The z-score is a measure of how many standard deviations a data point is from the mean, calculated by subtracting the mean from the data point and then dividing the result by the standard deviation
The standard normal distribution is a bell-shaped curve with a mean of 0 and a standard deviation of 1, used to model various data types like heights, weights, and test scores
For the normal distribution, the mean (μ) represents central tendency, while dispersion is measured by σ, σ2, standard error, and the 95% confidence interval
The z-score is a measure of how many standard deviations a data point is away from the mean, calculated by subtracting the mean from the data point and then dividing the result by the standard deviation
The standard normal distribution is a bell-shaped curve with a mean of 0 and a standard deviation of 1, used to model various types of data like heights, weights, and test scores
A normal deviate tells how many standard deviations a data point is from the mean, aiding in finding the probability of a data point falling within a given range of values
The standard normal distribution is a bell-shaped curve with a mean of 0 and a standard deviation of 1, used to model various data like heights, weights, and test scores
The table of the standard normal distribution shows the proportion of a normal distribution beyond a given normal deviate, aiding in finding the probability of a data point falling within a specific range of values