Z-scores and Normal Distribution (copy)

Normal Distribution

Theoretical distribution of population scores that is bell-shaped and symmetrical

Confidence Interval

Range of possible values for the true mean of a population, typically expressed with a certain level of confidence

Standard Scores

Transformed scores that designate how many standard deviation units a raw score is from the mean, often represented by z-scores

Skewness

Measure of lack of symmetry in a distribution, indicating whether the data is skewed left or right from its center point

Kurtosis

Describes the peakedness or tailedness of a distribution, providing information on the shape of the distribution curve

Z-score

Value that represents the number of standard deviations a data point is from the mean in a standard normal distribution

Sampling Distribution

Estimated distribution of sample means, with larger sample sizes expected to have normally distributed sampling distributions

Central Limit Theorem

States that with a large enough sample size, the sampling distribution of the sample mean will be normally distributed regardless of the shape of the original population distribution.