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Inductive research/observation/reasoning means using a particular observation to generate general explanation. For example, after eating sandwich from KFC over a month, you concluded that all sandwich at KFC outlets are delicious.

In most works of literature, survey has been defined as the collection of facts and figures to gain insight about a specific subject, hence quantitative in nature.

The statement: the average weight of Americans studying at Harvard is 45kg. This statement can either be true or false. We can only test this hypothesis by recording the weight of each and every American student studying at Harvard and then finding out whether the average weight is indeed 45kg. This is an example of a hypothesis.

Applied research are those research that are meant to directly solve problems to improve human conditions. Fundamental research is a kind of research solely meant for knowledge acquisition. It helps to expand our knowledge beyond our immediate surroundings.

Sample size play a very important role in every research you undertake. That is why it is very essential you gather enough information about your subject.

Let’s assume from the scenario illustrated here, that the average income of all the customers is $1,300/month. Given that this amount is calculated from the sample drawn from the population, it is called a Statistic or Sample Statistic.

Imagine this, you (as a researcher) have been tasked by a large marketing company in your country to find the average income of all their customers to help them formulate new marketing strategies to enrich consumer preference and interests.
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Let’s take a look at the distinction between two of the most widely used survey methods by both academician and industry experts.

The sole aim of this tutorial is to teach you how to assess common method bias using Harman’s one-factor test for your study especially when the same measurement instrument is used to collect data for both dependent and independent variables.

P-value is also known as probability value and it ranges from 0 to 1. The interpretation of a p-value varies depending on what one is studying.