goal is to make an informed conclusion on a claim considered to be true pertaining to population parameters (Freeman, nd).
Data collected is complex and insignificant in communicating the state of the phenomena to users. The data analysis phase transforms raw data into a user-friendly product that is simple to study and comprehend. The scientific approach of research recommends researchers to start by conducting a descriptive analysis of their sample data. The second step in data analysis involves inferential statistics procedure, which varies depending on the nature of data and the objective of the researcher. Descriptive statistics is mainly applied to measures of central tendency and virtual presentation through charts and tables (Smith, 2018).
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Data used in scientific research should be credible and reliable data, and it can be obtained from primary or secondary sources. The process of hypothesis testing has three major phases developing a research design, data collection, and conducting statistical significance analysis. Each phase of the process has several steps, and a researcher must adhere to convectional scientific research principles applied to the whole process, phase, and step to make research findings credible (Smith, 2018).
The data provided on the 'sample Excel spreadsheet' pertains to questions asked to college students on their mobile phone use behaviors. The primary objective of collecting sample data was to test the significance of mobile phone use impact on destructing sleeping pattern among college students. The sample data has six questions with multiple response choices from which respondents picked the response that befitted their mobile phone use behavior.
Data collection and Findings
The data collection tool was, and findings can be summarized as illustrated in the table below.
Research Tool Structure |
Raw Data Collected | ||
| Core Phone Use phenomena Investigated | List of choices | Frequency of each response | Percentage |
|
Mode of phone alerts while asleep Q- ‘Do you sleep with your phone on silent, vibration, both, or neither?’ |
Silent Vibration Both Neither |
9 6 0 0 |
60.00% 40.00% 0.00% 0.00% |
|
Destruction from sleep by phone alerts and notifications Q- ‘If you leave your mobile phone on the ring, then do you wake up to the sound of your phone every time you get text messages, email, or phone call?’ |
Yes No |
4 11 |
26.67% 73.33% |
|
Features, services, and apps frequently used before going to sleep Q- ‘Which features of your mobile phone do you use if you use your phone within the range of two hours before sleep? (Check as many as applicable)’ |
Texting/Messaging Phone call/Video call Internet/Web Browsing Playing Games Social Networking |
14 4 9 1 11 |
35.90% 10.26% 23.08% 2.56% 28.21% |
|
Use of mobile phone before sleeping Q- ‘Do you use your mobile phone leading up to you going to bed?’ |
Yes No |
12 3 |
80.00% 20.00% |
|
P hone location while asleep Q- ‘Where is your mobile phone located when you go to bed?’ |
Within arm’s reach On your study table Not within five feet of your hands Not in your bedroom |
11 2 2 0 |
73.33% 13.33% 13.33% 0.00% |
|
Sleeping hours Q- ‘What is your average hours of sleep every night?’ |
Eight or more hours 7 to 8 hours 6 to 7 hours less than 6 hours |
0 7 4 2 |
0.00% 53.85% 30.77% 15.38% |
Table 1.0. Research questions and findings summary
Findings and conclusion
From the data provided, the first inference one can make is that the phone has an insignificant effect on college students sleeping patterns. The reason why one would make the claim is that 60% of students leave their phones on silent mode and 40% on vibration. Alert mode can increase destruction. Another reason for the inference is 73.33% do not respond to incoming notifications while asleep. The second inference is that college students have no significant use of the mobile phone on personal recreation and cognitive enhancement. Web-browsing and games only account for 25.64% of phone use, while social life-related issues account for 74.36%. The third inference pertains core subject, which one can state as "college students have adequate sleeping hours." 84.62% of respondents slept for 6-8 hours, which is adequate for adults.
The conclusion arrived above is based on data provided, and therefore, the credibility of the data is crucial. To enhance the perception of the data, one would enquire from the researcher the following three issues:
What is the target population size? Population size would help to determine if a reliable sample size was used.
Do students have access to free internet? Free internet can influence student use of the mobile phone for recreation, studies, and even social media.
What was the gender for each respondent? Gender can be used for comparative studies and evaluation between male and female students.
The researcher managed to present the data well using tables and charts, which include pie-chart and bar graphs. The use of different colors to represent for different observations and well-spaced bar-graphs contribute to clarity, enhances communication of findings, and maximize capacity to enhance user interaction and understanding (Freeman, nd).
References
Freeman, J.V. (nd). Scope Papers. Retrieved from: https://www.sheffield.ac.uk/polopoly_fs/1.104345!/file/Scope_tutorial_manual.pdf
Smith, M. (2018). Statistical Analysis Handbook. Retrieved from: www.statsref.com
