Use of the SAS Macro Language in Developing Control Chart Limits
... Macro REPEATER implements steps 2 to 5 of II. Notice that REPEATER will rerun until a stable set of data for the standard deviation is obtained or until the number of tries exceeds a user-defined bound (in this case, 20). When REPEATER finishes, it calls STABLEMN t which implements steps 6 and 7 of ...
... Macro REPEATER implements steps 2 to 5 of II. Notice that REPEATER will rerun until a stable set of data for the standard deviation is obtained or until the number of tries exceeds a user-defined bound (in this case, 20). When REPEATER finishes, it calls STABLEMN t which implements steps 6 and 7 of ...
Short Course on Data Analysis and Errors of Observation
... Errors = Random Errors + Systematic Errors How to minimize RE and SE: (a) RE – by taking MORE measurements! (b) SE – by SPOTTING! Precision Accuracy ...
... Errors = Random Errors + Systematic Errors How to minimize RE and SE: (a) RE – by taking MORE measurements! (b) SE – by SPOTTING! Precision Accuracy ...
Central Tendency and Variability
... – Good if you need to know most frequent observation – Quick and easy ...
... – Good if you need to know most frequent observation – Quick and easy ...
Final exam Review (retesting for the last two tests – Statistics)
... 11. In a normal distribution, the mean weight of 12-year old children is 85 pounds the standard deviation is 4 pounds. What weight is exactly 1 SD above the mean? Below the mean? What weight is exactly 2 SD above the mean? Below the mean? What percent of the children weigh less than 77 pounds? What ...
... 11. In a normal distribution, the mean weight of 12-year old children is 85 pounds the standard deviation is 4 pounds. What weight is exactly 1 SD above the mean? Below the mean? What weight is exactly 2 SD above the mean? Below the mean? What percent of the children weigh less than 77 pounds? What ...
Statistics
... statistics: summarize data so they can easily be comprehended. Frequency distribution (f) and percentages are descriptive statistics. ...
... statistics: summarize data so they can easily be comprehended. Frequency distribution (f) and percentages are descriptive statistics. ...
Chapter 7
... to this situation (and to others, such as the contingency table problem of Example 6.C). 7.1. The Multinomial Distribution. The multinomial distribution is, as its name suggests, a generalization of the binomial. Suppose an experiment may be viewed as consisting of n independent trials, where in eac ...
... to this situation (and to others, such as the contingency table problem of Example 6.C). 7.1. The Multinomial Distribution. The multinomial distribution is, as its name suggests, a generalization of the binomial. Suppose an experiment may be viewed as consisting of n independent trials, where in eac ...
Section 6-1
... A continuous random variable Y has infinitely many possible values. All continuous probability models assign probability 0 to every individual outcome. Only intervals of values have positive probability. ...
... A continuous random variable Y has infinitely many possible values. All continuous probability models assign probability 0 to every individual outcome. Only intervals of values have positive probability. ...
inference_steps - the Department of Statistics Online Learning!
... true mean GPA difference between males and females” or “Estimate the true mean GPA difference between males and females” we would calculate a confidence interval. However, if the question states a current parameter exists and we disagree with this value or we want to demonstrate statistically that t ...
... true mean GPA difference between males and females” or “Estimate the true mean GPA difference between males and females” we would calculate a confidence interval. However, if the question states a current parameter exists and we disagree with this value or we want to demonstrate statistically that t ...
Lesson3 - Ka
... that the student has only a stereo, only a TV, and both a stereo and TV? P(student has a stereo) = 320/500 = .64. P(student has a TV) = 175/500 = .35. P(student has both a stereo and TV) = 100/500 = .20. P(student as only a stereo) = 220/500 = .44. P(student has only a TV) = 75/500 = .15. P(student ...
... that the student has only a stereo, only a TV, and both a stereo and TV? P(student has a stereo) = 320/500 = .64. P(student has a TV) = 175/500 = .35. P(student has both a stereo and TV) = 100/500 = .20. P(student as only a stereo) = 220/500 = .44. P(student has only a TV) = 75/500 = .15. P(student ...
V. Tail Behaviors of the Models
... event is by risk, which is the expected impact by definition. However, considerable computation would be needed to find out the impact. Another way to prioritize is by event probability, assuming the impacts of events are of about the same magnitude. The event with highest possibility will be “compu ...
... event is by risk, which is the expected impact by definition. However, considerable computation would be needed to find out the impact. Another way to prioritize is by event probability, assuming the impacts of events are of about the same magnitude. The event with highest possibility will be “compu ...