Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
29 Cards in this Set
- Front
- Back
Parameter
|
A numerical value based on the population
|
|
Statistic
|
A numerical value based on the sample
|
|
Outlier
|
A data value that is an extreme value
|
|
Resistance Measure
|
a measure that is not affected by outliers
|
|
The Median is a __________ measure
|
Resistance
|
|
Location formula for Percentiles
|
The mth percentile, written Pm is loacted with the formula:
(m/100) * (n+1) if not an integer continue with: [location integer] + [decimal * distance between integer and next position] |
|
Outlier Detection Formula
|
Q1 - 1.5 (IQR)
Q3 + 1.5 (IQR) |
|
Convexity Law
|
The probability of any event must be between 0 and 1
0 < P(Ei )< 1 |
|
The total sum of all probabilities for n mutually exclusive outcomes is __.
|
1
P(E1) + P(E2) + . . . + P(En) |
|
For any two events A and B:
P(A or B)= |
P(A) + P(B) - P(A and B)
|
|
The Multiplication Rule
|
For any two events A and B:
P(A and B) = P(A|B) P(A) = P(A|B) P(B) |
|
The Multiplication for independent events
|
P(A and B) = P(A) * P(B)
|
|
3 Types of probability
|
1) Marginal
2) Conditional 3) Joint |
|
Disease Diagnostics:
|
1) Symptoms
2) Signs 3) Disgnostic Tests |
|
The accuracy of an examinatino is affected by two factors:
|
1) Reproducability
2) Validity |
|
Experiment
|
A process in which the outcome cannot be predicted ahead of time
|
|
Sample Space
|
S = A collection of all possible outcomes
|
|
Event
|
E = A subset of the sample space
|
|
Equally Likely Events
|
each outcome has the same chance of occuring
|
|
Random Variable
|
When the value of a variable is obtained as the result of a chance factor.
A variable is a random variable if the exact value of the variable can not be predicted in advance. |
|
Discrete Random Variable
|
When the variable can only assume specific values
|
|
Continuous Random Variable
|
When the variable can theoretically assume any value on a given interval
|
|
Probability Density Function
(pdf) |
Describes the distribution of a continuous random variable
|
|
Probabiliy Mass Function (pmf)
|
Describes the distribution of a discrete random variable
|
|
Bernoulli Trial
|
When a random process or experiment results in one of only two mutually exclusive outcomes
|
|
Bernoulli Process
|
a sequence of Bernoulli Trials such that:
1) Each trial has only two mutually exclusive outcomes, one a success, the other a failure. 2) The prob. of a success p, remains constant from trial to trial, the prob. of failure is denoted as q. 3) Trials are independent |
|
Binomial Distribution
|
If the random variable x is defined to count the number of successes and our experiment is a Bernoulli Process, the resulting distribution is Binomial
|
|
The Poisson Distribution
|
Describes the number of events that will occur in a specified time, area or volume
|
|
Characteristics of a Poisson Distribution
|
1) Experiment consists of counting the number of times a certain event occurs in a specific time, area or volume
2) The prob. of any even tis the same for all units 3) The number of events that occur in one unit of time, area or volume is independent of the number of events that occur in other units 4) The mean of each unit is known and is denoted by Lambda. |