3 kinds of non-stop possibility distributions - ANS-The everyday probability
distribution...Facts have a tendency to fall into the center of the distribution and while very
excessive and very low values are pretty rare
The exponential distribution... Lower values generally tend to dominate and better values
don't arise very frequently. EX. Time among arrivals at a toll sales space. Lower instances
occur more often
The uniform distribution...All the values have the same hazard of happening
benefits/negative aspects to the usage of specific measures of valuable tendency -
ANS-Mean:
Simple to calculate
Summarizes the statistics with a unmarried value
With only a precis fee you lose information about the unique facts
Sensitive to outliers
median:
no longer stricken by excessive values
requires extra attempt to decide
mode:
can be used with express records
might not exist in some units
may additionally have multiple modes
advantages/hazards to the usage of unique measures of variability - ANS-range:
Easy to calculate and understand
Only primarily based on two numbers in the information set
(Ignores the manner in which data are disbursed)
Sensitive to outliers:
baye's theorem - ANS-expand a rule to calculate P(A facts approximately A)
biased samples - ANS-non-consultant pattern
-can result in distorted findings
-can occur deliberately or by accident
-consequences can be manipulated by how we ask questions and who is responding to
them
binomial chance distribution - ANS-summarizes the chance that a fee will take one among
impartial values underneath a given set of parameters or assumptions.
, The two impartial values, denoted by 'x', is 1) success, or 2) failure, and they're mutually
one-of-a-kind.
Residences:
1. The test consists of a series of n equal trials.
2. Two results, achievement and failure, are possible on each trial
three. The possibility of a fulfillment, denoted through p, does no longer trade from trial to
trial. This manner the probability of failure also does not exchange
four. The trials are unbiased
binomial random variable - ANS-binomial random variable X is described as the variety of
successes performed within the n trials of a Bernoulli manner. A binomial distribution
indicates the possibilities related to the possible values of X.
Coefficient of variant - ANS-measures the usual deviation in phrases of its percentage of the
suggest
A excessive CV suggests excessive variability relative to the size of the imply
A low CV indicates low variability relative to the size of the mean. More consistency.
Regularly used for investments. Lower CV=better
conditional probability - ANS-the possibility of Event A occurring, given the situation that
Event B has occurred
is also known as a posterior probability, that's a revision of the earlier possibility the use of
extra statistics
contengency/crosstabulation tables - ANS-offer a layout to display observations which have
multiple fee associated with them
Use rows and columns for separate variables to summarize the records correctly
may be used to show the wide variety of occurrences of occasions that are labeled
consistent with categorical variables. Used in probability
do that by using PIVOT TABLE on Excel
non-stop statistics - ANS-values that could tackle any real numbers, such as numbers that
include decimal factors
typically measured instead of counted
Examples are weight, time, and distance
Time required to examine chapter 2
Thickness of paint carried out to a car body
Voltage of batteries produced in August
cross section statistics - ANS-values accrued from a number of topics all through a single
term. Ex. Unemployment quotes in 2012 across states
cumulative relative frequency - ANS-totals the percentage of observations that are less than
or identical to the elegance at which you are looking
Shows the gathered share as values vary from low to excessive
statistics - ANS-the muse for statistics