Let's say you have two regular fair dice (six-sided, of course). If you throw them 360 times and keep track of the numbers you throw, you'll record a seven about 60 times. So, you could say that the ratio of all possible numbers (including sevens) to sevens to is 360 to 36 (360:60), which is the same as 6 to 1 (6:1). You could also say that the ratio of all OTHER numbers (excluding sevens) to sevens to is 300:60, or 5:1.
(there is no seven on a six sided die....)
You would have also recorded about 50 occurrences of sixes, so you could say that the ratio of sevens to sixes is 60 to 50, or 6 to 5 (6:5). Obviously, the ratio of sixes to sevens would be 5:6.
How about this:
Let's say that the probability that a certain type of rare snake will have male offspring is 0.4. Obviously, the probability of the snake's having female offspring is 0.6. If the snake has lots of offspring, the ratio of males to females will be 0.4 to 0.6, which is the same as 4 to 6, which is the same as 2 to 3 (2:3). Stated another way, for every five snakes born, two will be male, and three will be female.
By the way, whenever possible, it's a good idea to express ratios as close as you can to whole numbers, like 3:2 or 7:5. Also, whenever one of the digits is a one, it's particularly useful, like 3:1 or 9:1, or even 1.5:1. That last ratio, 1.5:1, is equal to 3:2. It depends on what you're more comfortable with.
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With probability ratios the value you get to describe the strength of the relationship when you compare (A given B) to (A given not B) is not the same as what you get when you compare (not A given B) to (not A given not B). This is, IMHO, a big problem. There is no such problem with odds ratios.
Probability is used in genetics to determine the possibilities of offspring having a particular trait
The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.
Larger t-ratios indicate a greater difference between the sample mean and the null hypothesis mean relative to the variability in the data. This suggests that the observed effect is less likely to be due to random chance. As a result, larger t-ratios are more likely to exceed the critical value for significance, leading to a higher probability of rejecting the null hypothesis. Thus, they often indicate stronger evidence against the null hypothesis.
No 1.001 is not a probability. Probability can not be >1