järeldusstatistikat

Järeldusstatistikat is the Estonian term for inferential statistics. It is a branch of statistics that involves using sample data to make generalizations, predictions, or inferences about a larger population. Unlike descriptive statistics, which summarizes and describes the characteristics of a dataset, inferential statistics goes beyond the observed data to draw conclusions about the underlying population from which the sample was drawn.

The primary goal of järeldusstatistikat is to determine the probability that an observed effect or relationship in a sample is likely to be true for the entire population. This involves concepts such as hypothesis testing, confidence intervals, and regression analysis. Hypothesis testing is used to test a specific claim or assumption about a population. Confidence intervals provide a range of values within which a population parameter is likely to lie, with a certain level of confidence. Regression analysis helps to understand the relationship between variables and predict future outcomes.

The validity of inferences made through järeldusstatistikat depends heavily on the sampling method used. Random sampling is crucial to ensure that the sample is representative of the population. Common techniques include random sampling, stratified sampling, and cluster sampling. Errors can arise from sampling bias or random sampling error, which are accounted for through statistical methods. Järeldusstatistikat is widely applied in various fields, including medicine, social sciences, economics, and engineering, to make informed decisions based on data.