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
In a normal distribution, approximately 76.4% of the data falls below a z score of 1.04. Therefore, the proportion of the distribution that corresponds to z scores greater than 1.04 is about 23.6%. This can be found using standard normal distribution tables or calculators.
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.
In a distribution of scores, statements that cannot be true include: a mean that is significantly higher than the maximum score, as this is mathematically impossible; a standard deviation of zero in a set of varied scores, which would imply no variability; and a negative score in a context where all scores are non-negative, such as test scores. Additionally, a distribution cannot have a mode that is greater than the maximum value present in the data set.
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.