All Flashcards
What are the differences between Z-scores and Percentiles?
Z-score: Measures standard deviations from the mean. | Percentile: Percentage of data below a value.
What are the differences between using the Large Counts Condition and the Central Limit Theorem to check for normality?
Large Counts Condition: Used for categorical data (proportions). | Central Limit Theorem: Used for quantitative data (means) with a sample size of at least 30.
What is the formula for calculating a Z-score?
What is the formula for calculating the z-score, given a data point (x), a mean (μ), and a standard deviation (σ)?
Explain the concept of the Empirical Rule.
68% of data falls within 1 standard deviation, 95% within 2, and 99.7% within 3 standard deviations of the mean.
Explain the concept of the Central Limit Theorem (CLT) in the context of normality.
If the sample size is at least 30, the sampling distribution of the mean will be approximately normal, regardless of the population's distribution.
Explain the concept of a positive Z-score.
A positive z-score indicates that the data point is above the mean.
Explain the concept of a negative Z-score.
A negative z-score indicates that the data point is below the mean.
Explain how the mean and standard deviation describe a normal model.
The mean (μ) defines the center, and the standard deviation (σ) defines the spread of the symmetrical bell curve.