Probability, Samples, And Research Issues in Statistics

These flashcards cover key concepts in probability and statistics as outlined in the lecture notes, focusing on definitions and fundamental principles.

Probability

The proportion (or fraction) of times an event is likely to occur.

Inferential Statistics

Statistics that allow us to make inferences and test hypotheses about a population from a sample.

P-value

The probability of obtaining a result at least as extreme as the one observed in your sample, under the assumption that the null hypothesis is true.

Mutually Exclusive Events

Events that cannot occur together.

Addition Rule

The rule stating that the probability of either event A or event B occurring is the sum of the probabilities of each event.

Independent Events

Events whose occurrence or non-occurrence does not affect the occurrence of other events.

Central Limit Theorem

As sample size increases, the sampling distribution of the sample mean approaches a normal distribution.

Sampling Error

The difference between the sample statistic and the population parameter it estimates.

Confidence Interval

A range of values that is likely to contain the population parameter with a specified level of confidence.