EDA MIDTERM Flashcards
Means possibility. A branch of mathematics that deals with the occurrence of a random event. The value is expressed from zero to one.
Probability
4 Key Probability Terms
Experiment, Outcome, Sample Space, Event
2 types of Event
Simple Event and Compound Event
process where specific results are obtained
Experiment
single result of a probability experiment
Outcome
set of all possible outcomes for a probability experiment
Sample Space
set of outcomes of a probability experiment; a subset of the sample space
Event
Rolling a pair of dice has a sample space of 36 outcomes [(1,1), (1,2),
(1,3), (1,4) …etc. or just simply 6 x 6). TRUE OR FALSE?
TRUE
one outcome (rolling 4 in one die)
simple event
two or more outcomes (rolling an even number on a die then getting a head in a toin coss)
Compound Event
3 MainTypes of Probability
Classical, Empirical, Subjective
each outcome in a sample space is equally likely to occur
Classical Probability
each outcome in a sample space is NOT equally likely to occur
Empirical Probability
an e d u c a t e d guess or estimate
Subjective Probability
Key rules in Probability T or F:
The probability of a n event is always between 0 and 1. No negative probabilities or
greater than 1.
TRUE
Key rules in Probability T or F: The sum of all outcomes in a sample space is always equal to 1.
TRUE
Key rules in Probability T or F: It is impossible for an event to occur, the probability of that event is 0.
TRUE
Key rules in Probability T or F: If the event is certain to occur, the probability is 1.
TRUE
Types of Probability Distribution
Discrete Probability Distribution and Continuous Probability Distribution
Types of Discrete Probability Distribution
Binomial, Poisson,Hypergeometric
Types of Continuous Probability Distribution
Normal and Exponential
is the number of successes that result from a hypergeometric
experiment.
hypergeometric random variable
The probability distribution of a hypergeometric random variable is called
a
Hypergeometric Distribution
is a process that uses sample statistics to test a claim about the value of a population parameter
Hypothesis Test
A verbal statement, or claim, about a
population parameter is called a
Statistical Hypothesis
is a statistical hypothesis that contains a
statement of equality such as ≤ ,=, or ≥ .
Null Hypothesis (Ho)
is the complement of the null
hypothesis. It is a statement that must be true if H0 is false and contains a statement of inequality such as >,≠ ,or <.
Alternative Hypothesis (Ha)
divides the nonrejection region from the rejection region.
Critical Value
occurs if the null hypothesis isrejected when it istrue and should not be rejected. The probability of a type Ierror occurring is α.
TYPE I ERROR
occurs if the null hypothesis isnot rejected when it isfalse and should be rejected. The probability of a type IIerror occurring is β .
TYPE II ERROR
No matter which hypothesis represents the claim,always begin the hypothesis test assuming that the null hypothesis is true. At the end of the test, one of two decisions will be made:
- Reject the null hypothesis
- Do not reject the null hypothesis
can be used when the population is normal and variance is known , or for any population when the sample size n is at least 30.
Z-TEST
will be used when the population is normal and variance is unknown , or for any population when the sample size n is less than 30.
T-TEST
for proportion is a statistical test for a
population proportion.
The z-test
means never having to say you are certain.
Statistics
Types of Estimates
Point and Interval Estimate
is a single value (statistics) used to estimate a population value (parameter).
Point Estimate
States the range within which a population parameter probably lies
Interval Estimate
symbolized by (1 – α) x 100%, where α is the
proportion in the tails of the distribution that is
outside the confidence interval
Confidence Level
symbolized by α = 1 – (confidence level), it is the
proportion in the tails of the distribution that is
outside the confidence interval
Level of Significance (a)
value of Z needed for constructing a
confidence interval
Critical Value
is a range of possible values for an
unknown parameter and is associated
with confidence level
(Point Estimate + Margin of Error)
Confidence Interval
is the mathematical estimation of the
number of subjects/units to be included in
a study
Sample Size Determination
