Lecture 4 Chapter 8: Secondary data Chapter 9: Primary data For both qualitative and quantitative research projects Chapter 9: Primary data For mainly quantitative research projects (p2) (p13)

Chapter 8: Secondary Data Data that have already been collected for other purposes, perhaps processed and subsequently stored, are termed secondary data Most research projects require some combination of secondary and primary data to answer research question(s) and meet the researcher’s objectives Where can we get them? (Figure 8.1) Other sources (refer to Tables 8.1 to 8.3, pp 255-258) (p3) (p4)

Figure 8.1 (p2) 3

Using Secondary Data Secondary data can be used in a variety ways: To provide the main data set; To provide longitudinal (time-series data); To provide area-based data; To compare with, or set in context, research findings. (p5)

Secondary Data (cont) Attention notes: Any secondary data that are used will have been collected for a specific purpose In addition, the secondary data are likely to be less current than any data collected by the researcher (why?) (p6)

How to find it Finding the secondary data required is a matter of detective work It involves with: Establishing whether the sort of data required are likely to be available; Locating the precise data (refer to Figure 8.1 for all possible sources) (p7)

Suitability Once located secondary data sources must be assessed to ensure their overall suitability for the research question(s) or objective(s) In particular attention must be paid to the measurement validity and coverage of the data How to evaluate? Pros and Cons (p8) (p9) (p10) (p12) (p1)

validity Ensure that Data match to what u need (since most data may not be measuring it up for what u wanted) (p7)

coverage Ensure that (p264): Unwanted data are or can be excluded Sufficient data remain for analyses to be undertaken once unwanted data have been excluded (p8)

Suitability (cont) Criteria to use: (Figure 8.2) Note: Reliability Bias Deliberate distortion of data inaccuracy (for either unintentionally or intentionally) costs and benefits in comparison to alternative sources, such as time and financial resources and will it answer your research questions Note: when assessing costs and benefits it is important to remember that secondary data that are completely reliable and contain some bias are better than no data at all if they enable the research question(s) to be answered partially and objectives met (p11) (p7)

(p10) (Figure 8.2) 11

Pros and Cons Pros (p257) May have fewer resource requirement Unobtrusive Longitudinal studies may be feasible Provide comparative and contextual data Result in unforeseen discoveries Permanence of data (p260) Cons May not match with what you need for your objective(s) Access may be difficult/costly Aggregation and definitions may be unsuitable No real control over data quality Initial purpose may affect how data are presented (p7)

Chapter 9: Primary data Here, we attempt to gain understanding the role that observation may play as data collection method in research design Two types of observation: Participant observation Structured observation (p14) (p20)

Participant observation It is a method in which the researcher participates in the lives and activities of those whom they are studying It may be used in a student placement, or the student may already be a member of an organization that will enable him or her to adopt the role of the practitioner-researcher (p15)

Participant observation (cont) Participant observation means that the research adopts a number of potential roles differentiated by the degree to which his or her identity is/is not concealed from the subjects of the research and the degree to which there is researcher participation in the events being studied How it works? (Figure 9.1) Which above method is a better? Data analysis and its result validity (subject to biasness) Pros and cons (p16) (p17) (p18) (p19) (p13)

(Figure 9.1) 16 Observing how things Works in office with Involvement in it, spying! Unethical? Observe and participate With identify revealed Observing without Taking part in it, such As exploratory study Observe without participate (Figure 9.1) (p15) 16

Participant observation Influencing factors Influencing factors (pp 286-288): The purpose of research The time devotion Degree to which you feel the suitability Organizational access Ethical considerations (p15)

Participant observation Data Analysis A prevalent form of data analysis used in here is analytic induction. (That is to establish what is going on) This may lead to an initial hypothesis being re-developed more than once (p15)

Pros and cons (pp 293, Table 9.1) Pros Cons Good to explain “what is going on” Provide insight to social process Useful to organizational management Practical real experience/feeling could be gathered All data collected are mostly useful Cons Time consuming Difficult to launch ethical dilemmas May consist of “role of conflict” between being employee and researcher Biasness may exit Special skill may required Difficulty to access organizations for participate Data recording is difficult (p15)

Structured observation It is concerned with the frequency of events. It is characterized by a high level of predetermined structure and quantitative analysis It tells you how often things happened rather than why they happened When to apply it? (p21)

How to evaluating its validity and reliability? Answer: “Time-and-motion” study, data collected from streets/mkt Pros and Cons How to collect data ? How to evaluating its validity and reliability? (p22) (p23) (p24) (p13)

Structured Pros and Cons (Table 9.2, p298) Pros Anyone can apply it after some training Can be adopted in different locations for result comparison Highly reliable results because it is actual event Possible to record the relationship between events Data cannot collected at time they occur then based on “second-hand” accounts Secure data that might otherwise be ignored by participants Cons Observer must be in the setting when phenomena under study are taking place (ie at the site) Results are limited to overt action or surface indicators Data are slow and expensive to collect (p21)

Structured observation (cont) A choice may be made between “off the shelf” coding schedule and a schedule that is designed for the purpose of the particular piece of research (refer to p297) (p21)

Structured Observation Validity and Reliability Treats :(p 301) Subject error Ensure subjects are performing normal routines Time error Ensure untypical time is not included in the observation Observer effect Ensure that the subjects are not conscious of being studied Remedies: a) minimal interaction b) habituation (ie adapted to it) (p22)