# biostats Flashcards

1
Q

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

A

statistics

2
Q

statistical methods

A

Educated guesses

3
Q

statistical or scientific methods

A

Pure guesses

4
Q

Statistics has two aspects

A

: theoretical and applied statistics.

5
Q

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

A

Mathematical/Theoretical statistics

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

7
Q

What are the types/branches of Statistics?

A

descriptive statistics and inferential statistics.

8
Q

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

A

DESCRIPTIVE STATISTICS

9
Q

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

A

INFERENTIAL STATISTICS

10
Q

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

A

Statistical Biology/Biostatistics

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

12
Q

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

A

variable.

13
Q

the value of a variable for an element.

A

An observation or measurement

14
Q

a collection of observations on one or more variables

A

A data set

15
Q

results when a single variable is measured.

A

Univariate data

16
Q

results when two variables are measured.

A

Bivariate data

17
Q

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

A

population

18
Q

results when more than two variables are measured.

A

Multivariate data

19
Q

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

A

sample

20
Q

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

A

census

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.

A

parameter

23
Q

a numerical measure that summarize data from a sample.

A

statistic

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
Q

a method of
sampling in which some member of the
population may not have any chance of
being selected in the sample.

A

Nonrandom sampling

26
Q

Two types of nonrandom sampling

A

convenience sampling and a judgment sampling.

27
Q

the most accessible members of the population are selected
to obtain the results quickly.

A

convenience sampling

28
Q

the members are selected from the population based on the
judgment and prior knowledge of an expert.

A

judgment sampling

29
Q

are used to
obtain a random sample that represents the
target population.

A

Random sampling techniques

30
Q

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.

A

Simple random sampling

31
Q

is the number of elements in the sample,
denoted by n.

A

Sample size

32
Q

denoted by N,
is the number of elements in the population.

A

population size

33
Q

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 .

A

Systematic random sampling

34
Q

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.

A

Stratified random sampling

35
Q

is a sampling technique in which the
entire population is divided into multiple groups (called
clusters) usually by geographical area.

A

Cluster sampling

36
Q

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.

A

Quantitative or Numeric variables

37
Q

is a variable whose values are countable with no possible
intermediate values between consecutive values.

A

discrete variable

38
Q

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

A

continuous variable

39
Q

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.

A

Qualitative or categorical variables

40
Q

is a data
collected on different elements at
the same point or for the same
period of time.

A

Cross-section data

41
Q

is a data
collected on the same element of
the same variable at different
points or for different period of
time.

A

Time-series data

42
Q

(pronounced sigma) is used to denote the sum of all values.

A

The uppercase Greek letter Σ

43
Q

the average of the given numbers and is calculated by dividing the sum of given numbers by the total number of numbers.

A

mean

44
Q

the middle number in a sorted ascending or descending list of numbers and can be more descriptive of that data set than the average

A

mediam

45
Q

number in a set of numbers that appears the most often.

A

mode

46
Q

number in a set of numbers that appears the most often.

A

mode