PROBABILITY & independent varaiable

PROBABILITY AND NON-PROBABILITY SAMPLING

Sampling can be a confusing concept for managers carrying out survey research projects. By knowing some basic information about survey sampling designs and how they differ, you can understand the advantages and disadvantages of various approaches.

The two main methods used in survey research are probability sampling and non-probability sampling. The big difference is that in probability sampling all persons have a chance of being selected, and results are more likely to accurately reflect the entire population. While it would always be nice to have a probability-based sample, other factors need to be considered (availability, cost, time, what you want to say about results). Some additional characteristics of the two methods are listed below.

Probability Sampling

·         You have a complete sampling frame. 

You have contact information for the entire population.

               You can select a random sample from your population

Since all persons (or “units”) have an equal chance of being selected for your survey, you can randomly select participants without missing entire portions of your audience.

·         You can generalize your results from a random sample.

With this data collection method and a decent response rate, you can extrapolate your results to the entire population.

·         Can be more expensive and time-consuming than convenience or purposive sampling.

Non-probability Sampling 

·         Used when there isn’t an exhaustive population list available.

Some units are unable to be selected, therefore you have no way of knowing the size and effect of sampling error (missed persons, unequal representation, etc.). 

·         Not random. 

·         Can be effective when trying to generate ideas and getting feedback

But you cannot generalize your results to an entire population with a high level of confidence. Quota samples (males and females, etc.) are an example.

·         More convenient and less costly

But doesn’t hold up to expectations of probability theory.

What is dependent and independent varaiable?

A Variable

A variable is an object, event, idea, feeling, time period, or any other type of category you are trying to measure. There are two types of variables-independent and dependent.

Independent variable

An independent variable is exactly what it sounds like. It is a variable that stands alone and isn't changed by the other variables you are trying to measure.

For example, someone's age might be an independent variable. Other factors (such as what they eat, how much they go to school, how much television they watch) aren't going to change a person's age. In fact, when you are looking for some kind of relationship between variables you are trying to see if the independent variable causes some kind of change in the other variables, or dependent variables.

Dependent variable

Just like an independent variable, a dependent variable is exactly what it sounds like. It is something that depends on other factors.

For example, a test score could be a dependent variable because it could change depending on several factors such as how much you studied, how much sleep you got the night before you took the test, or even how hungry you were when you took it. Usually when you are looking for a relationship between two things you are trying to find out what makes the dependent variable change the way it does.

Many people have trouble remembering which the independent variable is and which the dependent variable is. An easy way to remember is to insert the names of the two variables you are using in this sentence in the way that makes the most sense. Then you can figure out which is the independent variable and which is the dependent variable:

(Independent variable) causes a change in (Dependent Variable) and it isn't possible that (Dependent Variable) could cause a change in (Independent Variable).

For example:

(Time Spent Studying) causes a change in (Test Score) and it isn't possible that (Test Score) could cause a change in (Time Spent Studying).

We see that "Time Spent Studying" must be the independent variable and "Test Score" must be the dependent variable because the sentence doesn't make sense the other way around.