z =0 and P(X< x) = 0.5 Explanation: z = (x-xbar)/sd, where xbar is the estimated mean or average of the sample, sd is the standard deviation, and x is the value of the particular outcome. We change x to z so that we can use the normal distribution or t-tables tables, which are based on a zero mean and 1 standard deviation. For example: What is the probability that the mean value of the distribution is 5 or less, given the sample average is 5 and the sd is 2? The z-score would be (5-5)/2 which is equal to 0. The probability, if we assume the normal or t-distribution, is 0.50. (see normal distribution tables) I hope this makes sense to you. The normal distribution is symmetrical. Per the example, a sample average of 5 tells you there is equal chance of the population mean being above and below 5.
No.
No. But there can be more than one data point which has the same value as the mean for the set of numbers. Or there can be none that take the mean value.
The minimum data value in a data set is simply the lowest value of the set (easily found by arranging the set from lowest-highest values in an excel sheet or by hand).
false
50
You Get The Mean
When the data set consistys of a single value.
A modal score is the value that appears most frequently in a data set. It is a measure of central tendency, like the mean and median, but specifically identifies the mode among the values. In some cases, a data set may have more than one modal score if multiple values occur with the same highest frequency, making it multimodal. If no value repeats, the data set is considered to have no mode.
Every unique value has a unique distance from the mean, which leads to a unique z-score.
The least value of the data set is called the minimum.
Yes.
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To calculate the z-score, you need the mean and standard deviation of the data set, as well as the value for which you want to find the z-score. The formula for the z-score is ( z = \frac{(X - \mu)}{\sigma} ), where ( X ) is the value, ( \mu ) is the mean, and ( \sigma ) is the standard deviation. Without specific values for these parameters, I can't provide a numerical answer. Please provide the necessary data for further assistance.
No.
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No, the mean cannot be greater than the greatest value in a data set. The mean is calculated by summing all the values and dividing by the number of values, which means it will always fall within the range of the data set. Therefore, the mean will always be less than or equal to the maximum value.
It is a measure of the spread of the data around its mean value.