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NMED 220 - Quality Control I > Outcome 3 - Statistics > Flashcards

Outcome 3 - Statistics Flashcards

1
Q

Why stats?

A
  • it allows us to see if our measurements are sufficiently close to the true rate of decay (since it is random and will never be the same each time)
  • help distinguish errors from randomness of decay
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2
Q

What is PRECISION?

A

How reproducible the results are

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3
Q

What is ACCURACY?

A

How close the measurement is to the true value

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4
Q

What is RELIABILITY?

A

The level of reproducibility

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5
Q

What is CONSTANCY?

A

Reproducibility over time
Consistent measurements day after day

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6
Q

What is SENSITIVITY in DIAGNOSIS?

A

An operating characteristic that:
- measures the ability of a test to detect a disease/condition when it is truly PRESENT

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7
Q

What is SENSITIVITY in EQUIPMENTS?

A
  • Minimum detection limit of a radiation detector
  • ability to detect small changes in radioactivity present
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8
Q

What is SPECIFICITY in DIAGNOSIS?

A

An operating characteristic that:
- measures the ability of a tad to exclude the presence of a disease/condition when it is truly NOT PRESENT

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9
Q

What are the 5 types of errors?

A

1/2. Determinate or Systematic
3/4. Indeterminate or Random
5. Blunder (user error)

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10
Q

What is the difference between Determinate/Systematic errors and Indeterminate/Random errors?

A

Determinate/Systematic - results differ from the true value in a consistent way

Indeterminate/Random - inherent differences in the data that can’t be controlled (e.g. randomness of decay)

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11
Q

What is usually the cause of a determinate/systematic error?

A

usually an issue with equipment QC/calibration

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12
Q

What are the two types of distributions?

A
  1. continuous variables
  2. discrete variables
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13
Q

What is the difference between continuous and discrete variables?

A

continuous = variables that have any real number (including decimals)

discrete = variables that are limited to whole numbers

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14
Q

What distributions are used for continuous variables? discrete?

A

continuous - gaussian distribution

discrete - poisson distribution

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15
Q

What is Gaussian statistics?

A
  • used for LARGE sample sizes
  • allows the assumption of the sample to represent a “true” state of the entire population
  • uses normal distribution or bell curves
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16
Q

What does population mean?

A

all possible values for a particular characteristic

17
Q

What does the Y axis in a distribution graph represent?

A

Y axis = the frequency or probability density

18
Q

What does the X axis in a distribution graph represent?

A

X axis = the value of the variable being assessed

19
Q

What are central tendencies?

A

mean, mode, median

20
Q

How do you measure dispersion?

A

range, variance, standard deviation

21
Q

How do you calculate range?

A

difference between highest and lowest value

22
Q

How do you calculate variance?

A

sum of the (differences of all values from the mean) squared then divided by sample size - 1

23
Q

What is the measurement of dispersion?

A

it is how much the values in the sample vary from the center

24
Q

What is standard deviation?

A

the square root of the variance

25
Q

What is the co-efficient of variation (cv or v)? Why is it important?

A
  • standard deviation as a percentage of the mean
  • allows for the comparison between population with different means
26
Q

Large variance (s^2) = ?
Small variance (s^2) = ?

A

large = wide divergence from average
small = narrow divergence from average

27
Q

What are confidence intervals?

A

pattern that let’s you make assumptions on how many counts/measurements will fall within which interval

28
Q

difference between true mean and observed mean?

A

true = population mean
observed = sample mean

(sample - small group within a population; population - all possible values for a particular characteristic)

29
Q

In a normal distribution, what is the percentage of data that falls within +/- 1SD? +/- 2SD? +/- 3SD?

A

+/- 1SD = 68.3% (68%)
+/- 2SD = 95.5% (96%)
+/- 3SD = 99.7% (99%)

30
Q

What characteristics are required to apply Poisson distribution?

A
  • whole numbers greater than 0
  • events measured aren’t related to each other
  • probability of each event is the same
  • events are random, but there is a known rate of occurrence
31
Q

What is the difference of SD in Gaussian vs. Poisson?

A

Gaussian - SD is INDEPENDENT of mean
Poisson - SD is DEPENDENT on mean

32
Q

What does the SD of a single measurement indicate?

A

It is the prediction of how much variation there would be if there were repeated measurements

33
Q

of counts ____ = cv ______

A

Increases, decreases

34
Q

What is the minimum level of confidence in NM?

A

2% error with a 95% confidence level (3SD)
Therefore, a minimum of 10000 counts for statistical validity

35
Q

What is a Levy-Jennings graph used for?

A

To see the performance of the detector over time.

36
Q

What is a chi-squared test used for?

A

Sees if the detector demonstrates the predicted level of variation between measurements

NMED 220 - Quality Control I (2 decks)

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