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62 Cards in this Set
 Front
 Back
Descriptive Statistics 
Summarize a data set into a few numbers that represent or describe a group of numbers. Mean 

Inferential Statistics 
Compare information from one set of data to another set of data to make a comparison or inference about the data Ttest or linear regression 

Population 
the entire group of items that could possibly be measured Represented by N 

Sample 
A subset from the population. Should be randomly selected to accurately represent the population Represented by n 

Variable 
the characteristic you want to measure 

data 
the values you obtain from a sample population A single value is call a datum 

data set 
set of variable connected 

experiment 
a planned activity whose result yield a data set 

parameter 
a numerical value that summarizes one aspect of the data from a population 

Statistic 
a numerical value that summarizes one aspect of the data from a sample 

Qualitative 
Yes/No values pos/neg less than greater than 

Quantitative 
an actual number 

Accuracy 
the measurement closest to the true value Inaccuracy: lack of closeness to the true value 

Precision 
the repeatability of the process how reproducible are your values 

Inaccuracy and Variability 
Inaccuracy must be detectable and is accepted within it's defined limits variability: is expected and accepted within defined limits


Variability 
We must decide what is acceptable In the lab we test QC and use QC rules to do this 

Qualitative Data 
Gives a general impression:


Ways to show quantitative data 


Frequency distribution 


Histogram 


Meanm Median, Mode 
In a perfect distribution they should be the same 

Mean 
add all the numbers divided by the number of data 

Median 
Middle number Even set of numbers divide by 2 Odd set of number (n+1)/2 Not effected by extreme values 

Mode 
the number, or numbers, that occur the most frequently Some data is bimodal, sometimes there is no modal number not effected by extreme values 

Measures of variability Gaussian distribution 


Measures of variabilityStandard deviation and variance 


Coefficient of Variation 
The smaller the CV the better the precision 

Shift from the mean 
systematic error Can fix 

5 stages of QC 


Why test QC material 


QC material Selection and USe 


Assayed control 
QC material that has been repeatedly analyzed by the manufacturer: Includes means and SDs Statistical data is supplied with the QC material Expensive 

Unassayed controls 
have not been tested for concentration or variability 

For all controlled material 
The mean and the SD must be verified or established in your lab before use in your QC program QC with different lot # may have different analyte concentrations 

New lot # 
New mean and SD must be established 

Minimum QC 
two levels per day for each analyte 

Frequency of QC testing 
Instrument Manufacturer sets Experience dictates frequency of QC Criticality of the analyte dictates frequency 

QC levels 
Normal: Ref range Below: the normal/ref range Above: the normal/ref range 

QC level 1 
usually in the "normal/ref range" 

QC level 2 
usually in the abnormal range ( some high some low) 

QC level 3 
Low abnormal, normal, and high abnormal used in hematology for drug testing 

Evaluation of QC data 
Based on Gaussian Curve:


LeveyJennings Chart 


Creating a LeveyJennings Chart 


Analytic Errors 


Random Errors 


Systemic Error 


Gaussian distribution 


Shift 


Trend 


Shift/Bias 
The QC data shifts/move abruptly away from the mean for number of days 

Trend 
QC data either decreases or increases consistently over a period of 7 days 

Westgard QC multirules 
IDs the presence of:


One (1) QC warning rule 
gets your attention 

Five (5) QC failure rules 
used to reject qc data: 5 rules are applied if 2 QC levels are used, other rules exist if 3 qc levels are used 

Why repeat QC with a 13s QC error 


Why troubleshoot QC with a 22s error 


Troubleshoot QC Systemic error 


41s error 


10x failure rule 


Look at QC rules when 
QC violates the 12s warning rule, look at QC data continually 

Common mistakes in use of QC 
