Descriptive statistics involve summarizing and describing a set of data, while inferential statistics involve making predictions or inferences about a larger population based on a sample of data.
The Central Limit Theorem states that as the sample size increases, the distribution of sample means will approach a normal distribution, regardless of the population's underlying distribution. This allows for the use of statistical methods that assume a normal distribution, even if the data is not normally distributed.
A parameter is a numerical value that describes a population, while a statistic is a numerical value that describes a sample from that population. Parameters are often unknown and estimated using statistics.
Hypothesis testing is used to determine whether a certain assumption or claim about a population is supported by the data. It involves comparing a sample statistic to a hypothesized value and determining the likelihood of obtaining that result if the null hypothesis (no difference or no effect) is true.
Regression analysis is a statistical method used to identify and quantify the relationship between one or more predictor variables and a response variable. It can be used for prediction, understanding the relationship between variables, and identifying influential factors.