High Yield Biostatistics

Front 1

Probability of an event

Back 1

Denoted by p

Expressed as decimal fractions, not as percentages, must lie between zero (zero probability) and one (absolute certainty).

The probability of an event cannot be negative.

The probability of an event can also be expressed as a ratio of the number of likely outcomes to the number of possible outcomes.

Front 2

The probability of an event not occurring

Back 2

Equal to one minus the probability that it will occur; this is denoted by q

Front 3

Addition rule of probability

Back 3

states that the probability of any one of several particular events occurring is equal to the sum of their individual probabilities, provided the events are mutually exclusive (i.e., they cannot both happen).

ex. Because the probability of picking a heart card from a deck of cards is .25, and the probability of picking a diamond card is also .25, this rule states that the probability of picking a card that is either a heart or a diamond is:

.25 + .25 = .50.

Because no card can be both a heart and a diamond, these events meet the requirement of mutual exclusiveness.

Front 4

The multiplication rule of probability

Back 4

states that the probability of two or more statistically independent events alloccurring is equal to the product of their individual probabilities.

ex. If the lifetime probability of a person developing cancer is .25, and the lifetime probability of developing schizophrenia is .01, the lifetime probability that a person might have both cancer and schizophrenia is

.25 x .01 = .0025,

provided that the two illnesses are independent—in other words, that having one illness neither increases nor decreases the risk of having the other.

Front 5

The probability that a specific combination of mutually exclusive independent events will occur can be determined by the use _________________

Back 5

binomial distribution

A physician could therefore use the binomial distribution to inform a couple who are carriers of Tays Sachs how probable it is that some specific combination of events might occur—such as the probability that if they are to have two children, neither will inherit the disease.

Front 6

binomial distribution

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A binomial distribution is one in which
there are only two possibilities, such as yes/no, male/female, and healthy/sick

Front 7

Types of Data

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Data will always form one of four scales of measurement: nominal, ordinal, interval, or ratio. The mnemonic “NOIR” can be used to remember these scales in order.

Data may also be characterized
as discrete or continuous.

Front 8

Nominal scale

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data are divided into qualitative categories or groups, such as

male/female,

black/white,

urban/suburban/rural, and

red/green.

There is no implication of order or ratio.
Nominal data that fall into only two groups are called dichotomous data

Front 9

Ordinal scale

Back 9

data can be placed in a meaningful order

(e.g., students may be ranked 1st/2nd/3rd in their class).

However, there is no information about the size of the interval—no conclusion can be drawn about whether the difference between the first and second students is the same as the difference between the second and third.

Front 10

Interval scale

Back 10

data are like ordinal data, in that they can be placed in a meaningful order. In addition, they have meaningful intervals between items, which are usually measured quantities. For
example, on the Celsius scale, the difference between 100° and 90° is the same as the difference
between 50° and 40°. However, because interval scales do not have an absolute zero, ratios of scores
are not meaningful: 100°C is not twice as hot as 50°C because 0°C does not indicate a complete
absence of heat

Front 11

Ratio scale

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data have the same properties as interval scale data; however, because there is an
absolute zero, meaningful ratios do exist. Most biomedical variables form a ratio scale: weight in
grams or pounds, time in seconds or days, blood pressure in millimeters of mercury, and pulse
rate in beats per minute are all ratio scale data. The only ratio scale of temperature is the kelvin
scale, in which zero indicates an absolute absence of heat, just as a zero pulse rate indicates an
absolute lack of heartbeat. Therefore, it is correct to say that a pulse rate of 120 beats/min is
twice as fast as a pulse rate of 60 beats/min, or that 300K is twice as hot as 150K

Front 12

Discrete variables

Back 12

take only certain values and none in between. For example, the number
of patients in a hospital census may be 178 or 179, but it cannot be in between these two; the
number of syringes used in a clinic on any given day may increase or decrease only by units
of one.

Front 13

Continuous variables

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may take any value (typically between certain limits).

Most biomedical variables are continuous (e.g., a patient’s weight, height, age, and blood pressure).

However, the process of measuring or reporting continuous variables will reduce them to a discrete variable; blood pressure may be reported to the nearest whole millimeter of mercury, weight to the
nearest pound, and age to the nearest year.