The distribution of exam grades for an introductory psychology class is negatively skewed with a mean of μ = 71.5 and a standard deviation of σ = 12. Using the Distributions tool, answer the questions that follow. Standard Normal Distribution Mean = 0.0 Standard Deviation = 1.0 -3-2-10123z.5000.50000.000 What is the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75? By the central limit theorem, the negatively skewed distribution approximate a normal distribution, and the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75 . What is the probability of selecting a random sample of n = 36 students with an average exam grade greater than 75?
The distribution of exam grades for an introductory psychology class is negatively skewed with a mean of μ = 71.5 and a standard deviation of σ = 12. Using the Distributions tool, answer the questions that follow. Standard Normal Distribution Mean = 0.0 Standard Deviation = 1.0 -3-2-10123z.5000.50000.000 What is the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75? By the central limit theorem, the negatively skewed distribution approximate a normal distribution, and the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75 . What is the probability of selecting a random sample of n = 36 students with an average exam grade greater than 75?
The distribution of exam grades for an introductory psychology class is negatively skewed with a mean of μ = 71.5 and a standard deviation of σ = 12. Using the Distributions tool, answer the questions that follow. Standard Normal Distribution Mean = 0.0 Standard Deviation = 1.0 -3-2-10123z.5000.50000.000 What is the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75? By the central limit theorem, the negatively skewed distribution approximate a normal distribution, and the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75 . What is the probability of selecting a random sample of n = 36 students with an average exam grade greater than 75?
The distribution of exam grades for an introductory psychology class is negatively skewed with a mean of μ = 71.5 and a standard deviation of σ = 12. Using the Distributions tool, answer the questions that follow.
Standard Normal Distribution
Mean = 0.0
Standard Deviation = 1.0
-3-2-10123z.5000.50000.000
What is the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75?
By the central limit theorem, the negatively skewed distribution approximate a normal distribution, and the probability of selecting a random sample of n = 9 students with an average exam grade greater than 75 .
What is the probability of selecting a random sample of n = 36 students with an average exam grade greater than 75?
By the central limit theorem, the negatively skewed distribution approximate a normal distribution, and the probability of selecting a random sample of n = 36 students with an average exam grade greater than 75 .
For a sample of n = 36 students, what is the probability that the average exam grade is between 70 and 75?
By the central limit theorem, the positively negatively distribution approximate a normal distribution, and the probability of selecting a random sample of n = 36 students with an average exam grade between 70 and 75 .
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.
