What is the difference between statistics and parameter

Parameter and Statistics might look like similar terms but they are different from each other. A parameter is a numerical value obtained from a population while the statistics is a numerical value obtained from the sample. A parameter takes each and every person involved in an entire population into consideration whereas the statistics includes the data it receives from a selected sample without including the entire population.

The difference between Parameter and Statistic is that a parameter is a value used to summarize data for an entire population whereas statistics is a value used to summarize data from a sample which is a subset of the entire population.

A parameter is a value that describes the characteristics of the entire population. It is nearly impossible to determine the parameter, especially in case of a large population. A parameter can be easily determined for a very small population where every individual can be located with complete certainty.

It becomes easy to calculate a parameter if all individuals can be located and measured without missing a single individual. A few examples include the following: Product reviews on online stores are statistics. The data provided via product reviews reflect the opinions of those who take the time to log in and leave feedback, which is a sample of the full population of people who purchased the product.

Studies that report what percentage of people find the news media to be trustworthy are providing statistics. This information is based on data collected from a sample of people who answered a survey or participated in a research study, not everyone in the population.

Health studies that report what percentage of the population in a certain geographic region is overweight or has certain medical conditions are providing statistics. This information is based on data collected from survey respondents or study participants. It would not be possible for a researcher to obtain weight or health history for every person in a geographic area.

Political poll results that indicate how many points a certain candidate is leading by represent a statistic. This data point is based on a group of people who responded to a survey, not every registered voter or every person who intends to vote.

Parameter vs. A statistic describes a sample that was taken to estimate for the population; thus, a sample is an estimate for a particular parameter. It varies because the samples vary, thus it is unlikely to get the exact same statistic for more than one sample although the statistics should be relatively close.

Note: It is unnecessary to find a statistic if the parameter is known or if the population is small enough that the parameter can be found.

Identifying a parameter or a statistic:. You get sample statistics when you collect a sample and calculate the standard deviation and the mean. You can use sample statistics to make certain conclusions about an entire population, thanks to inferential statistics.

But, it would help if you had particular sampling techniques to draw valid conclusions. Using these techniques ensures that samples deliver unbiased estimates — correct on average.

To estimate population parameters in inferential statistics, you use sample statistics. For instance, if you collect a random sample of female teenagers in the U. You can use the sample mean as an unbiased estimate of the population mean.

You can calculate the standard deviation as the square root of the variance. The variance, on the other hand, is the average of the squared differences from the mean.