z value=0.44
A z score of .5 corresponds to 19% of the data between the mean and z. P( 0 < z < .5) = .19
You Get The Mean
176
A z-score of 70 would cover 35 standard deviations away from the mean. Note though, that a z-score of just 2.5 already covers 99% of the data. A z-score of 70 is incredibly high, and so is either a mistake, or will cover 100% of the data without fail. If a data point lies outside this, it is definitely an outlier and probably an error.
A z-score is a means to compare rank from 2 different sets of data by converting the individual scores into a standard z-score. The formula to convert a value, X, to a z-score compute the following: find the difference of X and the mean of the date, then divide the result by the standard deviation of the data.
A z score of .5 corresponds to 19% of the data between the mean and z. P( 0 < z < .5) = .19
The value is 0.3055
z = ±0.44
It is 84.3%
Your beacon score is basically an equifax branded FICO score, there is no difference except that a beacon score uses data found in your equifax credit report only. So if data furnishers do not report to equifax it will not appear on their credit report and thus this information will not be reflected in your beacon score.
No; since you refer to a math score (and not a math grade), it is ratio data.
You Get The Mean
Percent deviation formula is very useful in determining how accurate the data collected by research really is. Percent Deviation = (student data-lab data) / lab data then multiplied by 100 Note: If the percent deviation is a negative number that means the student data is lower than the lab value.
Yes.
It is .121
No.
Data consists of raw facts and figures. When that data is processed into sets according to context, it provides information.For example, recording the temperature of your classroom continuously over a set period is data collection. From that data information may be derived, such as the highest, lowest, and average temperatures over that period.A computer follows instructions (a 'program') in order to process 'data' into 'information', and can make possible the processing of vastly greater amounts of data that can be achieved efficiently otherwise.I'll give you an example,Data: Each student's test score is a piece of data.Information: The class' average score or the school's average score is the information that can be concluded from the given data.