In this video we discuss what are data sets, the different types of data sets and the organization of data sets.



Transcript/notes
In statistics there are 2 main types of data sets, populations and samples.

A population is a complete set of all individuals in a study, or all measurements, counts, outcomes or responses which are of interest.

A sample is a subset or a part of a population.

So, for example, let’s say you were to take a survey of 343 women in the United States and asked them if they regularly order items online, and 194 said yes, and 149 said no. The population would be the responses of all women in the United states, and the sample would be the responses of the 343 women you surveyed.

There are 2 important terms in regards to populations and samples, a parameter and a statistic.

A parameter is a characteristic of a population and a statistic is a characteristic of a sample.

For instance if I said the average salary of a professional linebacker in the NFL is $7,000,000 per year, this would be a parameter, because this is based on all of the linebackers in the NFL, the entire population.

If I said I did a random check of 428 math teachers and found the average salary of a math teacher in the united states is $57,000, this would be a statistic, because this is based on a subset or a sample of all the math teachers in the united states.

Timestamps
0:00 What is a population?
0:13 What is a sample?
0:42 What is a parameter and a statistic?

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