The 'population' is the entire collection of individuals that we are interested in studying. It is typically impossible or difficult to observe/test each member of the population totally. So we choose a subset containing the characteristics of a large population, called a 'sample', to study.
Descriptive statistics and Inferential statistics
When it comes to statistic analysis, there are two classifications: descriptive statistics and inferential statistics.
Both descriptive and inferential statistics rely on the same set of data.
Descriptive statistics is solely concerned with properties of the observed data, and does not assume that the data came from a larger population. When descriptive statistics are applied to populations, and the properties of populations, like the mean or standard deviation, are called parameters as they represent the whole population. Descriptive statistics are limited in so much that they only allow you to make summations about the people or objects that you have actually measured. You cannot use the data you have collected to generalize to other people or objects.
When examination of each member of an entire population is not convenient or possible, inferential statistics are valuable.
Inferential statistics does start with a sample and then generalizes to a population. Inferential statistics use a random sample of data taken from a population to describe and make generalizations about the population. Inferential statistics are based on the assumption that sampling is random. However, inferential statistics arise out of the fact that sampling naturally incurs sampling error and thus a sample is not expected to perfectly represent the population. There are two main areas of inferential statistics:
1. The estimation of parameter. This means taking a statistic from sample data and using it to explain something about the population. This is expressed in terms of an interval and degree of confidence that the parameter is within the data.
2. Testing of significance or hypothesis testing. This is where you use a statistical sample to answer research questions. However, there is some uncertainty in this process and can be expressed in terms of a level of significance.
Please read more explanation as this link https://www.thoughtco.com/differences-in-descriptive-and-inferential-statistics-3126224
No comments:
Post a Comment