Ch 7: Probability Flashcards
What is Probability?
The likelihood of an event occurring, expressed as a number between 0 and 1; a number that describes the likelihood of some event occurring, which ranges from zero (impossibility) to one (certainty); the expected relative frequency of a particular outcome
What is Sample Space?
The set of all possible outcomes for an event or experiment; We represent these by listing them within a set of squiggly brackets; examples: * For rain is {rain, not rain}
* For a coin flip, the sample space is {heads, tails}.
* For a six-sided die, the sample space is each of the
possible numbers that can appear: {1,2,3,4,5,6}.
What is an Event or Outcome?
A specific outcome or set of outcomes within the sample space; a subset of the sample space to examine specific probability;
What is Relative Frequency?
The number of times an event occurs divided by the total number of possible occurrences; the number of times an event takes place relative to the number of times it could have taken place.
What is the Law of Large Numbers?
The principle that empirical probability approaches true probability as sample size increases; shows that the empirical probability will approach the true probability as the sample size increases
What are Independent Events?
Events where the outcome of one does not affect the probability of the other.
What is Random Sampling?
Selection method where each member of the population has an equal chance of being chosen; one method that may
ensure representativeness of a sample; a researcher starts with a complete list of the population (sometimes referred to as a sampling frame) and randomly selects some of them to an experiment
What is a Probability Distribution?
Description of the probability of all possible outcomes in an experiment; describes the probability of all of the
possible outcomes in an activity
What is Cumulative Probability Distribution?
The probability of obtaining a value as extreme or more extreme than a specific value; tells us the probability of a value as large or larger (or as small or smaller) than some specific value
What is an Odds Ratio?
A measure comparing the relative likelihood of two different probabilities; is an example of what we
will later call an effect size, which is a way of quantifying how
relatively large any particular statistical effect is.
What is Probability Theory?
the branch of mathematics that deals
with chance and uncertainty; it provides us with the
mathematical tools to describe uncertain events.
Probability Formula:
Probability = Number of favorable (desired) outcomes / Total number of possible outcomes
P(A) = Number of favorable outcomes to A / Total number of outcomes
Features that a value has to have if it is going to be a probability:
- Probability cannot be negative.
- The total probability of all outcomes in the sample space is
1; that is, if we take the probability of each event and add
them up, they must sum to 1. This is interpreted as saying
“Take all of the possible events and add up their
probabilities. These must sum to one.” - The probability of any individual event cannot be greater
than one. This is implied by the previous point; since they
must sum to one, and they can’t be negative, then any
particular probability cannot exceed one.
What is the Standard Normal Distribution Table?
Where The probability of randomly getting one of those z-scores in the specified region can then be found; also known as the z-table; . The table also only presents the area in the body because the total area under the normal curve is always equal to 1.00
What two elements must be ensured to have probability be consistent and accurate?
- Every person in the population has an equal chance of
being selected - Sampling occurs with replacement
What is sampling with replacement?
In order for the total number of outcomes to remain constant; as one person is selected, another person must be added to keep the total number of possible outcomes the same; which equals to the full definition of random sampling`
What is Statistical Independence?
between two variables means that knowing the value of one variable doesn’t tell us anything about the value of the other; an be expressed as: P(A|B)=P(A); the probability of A given
some value of B is just the same as the overall probability of
A (because they are independent)
