Exam 1 Flashcards
(120 cards)
1
Q
W. Edwards Deming
A
used statistics to aid the US Census estimates and helped to improve the quality of manufacturing
2
Q
Plan-Do-Check-Act
A
problem solving process used in quality control
3
Q
what did Deming use to call for change in management philosophy?
A
14 points
4
Q
pattern recognition
A
helps to determine whether an event or observation is unique
5
Q
regression to the mean
A
after a good/bad performance it almost always goes back to the mean
6
Q
availability bias
A
link an event to something in your past
7
Q
quantitative
A
numerical values that can be put into a number line
8
Q
internal validity
A
truth within a study
9
Q
external validity
A
truth beyond a study
10
Q
objectivity
A
seeing things as they are without making it conform to a preconceived view
11
Q
variables
A
the characteristics being measured
12
Q
valued
A
realized measurements
13
Q
categorical
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places observations into unordered categories
14
Q
examples of categorical things
A
sex, blood types, disease status
15
Q
ordinal
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puts observations into categories that can be ranked
16
Q
example of ordinal things
A
cancer stage, opinions
17
Q
examples of quantitative things
A
age, bp, body weight
18
Q
GIGO
A
bad input means a bad output
19
Q
imprecision
A
inability to get the same result upon repetition
20
Q
bias
A
tendency to overestimate the true value
21
Q
surveys
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quantifies population characteristics
22
Q
comparative studies
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quantifies relationships between variables
23
Q
census
A
attempts to collect information on all individuals in the population
24
Q
probability sample
A
sample in which each member of the population has a known probability of entering the sample
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sampling fraction
n/N
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n
size of sample
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N
population size
28
undercoverage bias
some groups are left out or underrepresented
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volunteer bias
self-selected participants tend to be atypical of the population
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nonresponse bias
a large percentage of individuals refuse to participate
31
stratified random samples
draws SRSs from a relatively homogenous groups
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SRS
simple random sample
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cluster samples
randomly select large units consisting of smaller units
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experimental studies
investigator assigns the exposure to one group while leaving the other nonexposed
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non experimental studies
classifies groups as exposed or non exposed without intervention
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explanatory variable
treatment/exposure that explains or predicts changes in the response variable
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response variable
outcome/exposure being investigated
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are discrepancies in experimental and non experimental studies normal?
hek ya
39
confounding
occurs when effects of a lurking variable become mixed up with the effects of the explanatory variable
40
single-blind
subjects are kept in the dark about the specifics of the treatment they're receiving
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double-blind
subjects and investigators are kept in the dark
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triple-blind
subjects, investigators and statistician are kept in the dark
43
frequency distributions
tells us how often we see the various values in a batch of numbers
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what does a stem and leaf plot show us?
shape, location and spread
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modality
number of peaks in a distribution
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kurtosis
steepness of the mound
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median
point that divide the data set into a top half and a bottom half
48
spread
informed way to refer to the dispersion or variability of data points
49
what is the worst kind of sampling and why?
convenience sampling, it's usually biased
50
consecutive sampling
biased, sample people with characteristics that they want, often used in healthcare
51
best kind of sampling and why?
simple random sampling, each member has the same chance of being selected
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systemic sampling
take every nth individual
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cluster sampling
random sampling of natural groupings (schools, towns etc)
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what should you check data for?
outliers, variables are normally distributed, see if you can combine
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discrete random variable
countable set of random outcomes
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is the mean susceptible to outliers?
yea
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the mean can be used to predict...
1) an individual value drawn at random from a sample
2) a value drawn at random from a population
3) the population mean
58
is the median more resistant to outliers and skews?
ya
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mean=median
symmetrical
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mean>median
positive skew
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range=
maximum-minimum
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how many set does a quartile divide the data into
4
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example of discrete random variable
of leukemia cases in a geographic region in a given period
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continuous random variable
address quantities that take on an unbroken continuum of possible values
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example of continuous random variable
time it takes to complete a task
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probability mass function (pmf)
mathematical relation that assigns probability to all possible outcomes for a DISCRETE random variable
67
A
event A
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Pr(A)
probability of event A
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S
sampling universe
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p
probability of success of each trial
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q
probability of failures of each trial
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why is it better to have a bigger sample size?
larger sample size means you'll be closer to the actual mean
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statistical interference
act of generalizing from a sample to a population with calculated degree of certainty
74
Where did Deming go to school?
University of Wyoming and Yale
75
Where did Deming work?
Western Electric and as a US census statistician
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How did Deming help during war times?
improved the manufacturing process by reducing errors and minimizing waste
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Who was Deming influenced by?
Walter Andrew Shewhart
78
Kaizen
quality improvement is a continuous process that requires teamwork and open communication and competence in problem solving
79
What is Demings quote?
quality is about people, not products
80
Nelson Data-to-Wisdom
starts with collecting data and then organizing it to find new insights and knowledge
81
normal probability graph shape
bell curve
82
uniform probability graph
each score is equally likely and is shaped like a rectangle
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exponential probability graph
the negative slope, u kno the one
84
why do you need more data to get a good probability distribution?
too little makes it have a funky shape, more data means a smooth curve, like schreier
85
reliability
ability to collect the same values for a variables
86
example of reliability
measuring a childs height three times
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validity
how truthful the data is (are free from error)
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how does reliability look on a bullseye?
how close the darts are together
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how does validity look on a bullseye?
if the darts hit the center
90
scientific ethos
statisticians must maintain objectivity
91
incidence
number of newly developing cases of a disease occurring in a defined population over a defined period
92
prevalence
total number of individuals with the disease in a population at a given point of time
93
RCT
randomized controlled trial
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RCT definition
getting a group of people with the same condition then assigning them to an intervention group or control group
95
James Lind Scurvy treatment
took 12 sailor with scurvy and gave them all different treatments to see what worked
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key features of RCTs
- randomization
- use of a control group for comparison
- blinding or masking
- ethics
97
frequency tables
lists all the data values and present the frequency count of each value
98
why are frequency tables nice?
good way to identify outliers and check for data entry errors
99
standard deviation
deviations around the mean (how far away from the mean they are)
100
variance
sum of squared deviations divided by the sample size minus one
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random variable
numerical quantity that takes on different values depending on chance
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what is the most common pdf?
normal
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pdf
probability density function
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population
set of all possible values for a random variable
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event
outcome or set of outcomes
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probability
proportion of times an event is expected to occur in the population
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binomial random variable
type of discrete random variable that only has two possible outcomes
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area under the curve
probability of something happening
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normal random variable
continuous random variable that describe some natural phenomena
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68-95-99.7 rule
68% of the area under the curve is within u+/-o
95% "" u+/-2o
98% ''' u+/-3o
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one side vs. two side tests
one sided=greater than Ho
| two sided=greater or less than Ho
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example of a normal random variable
height, weight, systolic blood pressure
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sampling behavior of the mean
tend to be normal with and expected value equal to populations mean and standard deviation
114
interval estimation
surrounds the point estimate with a margin of error
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standard error of the mean
deviation over square root of sample size
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type 1 error
rejecting null when you should have kept it
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significance level
a smaller P-value gives stronger evidence against Ho
118
whats the funky u mean?
expected value
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type 2 error
keeping null when you should have rejected it
120
pdf definition
assigns probabilities to all possible outcomes for CONITNUOUS random variable
