Assuming a normal distribution, the proportion falling between the mean (of 8) and 7 with standard deviation 2 is:
z = (7 - 8) / 2 = -0.5 → 0.1915 (from normal distribution tables)
→ less than 7 is 0.5 - 0.1915 = 0.3085 = 0.3085 x 100 % = 30.85 %
(Note: the 0.5 in the second sum is because half (0.5) of a normal distribution is less than the mean, not because 7 is half a standard deviation away from the mean, and the tables give the proportion of the normal distribution between the mean and the number of standard deviations from the mean.)
T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
In a normal distribution, approximately 68% of scores fall within one standard deviation of the mean (between -1 and +1 standard deviations). About 95% of scores fall within two standard deviations (between -2 and +2 standard deviations). Therefore, the percentage of scores that falls specifically between the mean and -2 to 2 standard deviations is about 95% minus the 50% that is below the mean, resulting in approximately 45%.
In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean. This means that around 34% of the data lies between the mean and one standard deviation above it, while another 34% lies between the mean and one standard deviation below it.
In a normal distribution, approximately 68% of the population falls within one standard deviation of the mean, and about 95% falls within two standard deviations. Therefore, to find the percentage of the population between one standard deviation below the mean and two standard deviations above the mean, you would calculate 95% (within two standard deviations) minus 34% (the portion below one standard deviation), resulting in approximately 61% of the population.
A single number, such as 478912, always has a standard deviation of 0.
T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
In a normal distribution, approximately 68% of scores fall within one standard deviation of the mean (between -1 and +1 standard deviations). About 95% of scores fall within two standard deviations (between -2 and +2 standard deviations). Therefore, the percentage of scores that falls specifically between the mean and -2 to 2 standard deviations is about 95% minus the 50% that is below the mean, resulting in approximately 45%.
In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean. This means that around 34% of the data lies between the mean and one standard deviation above it, while another 34% lies between the mean and one standard deviation below it.
The area between the mean and 1 standard deviation above or below the mean is about 0.3413 or 34.13%
X = 50 => Z = (50 - 70)/12 = -20/12 = -1.33 So prob(X < 50) = Prob(Z < -1.33...) = 0.091
In a normal distribution, approximately 68% of the population falls within one standard deviation of the mean, and about 95% falls within two standard deviations. Therefore, to find the percentage of the population between one standard deviation below the mean and two standard deviations above the mean, you would calculate 95% (within two standard deviations) minus 34% (the portion below one standard deviation), resulting in approximately 61% of the population.
There must be a formula, but in the mean time there is a handy site that does it for you. [See related link below for the converter]
A single number, such as 478912, always has a standard deviation of 0.
Standard deviation calculation is somewhat difficult.Please refer to the site below for more info
A single number, such as 478912, always has a standard deviation of 0.
There are approximately 16.4% of students who score below 66 on the exam.
z=-20/12 = -1.667 Assuming normal distribution, P(Z < -1.667) = 0.04779 or 4.8% of the scores should be less than 50. You can get the probabilities by looking them up on a table or use Excel, where +Normdist(50,70,12,true). My normal table has only 2 digit accuracy so for -1.67 = 0.0475.