Karteikarten: Fundamentals of Probability and Statistics — 18 Karten

Sample data variability — definition?

Natural differences observed in collected data.

Variability in sample data — meaning?

Extent of data points' differences from the mean.

Sources of variability — examples?

Measurement errors, natural fluctuations, population differences.

Probability of an event — role?

Quantifies likelihood of occurrence.

Probability rules — bounds?

Between 0 and 1, inclusive.

Event probability — complement?

1 minus the probability of the event.

Random variable — definition?

Numerical outcome of a random experiment.

Distribution of a variable — purpose?

Describes likelihood of each possible value.

Expected value — meaning?

Long-term average of the random variable.

Variance — what?

Measure of data spread around the mean.

Poisson distribution — models?

Number of rare events in a fixed interval.

Binomial distribution — models?

Number of successes in fixed trials.

Normal distribution — shape?

Bell-shaped, symmetric around mean.

Other distributions — examples?

Exponential, uniform, skewed distributions.

Conditional probability — formula?

P(A|B) = P(A∩B)/P(B).

Independence — condition?

P(A∩B) = P(A)×P(B).

Correlation — measure?

Strength and direction of linear relationship.

Statistical inference — purpose?

Estimate population parameters from samples.