Outcome 3 - Statistics

Question 1

Why stats?

Answer 1

• 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

Question 2

What is PRECISION?

Answer 2

How reproducible the results are

Question 3

What is ACCURACY?

Answer 3

How close the measurement is to the true value

Question 4

What is RELIABILITY?

Answer 4

The level of reproducibility

Question 5

What is CONSTANCY?

Answer 5

Reproducibility over time
Consistent measurements day after day

Question 6

What is SENSITIVITY in DIAGNOSIS?

Answer 6

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

Question 7

What is SENSITIVITY in EQUIPMENTS?

Answer 7

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

Question 8

What is SPECIFICITY in DIAGNOSIS?

Answer 8

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

Question 9

What are the 5 types of errors?

Answer 9

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

Question 10

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

Answer 10

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)

Question 11

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

Answer 11

usually an issue with equipment QC/calibration

Question 12

What are the two types of distributions?

Answer 12

1. continuous variables
2. discrete variables

Question 13

What is the difference between continuous and discrete variables?

Answer 13

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

discrete = variables that are limited to whole numbers

Question 14

What distributions are used for continuous variables? discrete?

Answer 14

continuous - gaussian distribution

discrete - poisson distribution

Question 15

What is Gaussian statistics?

Answer 15

• 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

Question 16

What does population mean?

Answer 16

all possible values for a particular characteristic

Question 17

What does the Y axis in a distribution graph represent?

Answer 17

Y axis = the frequency or probability density

Question 18

What does the X axis in a distribution graph represent?

Answer 18

X axis = the value of the variable being assessed

Question 19

What are central tendencies?

Answer 19

mean, mode, median

Question 20

How do you measure dispersion?

Answer 20

range, variance, standard deviation

Question 21

How do you calculate range?

Answer 21

difference between highest and lowest value

Question 22

How do you calculate variance?

Answer 22

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

Question 23

What is the measurement of dispersion?

Answer 23

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

Question 24

What is standard deviation?

Answer 24

the square root of the variance

Question 25

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

Answer 25

- standard deviation as a percentage of the mean - allows for the comparison between population with different means

Question 26

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

Answer 26

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

Question 27

What are confidence intervals?

Answer 27

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

Question 28

difference between true mean and observed mean?

Answer 28

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

Question 29

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

Answer 29

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

Question 30

What characteristics are required to apply Poisson distribution?

Answer 30

- 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

Question 31

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

Answer 31

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

Question 32

What does the SD of a single measurement indicate?

Answer 32

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

Question 33

# of counts ____ = cv ______

Answer 33

Increases, decreases

Question 34

What is the minimum level of confidence in NM?

Answer 34

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

Question 35

What is a Levy-Jennings graph used for?

Answer 35

To see the performance of the detector over time.

Question 36

What is a chi-squared test used for?

Answer 36

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