Z = 1.25 How to use this Z Score to Calculate Result? In this problem, the population (number of students) doesn’t matter at all. σ is the standard deviation (SD) for the average of a sample from a population “n” = 12.To solve this problem, we can calculate the Z-score for the given data with the help of the formula mentioned above. Calculate the probable percentage of students who scored higher than 85. Problem: Let’s say the test score of students in an examination has a mean of 70 with a standard deviation of 12. Here is a solved example to help you understand the concept of Z-score better: In case the number of elements in the set happens to be quite large, around 68% of the elements have a Z-score between -1 and 1, around 95% have a Z-score between -2 and 2, and around 99% have a Z-score between -3 and 3.Similarly, a Z-score equal to -2 indicates that the element in question is 2 standard deviations less than the mean. A Z-score equal to -1 signifies that the element in question is 1 standard deviation less than the mean.Similarly, a Z-score equal to 2 indicates that the element in question is 2 standard deviations greater than the mean. A Z-score equal to 1 signifies that the element in question is 1 standard deviation greater than the mean.A Z-score equal to zero indicates that the element is equal to the mean.A Z-score greater than zero indicates that the element is greater than the mean.A Z-score lesser than zero indicates that the element is less than the mean.σ is the standard deviation (SD) for the average of a sample from a population “n”.In this case, its Z-score can be calculated by subtracting the mean from X and dividing the result by the standard deviation, as: Let’s say X is a random variable from a normal distribution, with mean μ and standard deviation σ. The Z-score formula can be used to compare the results from a test to a so-called normal population. It can be used to calculate the area under the standard normal curve for any value between the mean (zero) and any Z-score. After this, a Z-table can be used to find percentages under the curve. Therefore, the normal curve is standardized and set to have a mean of zero and a standard deviation of one. As a result of these wide ranges, it can be extremely tricky and tough to analyze data. For example, the heights of human beings can range from eighteen inches to eight feet, and their weights can range from one pound to more than five hundred pounds. There is a different set of values associated with every set of data.
Z– score (also called a standard score) gives you an idea of how far from the mean a data point is. How to use this Z Score to Calculate Result?.
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