biostats Flashcards

(46 cards)

1
Q

a group of methods used to collect, analyze,
present, and interpret data and to make decisions.

A

statistics

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2
Q

Decisions made by using
statistical methods

A

Educated guesses

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3
Q

Decisions made without using
statistical or scientific methods

A

Pure guesses

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4
Q

Statistics has two aspects

A

: theoretical and applied statistics.

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5
Q

deals with the development, derivation, and
proof of statistical theorems, formulas, rules, and laws.

A

Mathematical/Theoretical statistics

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6
Q

involves the application of those theorems, formulas, rules, and
laws to solve real-world problems (e.g. economics, psychology, public health).

A

Applied statistics

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7
Q

What are the types/branches of Statistics?

A

descriptive statistics and inferential statistics.

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8
Q

consists of methods for organizing,
displaying, and describing data by
using tables, graphs, and summary
measures

A

DESCRIPTIVE STATISTICS

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9
Q

consists of methods that use sample
results to help make decisions or
predictions about a population from a
sample.

A

INFERENTIAL STATISTICS

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10
Q

is the branch of applied statistics
directed toward applications in the health sciences and biology.

A

Statistical Biology/Biostatistics

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11
Q

a specific subject of object (e.g. a
person, a company, a state, or country) about which the information is collected.

A

element/ member of a sample or population

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12
Q

a characteristic under study that assumes different values of different
elements.

A

variable.

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13
Q

the value of a variable for an element.

A

An observation or measurement

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14
Q

a collection of observations on one or more variables

A

A data set

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15
Q

results when a single variable is measured.

A

Univariate data

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16
Q

results when two variables are measured.

A

Bivariate data

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17
Q

the collection of all elements–individuals, items, or objects–whose
characteristics are being studied.

A

population

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18
Q

results when more than two variables are measured.

A

Multivariate data

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19
Q

the collection of a number of elements selected from a population. It is a
subset selected from the target population.

20
Q

the collection of information that includes every
member of the population.

21
Q

the collection of information from the
elements of a sample.

A

sample survey

22
Q

a numerical measure that summarize data for an entire population.

23
Q

a numerical measure that summarize data from a sample.

24
Q

a method of
sampling in which each member of the
population has some chance of being
selected in the sample.

A

Random sampling

25
a method of sampling in which some member of the population may not have any chance of being selected in the sample.
Nonrandom sampling
26
Two types of nonrandom sampling
convenience sampling and a judgment sampling.
27
the most accessible members of the population are selected to obtain the results quickly.
convenience sampling
28
the members are selected from the population based on the judgment and prior knowledge of an expert.
judgment sampling
29
are used to obtain a random sample that represents the target population.
Random sampling techniques
30
is a sampling technique in which any particular sample of a specific sample size has the same chance of being selected as any other sample of the same size.
Simple random sampling
31
is the number of elements in the sample, denoted by n.
Sample size
32
denoted by N, is the number of elements in the population.
population size
33
is a sampling technique in which the elements of the sample are taken from every kth element in the population arranged alphabetically or by other characteristic. Here, k = 𝑁/𝑛 .
Systematic random sampling
34
is a sampling technique in which the entire population is divided into smaller groups (called strata; stratum in singular) that are not overlapping and represent the entire population.
Stratified random sampling
35
is a sampling technique in which the entire population is divided into multiple groups (called clusters) usually by geographical area.
Cluster sampling
36
are variables that can be measured numerically. These variables are collected in quantitative data such as income, height, gross sales, price of a home, number of cars owned, and a number of accidents.
Quantitative or Numeric variables
37
is a variable whose values are countable with no possible intermediate values between consecutive values.
discrete variable
38
is a variable that can assume any numerical value between two numbers. Weight is an example of the variable since it can assume any value
continuous variable
39
are variables that cannot be measured numerically can be divided into different categories. These variables are collected in a qualitative data. Civil status is an example of a qualitative variable which can take the values “Single”, “Married”, “Widowed”, or “Separated” – nonnumeric values.
Qualitative or categorical variables
40
is a data collected on different elements at the same point or for the same period of time.
Cross-section data
41
is a data collected on the same element of the same variable at different points or for different period of time.
Time-series data
42
(pronounced sigma) is used to denote the sum of all values.
The uppercase Greek letter Σ
43
the average of the given numbers and is calculated by dividing the sum of given numbers by the total number of numbers.
mean
44
the middle number in a sorted ascending or descending list of numbers and can be more descriptive of that data set than the average
mediam
45
number in a set of numbers that appears the most often.
mode
46
number in a set of numbers that appears the most often.
mode