Students able to understand what secondary data is and what are the different methods for collecting secondary data.

Running head: EXPLAINING OBSERVATION AND EXPERIMENTATION 1

EXPLAINING OBSERVATION AND EXPERIMENTATION 6

OBSERVATION AND EXPERIMENTATION

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Explaining Observation and experimentation

Observation is a scientific study of variations in which data is collected through surveying — the information collected by the researcher by hearing responses or merely observing the variables. Conclusions are made from what has been gathered by either of the methods. In observation, there should be no interference with the study in any way. To study the effect of sports on class performance, a teacher will select randomly ten students active in sports and ten that are not. Their report cards will be checked for the whole year and analyzed, interpreted and conclusions made.

Experimentation is a style for examining scientific practice. In this category, investigators apply treatments to variables and later recording the effects. The records taken should be based on the effects of the treatment given. In this study, the independent variable is controlled, which means that there is interference with the survey (Gomes et al., 2018). For example, to study the effects of sporting activity in student’s class performance, a teacher will select randomly half of the students to participate in sporting activities for one hour daily and the other half not given this treatment. At the end of the year, the grades of the students are analyzed, interpreted and a conclusion drawn.

Sources of secondary data information

Secondary data is information gathered by another person other than the user. They are information that are not derived from their original source, therefore reported in another source. They include information from internet searches, electoral statistics, tax records, among others.

Differences among nominal, ordinal, interval, and ratio scales

The nominal scale is a level of measurement in which the groups are only named to create a noticeable classification. It is only used where labeling is of importance. For ordinal scales, it has all its variables structured other than just giving them names for example, including gender. The third level of measurement is, Interval scales which entail labels, order as well as the definite interval for each group (Awang et al., 2016). This scale checks on differences between variables but have no true-zero value. The highest of these level is the ratio scale; the unique characteristic is that it accommodates absolute zero. Attitude scales in some occasions fall in this category.

Sample versus Census

Sample entails a process of investigating a population in which few units are studied to represent the rest. Conclusions in this method are based on the analysis of the data recorded from the sample selected. Sample has a scope of error, but this can be reduced by using more units. Census, on the other hand, is a procedure of formally acquiring and recording data about an entire population. Information is collected from everyone through a complete count. This method consumes a lot of time labor and finances, but it is more reliable since it allows for a low margin of error.

Differences between a probability sampling and a non-probability sampling

In probability sampling, the selection criteria are random, and each member of the population has an equal chance to be picked for the survey. Because it is random in the selection, the results usually are unbiased. Non-probability sampling, on the other hand, is non-random and therefore, not known who among the population will be selected as a sample (Vehovar et al., 2016). Because the selection is arbitrarily conducted, the method is subjective, and the results are biased.

Direct and indirect questions

Direct questions are questions that are asked to people that that one knows well, for example, a colleague at the workplace, a friend or relative. For example, what did you tell him about me? On the contrary, indirect questions are questions asked to get information or ask personal questions politely. For example, Do you know the owner of that car?

Open-ended and closed questions

Open questions are questions that allow for free responses. The response could be a single word or in a paragraph. They are usually asked to get qualitative information. Closed-ended, on the contrary, offers a limited selection of answers. They are for answering ‘why’ questions.

Research, investigative, and measurement questions

Research questions are those that are intended for issuing solutions to a particular dilemma. This is after having an idea of what is to be studied. Investigative questions are research inquiries that are specific and give specific coverage to the research question (Fisher et al., 2016). Measurement questions, these are questions that are answered by the correspondent and the response used to provide answers to management questions after they have been examined.

References

Awang, Zainudin, Asyraf Afthanorhan, and Mustafa Mamat. "The Likert scale analysis using parametric based Structural Equation Modeling (SEM)." Computational Methods in Social Sciences 4.1 (2016): 13.

Fisher, G.G., Matthews, R.A. and Gibbons, A.M., 2016. Developing and investigating the use of single-item measures in organizational research. Journal of occupational health psychology, 21(1), p.3.

Gomes, Hugo S., Ângela Maia, and David P. Farrington. "Measuring offending: self-reports, official records, systematic observation and experimentation." Crime Psychology Review 4.1 (2018): 26-44.

Vehovar, Vasja, Vera Toepoel, and Stephanie Steinmetz. "Non-probability sampling." The Sage handbook of survey methods (2016): 329-345.