Collection and Editing of Data || What exactly is the difference between primary and secondary data || What is the distinction between a mistake and an error?

Collection and Editing of Data

Q.1 What do you mean by data collection? Distinguish between primary and secondary data.

The primary activity of statistical science is data collection. It refers to the collecting of information and numbers linked to a certain occurrence under the study of any subject, whether in business economics, social sciences, or natural sciences. Such information might be received directly from individual units, referred to as primary sources, or from previously published material, referred to as secondary sources.

What exactly is the difference between primary and secondary data

Q.2 What exactly do you mean by "questionnaire"? Give the advantages of a good questionnaire.

A questionnaire is a document that contains questions relevant to the specific demand of a statistical inquiry for the gathering of information, and it is filled out by the informants themselves.

A good questionnaire should include the following characteristics:

                                                        i.            Questions that are straightforward, clear, and concise.

                                                      ii.            Simple multiple-choice or alternative questions.

                                                   iii.            Unmistakable and precise.

                                                    iv.            The questions should be asked in the correct order.

                                                      v.            Accuracy test.

                                                    vi.            There will be no restricted queries impacting personal whims.

                                                 vii.            Assurance of confidentiality to informants.

                                               viii.            The likelihood of a flawless solution.

                                                    ix.            Questions that are directly relevant

Q.3 What are the laws of 'Statistical Regularity' and 'Inertia of Large Numbers'?

Based on probability theory, the Law of Statistical Regularity argues that if a sample is drawn at random from a population, it is likely to have the same characteristics as the population. A sample chosen in this manner would be representative of the entire population. If this criterion is met, it is feasible to describe the features of the population pretty accurately by analysing only a subset of it.

The 'Concept of Inertia of Large Numbers' is a corollary to the law of statistical regularity. It asserts that all else being equal, the greater the sample size, the more accurate the results are expected to be. This is due to the fact that when big numbers are evaluated, the changes in the component components tend to balance each other out and, as a result, the variance in the aggregate is unimportant.

Q.4 What exactly is random sampling? Alternatively, define Random Sampling.

Random sampling is a method of selecting objects in such a way that every item in the universe has an equal chance of being chosen. Random sampling is a probability-based method that is devoid of bias.

The many ways of Random Sampling are as follows:

a) Lottery method.

b) Turning the drum.

b) By methodical organisation.

d) Routed wheel technique

e) Using random numbers

Q5. What exactly do you mean by statistical error? What is the difference between a mistake and an error?

The discrepancy between the actual and estimated values of a figure is referred to as a statistical error. For example, if the number of students at a college is 1,255 but printed in round figures as 1,300, the disparity is referred to as a 'Statistical mistake.' Prof. Connor defines "error" as "the difference between the estimated value and the real or ideal value, the exact determination of which is not feasible."

What is the distinction between a mistake and an error?

Q.6 Create a note on the Editing of Primary and Secondary Data for Analysis and Interpretation.

Before analysing and interpreting the data, it is required to edit it to uncover any flaws and inaccuracies in order to achieve reliable and unbiased findings. Thus, editing refers to the act of checking for mistakes and omissions and, if required, making fixes. Editing is a highly specialised activity that needs a high level of ability and attention to achieve the desired level of correctness.

Primary Data Editing:

The following considerations should be kept in mind when altering primary data:

                                                        i.            Consistency editing

                                                      ii.            Editing to ensure completeness

                                                   iii.            Editing for precision

                                                    iv.            Editing for consistency or homogeneity

Secondary Data Editing:

Because secondary data has already been gathered, it is extremely desired that such data be thoroughly examined before being used by the investigator. Bowley correctly observes that "secondary data should not be accepted at face value."

As a result, before considering secondary data, investigators should examine the following:

                        i.            Whether the Data are Appropriate for the Purpose of the Investigation: Quite often, secondary data does not meet current demands since it was compiled for another purpose. The variance might be in the units of measurement, the date/period to which the data is connected, and so on.

                                               ii.            Whether or whether the data is sufficient for the investigation: The adequacy of data is to be assessed in light of the survey's requirements and the geographical region covered by the available data. For example, if our goal is to investigate the salary rates of workers in the sugar business in India, yet the available data only covers the state of Rajasthan, the study will be ineffective.

                                                   iii.            Whether or not the data is reliable:

The following factors should be considered when determining the dependability of secondary data:

                                                        i.            The collection agency was objective.

                                                      ii.            The enumerators have received sufficient training.

                                                   iii.            A thorough examination of the correctness of the fieldwork.

                                                   iv.            Was the editing, tabulating, and analysing done meticulously and conscientiously?