Research data can be defined as a factual data that is recorded through different sources and is accepted widely by scientific communities which is necessary for data validation. There are different types of research data which includes documents and spreadsheets in the form of text or word, questionnaires, laboratory and field notebooks, database contents, test responses, audio or video tapes and so on.
This research data can be stored and managed in different ways, i.e. project files, research and technical reports, and electronic or paper based mails.
Mainly, research data can be classified as raw or primary data, processed data, and published data. Raw or primary data consist of the information recorded as computer files, images or surveys. Processed data consist of reports or descriptions, and published data is information that is distributed among people as a reliable source.
Considering the case of our topic “Usage of smart phones”, research data will be collected through telecom companies, surveys and smart phone dealers and companies. The information is recorded in terms of numerical data, i.e. number of smart phone users over the world. Smart phone companies and dealers will provide information on their sales in a year and details of the customers, i.e. their gender, age group and location. This information is usually stored in the database and other manual records. More information can also be collected through users by means of surveys, questionnaires and interviews regarding their requirements and the purpose of usage.
Types of Research Data
Different types of research data can be broadly categorized in 2 types of data, i.e. qualitative and quantitative data.
- Qualitative data
- Quantitative data
Qualitative Data
Qualitative data are the one which is expressed by means of natural language description. This type of data is also called categorical data as it is based on categories. Data is analyzed as according to the type of category i.e. ordinal or nominal. Qualitative data are never expressed in terms of numbers, but only describes the quality or physical traits of information. As discussed earlier, the information collected for the details of usage of smart phones will not be qualitative data but rather quantitative .
Quantitative Data
In comparison to the qualitative data, quantitative data is opposite. It is expressed in terms of numbers or numerical measurement. This information is not measured in the form of natural language because every data is not continuous or measurable. If it is not easy to measure data quantitatively, then research scales are being used. Rates are being assigned with numbers. This makes it easier to measure the strength of particular data .
In case of the topic “Usage of Smart Phones”, information collected through different sources, i.e. telecom and smart phone companies, customers, and dealers will be in the form of quantitative data. Since, the topic is to measure the rate of smart phone usage by time, so it can only be compared, if the information is in the form of numbers.
Methods of Collecting Quantitative Data
There are different methods of data collection, i.e. interviews, surveys, objective measuring, and transcript analysis and so on. In case of usage of smart phones, different techniques can be used. For example, interviewing with the customers and dealers, collecting information through questionnaires, and using an objective measuring technique for focusing only on usage of smart phones.
In order to conduct quantitative research, the researcher needs to follow a particular set of techniques as according to the requirements of research. First, the problem statement is clearly and concisely defined. Second, the related research or literature is reviewed regarding the topic. The third section elaborates theoretical framework, define related concepts and state hypothesis.
Later on, specific methodology is followed to conduct the quantitative research. Population and samples are being studied and selected appropriately as per data collection feasibility. Different tools and methods are being used to collect information. These techniques are being elaborated in the methodology section. In later sections, data are being analyzed using different programs and tools.
Results are stated in the next chapter and later being discussed. Statistical analyses are usually carried out through software programs i.e. MS Excel and SPSS. Results are discussed by means of using charts, graphs, and tables. These statistical measures can easily be retrieved through using software programs. The hypothesis are then tested and discussed by measuring the relationships and impacts of one to another variable. In the last section, research limitations and the gap between the literature and current study are being discussed.
In case of “usage of smart phones” research, data will be collected from 50 people randomly in a specific area. Questionnaires will be distributed among the users of any age. The questionnaire will collect demographic information, queries related to purpose of usage of smart phones, and duration of usage. This collected data will then be fed into the MS Excel program and analyzed. The hypothesis will be tested by carrying out correlation tests. Later, the results will be discussed and concluded.
Besides collecting data through the users, information will also be collected through smart phone companies and dealers so that to record information regarding the growth of usage of smart phones. Interviews will be conducted by the sales manager of different smart phone companies. Moreover, sales reports of the companies will be reviewed to know about the growth of smart phone usage.
As according to the statistics and research, it is expected that the number of smart phone users will surpass 1.75 billion in the year 2014. It is also expected that there will be 4.55 billion mobile phone users worldwide in the year 2014. This increase is mainly due to penetration of mobile phones in Asia-Pacific, Middle East and African countries. It is expected that penetration will increase from 61.1 % to 69.4% between 2013 and 2017. As according to eMarketer, it is found, adoption of smart phones is being increased. About two fifth of all mobile phone users worldwide has already switched to smart phones and this rate will keep on increasing till 2017 .
Mobile phone users are switching to smart phones due to several reasons. First, they cost economical due to affordability of 3G and 4G networks in phones. Smart phone users mainly use their phones for the purpose of the fast speed internet and various other features. Tablets are also getting popularity worldwide, especially among adults . It has been found through other research that trends in US, UK, France, Germany, and Japan are changing. Most of the smart phone users prefer using their phones to access an internet and for other work instead of their computers. This trend is not only common among adults but is also increasing among aged of 45+ years. Smart phones have already been penetrated 45% in the UK, 38% in France and US, 23% in Germany, and 17% in Japan .
Advantages and Disadvantages of Data Collection Method
This research is mainly focused on determining the rate of increase in the use of smart phones, the gender and age of the smart phone users, purpose, and for how long or duration they use smart phones. In order to determine this information, two units have been selected. Firstly, the smart phone companies’ managers to know about the rate of their sales each year and secondly, the smart phone users to know about their demographic information, purpose and duration of smart phone usage. Other secondary sources will also be used for the purpose of building up the base of research and so the hypothesis. Questionnaires will be distributed among the users and managers to know about the concerned details.
Population for this research is too large therefore data cannot be collected from all people around the world, therefore sample will be chosen. The sample will consist of 50 people randomly selected of different ages. However, this sample may show a certain percentage of probability error because of less number of records. But to the other side, an idea of the results can be concluded on the basis of small sample representing worldwide smart phone users. On the basis of the results of this research, various important decisions can be made. This research can be highly useful for the smart phone companies. It will also help them identify the age group in which smart phones are more popular and for what purpose. Thus, they can focus more on particular features that their users want in smart phones and market them.
Results
Correlation between age and hours = -0.710204203
There is a negative correlation between age and hours. It means that the usage of smart phones decreases with an increase in the age. Aged people do not spend more hours using smart phones. It has been also found through the chart that smart phones are more popular among youngsters or adults.
- The hypothesis, usage of mobile phones is most popular among youngsters is already been verified with the above scatter chart. Since, the chart shows the number of users in the early section, i.e. before 30 years of age.
- There is a 4% probability that smart phone users above or equal the age of 40 years use it for web browsing.
5a) Randomly selected person having phone usage time which is between 4 hours and 7.5 hours = 21/50 = 0.42 or 42%
5b)
Works Cited
Australian Bureau of Statistics. Quantitative and Qualitative Data. 4 July 2013. Statistical Language.
Ipsos MediaCT Germany. Mobile Internet & Smartphone Adoption. Germany: Google, 2011.
Jaume, Jasmine. Smartphone and Tablet Use Continues to Rise: The Stats. 19 June 2013. Brandwatch.
McLeod, Saul. Qualitative Quantitative. 2008. Simply Psychology.
UO Libraries. Research Data Management. 2014.
Webinar, eMarketer. Smartphone Users Worldwide Will Total 1.75 Billion in 2014. 16 Jan 2014.
