Because there are so many things that happen - some predictably, some coincidentally - that all fall into the category of random "chance" - it's this way one time, that way the next. Statistics are carefully calculated to have a cut-off point, below which is considered to be within the category of "random". Above that figure, it is more frequent than "random" can explain. At that point, it becomes - to a greater or lesser degree - "statistically significant". A simplistic example: If a child has a school year 180 days long, and the child is "home sick" seven out of those 180 days, that is within the realm of random. If the child is "home sick" 57 of those 180 days, that is "statistically significant".
what is the significance of statistical investigation to management information?
Because it allows us to recognize that inference is not perfect and no matter how much confidence we have in the outcome, there is always a chance we may be wrong.
look for a paper being published in "The Oncologist" later this year (2008)
The level of significance; that is the probability that a statistical test will give a false positive error.
Standard deviation of 0 can only be attained if all observations are identical. That is, the variable in question has just one possible value so statistical considerations are irrelevant.
what is the significance of statistical investigation to management information?
It represents unity.
Statistical significance means that you are sure that the statistic is reliable. It is very possible that whatever you conclusion or finding is, it may not be important or it not have any decision-making utility. For example, my diet program has a 1 oz weight loss per month and I can show that is statistically significant. Do you really want a diet like that? It is not practically significant
Binomial distribution is the basis for the binomial test of statistical significance. It is frequently used to model the number of successes in a sequence of yes or no experiments.
Because it allows us to recognize that inference is not perfect and no matter how much confidence we have in the outcome, there is always a chance we may be wrong.
There is no statistical significance in the result.
levels of variables important in statistical analysis?
look for a paper being published in "The Oncologist" later this year (2008)
Statistical significance refers to when a statistical assessment of observations reveals a pattern rather than random chance. In simpler terms it means when well observing or recording a set of data you recognize that somethings happens all or most of the time rather than by random.
The level of significance; that is the probability that a statistical test will give a false positive error.
If the outcome is below or equal to 0.05, then it is statistically significant; above is not.
statistical significance