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83 Cards in this Set

  • Front
  • Back
Science of Collecting/ interpreting data
Study of complete set of people being studied
population parameters
Characteristics of the population
subset of population from data are actually obtained
samples Statistic
Sample found by consolidating or summarizing the raw data
Margin of Error
describes range of values likly to contain the pop. parameter

Sample stat- margin of error
sampple stat+ margin of error
Steps in Statisitcal study
1 identify goal
2 choose sample
3 collect data
4 use sample to make inferences
5 draw conclusions
collection of data from every population
represtative data
sample has relevent characteristics of the general population
bias if.....
tend to favor certain results
Simple random sample
sample item in such way that every sample of same size has equal chance of being selected
Systematic sampling
Simple system to choose sample..... 10th or every 50th
Convenience sampling
sample that happens to be convenient
Cluster Sampling
Divide pop into groups, then pick groups randomly
stratified sampling
use when concerned about differences amoung sub groups... draw random samples from the individual strata
People or objects chosen from sample
if subjects are people, called participants
Observational Study
Observe or measure characteristics of the subjects, but do not attempt to influence
Apply some treatment and observe
meta Analysis
Study topic that has been the subject of many other studies
Treatment group
group which recieves the treatment being tested
control group
an experiment is the group of subjects who do not receive the treatment being tested
Randomized Experiment
Subjects are assinged to the treatment group or control group at random so that each has = chance of being assigned to either group.
placebo effect
lacks the active ingredient of a treatment being tested, identical in apperence to the treatment.
placebo effect
Situation which patients improve simply because thehy believe they are reciving a useful treatment
single blind
Do not know whether they are members of treatment group or members of control---- Experimenters know!
double blind
Niether participants nor any experimenters know who belongs to treatment or control
case control
Observational study- natually divides into two or more groups.

*people who behave inder study form case

* people who do not behave are controls
selection bias
Researchers select their sample in bias way
participantion bias
occurs anytime participation in a study is voluntary
self selected survey
people decide for themselves whether to be included in the survey
Item that can vary or take on different values
Data Types
Qualitative data
Quantitative data
Qualitative data
Values that can be placed into nonumerical categories
Values representing counts or measures
an take on any value in a given interval
can take on only particular values and not other values
nominal level
data that consist names, lables or catorgories.... Qualitiative and and can't be rank or ordered
Ordinal level
applies to qualitative data that can be arrange in some order( high to low)
Interval level
Qualititative data --- intervals are important
Ratio level
applies to Quantitative data-- intervals and ratios are important
Random error
Unpredictable events in the measurment process
systematic errors
Problem in measurment system
Absolute error
how far measured value lies from the true value

Absolute= measured - true value
Relative error
measured value- true value
------------------------- x 100
true value
how close a measurment approximates a true value
Amount of detail in a measurement
Absolute Difference
Absolute diff = compard - refernce val
relative difference
compard value- ref val
--------------------- x100

Ref value
Index numbers
Index numbers= Value
------- x 100
ref val
consumer price index
Computed monthly, based on prices in a sample of more than 60,000 services
Frequency tables
1. Categories

2. Frequency
group catorgies
relative frequency
proportion or percentage of the data value that falls in category

Relative Freq= Freq in categoriey
total freq
Cumulative Freq
number of data values in that category and all preceding categories
way values are spread over all possiable values
bar gragh
bars representing freq
dots represent freq
pareto chart
Bars arranged in freq order( nominal level)
bar graph--- which show distributions for quanitiative data
stem leaf plot
Histogram turned sideways.. no bars.. see indivdual data
line chart
distrobutions of quantitative data as a series of dots onnected by lines
Average value
middle value
Most common value
data set which is much higher or much lower than mos values
weighted mean
sumof (each data value x its weight)
sum of all weights
A distribution is Symmetric if
left half is a mirror image of its right
Left Skewed
Value are more spread out n the left side
right skewed
values are more spread out to the right side
how widly spread out about the center of data set
lower Quartile
divides lower fouth from upper fouth
Middle Quartile
Overall Median
Upper Quartile
divides lower fourths three- fourths from upper three fouths
five number summary
Distribution consists of the following

1 lower value
2 lower value
3 median
4 upper Quartil
5 high quartil
nth percentil
Divides the bottom % of data values from the top (100-n)%

Percentile of data value= number of values lessthat this data value
Total number of values in data set

X 100
normal distribution
symmetric, bell shaped distribution with single peak
Relative Freq and Normal Distribution
area under normal distribution curve corresonding to the range of vales on the horizontal axis is relative frequency of those values

Total relative freq must be 1. area under the normal distribution curve must equal 1
condition for normal distribution values clustered near mean= single peaked
2.Values spread evenly around mean making symmetric
3.Large deviation from mean becomes incresingly rare= producing tapering tails
4.Indiviual data results from comnination of many different factors such as genetic and enviormental factors
Data falls within 1 Standard Deveiation of the mean
Data points fall within 2 standard deviation of the mean
Fall within 3 standard deviation of the mean
Standard scores
data values that lies above or below the mean

z= standard score= data value-mean
Standard Deviation