All Flashcards
What is the definition of Normal Distribution?
A symmetrical, unimodal, continuous probability distribution where Mean = Median = Mode.
What is the definition of Mean (μ)?
The arithmetic average of the data; the center of the normal distribution.
What is the definition of Standard Deviation (σ)?
A measure of the dispersion or spread of data around the mean in a normal distribution.
What is the definition of Z-score?
The number of standard deviations a data point is from the mean.
What is the definition of Percentile?
The percentage of data that falls below a certain value.
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.
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.