A simple random sample of size n = 51 is obtained from a population that is skewed left with u = 67 and 0 = 5. Does the population need to be normally distributed for the sampling distribution of x over bar x to be approximately normally distributed? Why? What is the sampling distribution of x overbarx?
A simple random sample of size n = 51 is obtained from a population that is skewed left with u = 67 and 0 = 5. Does the population need to be normally distributed for the sampling distribution of x over bar x to be approximately normally distributed? Why? What is the sampling distribution of x overbarx?
A simple random sample of size n = 51 is obtained from a population that is skewed left with u = 67 and 0 = 5. Does the population need to be normally distributed for the sampling distribution of x over bar x to be approximately normally distributed? Why? What is the sampling distribution of x overbarx?
A simple random sample of size n = 51 is obtained from a population that is skewed left with u = 67 and 0 = 5. Does the population need to be normally distributed for the sampling distribution of x over bar x to be approximately normally distributed? Why? What is the sampling distribution of x overbarx?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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