Dare to Ask Mian Aamir All about Business Research Process

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[highlight]Dear sir,Please elaborate of data presentation in tables with some easy examples[/highlight]

Dear student, I appreciate your query and glad that you asked.

Data presentation refers to present data in form of tables and graphs in order to infer meaning from the research data. For example frequency distribution table is one of the forms to present data in numerical form. Assume you have hypothetical data of 1000 students with four categories i.e. “excellent”, “average”, “below average” and “Fail”. As per data, 500 students passed the course excellently, 250 students lie in average category, 200 students lie in below average category and 50 students failed the course. In order to construct a frequency distribution table you have to draw percentages of each category in such a way;

Student performance in Artificial Intelligence course (MCS)

Passing criteria

Frequency

Percentage

Excellent

500

500/1000*100=50

Average

250

25

Below average

200

20

Fail

50

5

Total

1000

100

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Q: What is meant by wider generalisability?

Q: Please give examples of Probability & non-Probability sampling?

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Dear student

“Generalizability” means making predictions on the basis findings got. Similarly wider generalizability means stating the results to a broad level.

As there are many types of probability and non-probability sampling; the example can be narrowed down to one type of probability sampling which is random sampling. The most common example of it is lottery method. In this method sampling frame is made and unique number is given to each item. Number is selected either by selecting piece of paper having written unique number assigned to each item or through computer software.

The example of non-probability sampling can be convenience sampling. Such as a student who wants to do research on knowing perception of people regarding the super markets can gather data on convenience basis from the respondents who are available at ease.

[highlight]AOA. sir What is field editing n in house editing kindly tell me easiest example which me understand easily.

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Data editing is a very important and essential step in research. Problems in data editing are; not following instructions properly, the issue of including or cancelling the response if two options are ticked by the respondent and the presence of inconsistent responses.

The editing can further be of two types:

Field editing: it refers to editing the responses in the field by field worker as soon as responses are gathered. For example if some response is missing then fieldworker can spontaneously follow up the respondent and get the required answer immediately.

The second type is in-house editing: sometimes responses are two much that initial screening of responses does not point out the responses not answered. This asks the editing while entering the data. For example a researcher while entering the data in the system edits the non-responses is in house editing.

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Q: Main difference between open ended and closed ended questions?

Q: Is the logistical support adequate? Please sir describes this point clearly from book I can’t understand.[/highlight]

Dear Student

You are directed to view my previous post in this regards Click at the below link

Dare to Ask Mian aamir all about VU Final Project

[highlight]Sir please explain coding and code construction in simple words and also define rules for code construction?[/highlight]

[highlight]Sir plz give easy example of strated sampling thanks[/highlight]

I perceive your query is about stratified random sampling.

The stratified sampling technique is used when population is heterogeneous. Sample selected from simple random sampling in heterogeneous population may select disproportionate number of one group or the other. Thus, in order to make sample representative of population, researchers make strata that are homogenous within itself. For example researcher is interested to know the achievements of school students. Firstly researcher has to split school in strata i.e. public, private and semi government schools. After making stratum research can select sample from each stratum by simple random technique in order to have maximum representation of population.

[highlight]Why questionnaire Design?its is essential for data collection tools?[/highlight]

Dear Student

While conducting a research, a researcher sets some questions and to answer those questions he/she needs some evidences. Those evidences may be in the form of data. To collect the data various techniques are used like making observations, conducting interviews, performing experiments and conducting surveys. In surveys, to find the perception of participants, researcher needs a standardized tool against which he/she can collect data. The standardized tool is called questionnaire and to make it standardized, researcher has to design that questionnaire according to predefined rules. For all studies, it is not necessary to design questionnaire. Sometimes researcher uses already developed questionnaires and in some case, he/she develops new questionnaire.

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