Yes.
Consider the values 0,1,1,1,1,1,1,1,1,1
The mean is 0.9
9 out of 10 values are higher than this mean, which is obviously more than 50%.
0.2533
If most the population has many high scores, the distribution is negatively skewed. If most have many low scores, it is positively skewed
Variance
True or False, One major advantage of transforming X values into z-scores is that the z-scores always form a normal distribution
2
To find the proportion of a normal distribution corresponding to z-scores greater than +1.04, you can use the standard normal distribution table or a calculator. The area to the left of z = 1.04 is approximately 0.8508. Therefore, the proportion of the distribution that corresponds to z-scores greater than +1.04 is 1 - 0.8508, which is approximately 0.1492, or 14.92%.
-1.28
It is 68.3%
Scores on the SAT form a normal distribution with a mean of µ = 500 with σ = 100. What is the probability that a randomly selected college applicant will have a score greater than 640?
0.13
0.2533
The mean of a distribution of scores is the average.
true
50% to 100%.
A Z score of 300 is an extremely large number as the z scores very rarely fall above 4 or below -4. About 0 percent of the scores fall above a z score of 300.
It is not possible to convert a raw score into a percentile without knowing the distribution of scores and key parameters of the distribution. Since none of this information is provided, it is not possible to give a sensible answer.
To determine the percentage of scores between 61 and 82, you would need to know the distribution of the scores (e.g., normal distribution) and the total number of scores. If the data is normally distributed, you can use the mean and standard deviation to find the percentage of scores in that range using a z-score table. Without specific data, it isn't possible to provide an exact percentage.