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CMMW > Chapter 4 - Stats > Flashcards

Chapter 4 - Stats Flashcards

1
Q

is 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

Statistics can be divided into two areas:

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

An element or member of a sample or population in a specific subject of object (e.g. a person, a company, a state, or country) about which the information is collected. This can also be called an?

A

observational unit

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12
Q

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

A

variable

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13
Q

is the value of a variable for an element.

A

observation or measurement

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14
Q

is a collection of observations on one or more variables.

A

data set

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15
Q

results when a single variable is measured. Example: body temperature of 150 people.

A

Univariate data

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16
Q

results when two variables are measured. Example: body temperature and age of 150 people.

A

Bivariate data

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17
Q

results when more than two variables are measured.

A

Multivariate data

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18
Q

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

A

population

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19
Q

Population is also usually called the?

A

target population

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20
Q

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

A

sample

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21
Q

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

A

census

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22
Q

is the collection of information from the elements of a sample

A

sample survey

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23
Q

Timeliness is important in conducting research or experiments.

A

TIME

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24
Q

Collecting information from all members of the population may require huge budget which is not efficient and practical.

A

COST

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25
Q

Identification of and access to all members of the population may be unachievable.

A

IMPOSSIBILITY TO CONDUCT A CENSUS

26
Q

is a numerical measure that summarize data for an entire population

A

parameter

27
Q

is a numerical measure that
summarize data for a sample

A

statistic

28
Q

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

A

Random sampling

29
Q

is 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

30
Q

A random sample is usually a?

A

Representative sample

31
Q

Two types of nonrandom sampling are a?

A

convenience sampling and a judgment sampling

32
Q

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

A

convenience sampling

33
Q

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

A

judgment sampling

34
Q

is a statistical error that occurs when an analyst does not select a sample, that represents the entire population of data.

A

sampling error

35
Q

can occur both in a sample survey and in a census. Such errors occur because of human mistakes and not chance.

A

Nonsampling errors or biases

36
Q

Nonsampling errors are also called

A

Systematic errors or biases

37
Q

Types of Sampling Errors:

A
  1. Selection Error
  2. Nonresponse Error
  3. Response Error
  4. Voluntary Response Error
38
Q

is the error that occurs because the sampling frames is not representative of the population.

A

Selection Error

39
Q

When we need to select a sample, we use a list of elements from which we draw a sample, and this list usually does not include many members of the target population. Most of the time it is not achievable to include every member of the target population in this list. This list of members of the population that is used to select a sample is called the?

A

sampling frame

40
Q

is the error that occurs because many of the people included in the sample do not respond to a survey.

A

Nonresponse error

41
Q

occurs when people included in the survey do not provide correct answers.

A

response error

42
Q

occurs when a survey is conducted on a randomly selected people but on a questionnaire published in a magazine or newspaper and people are invited to respond to that questionnaire.

A

Voluntary response error

43
Q

RANDOM SAMPLING TECHNIQUES:

A
  1. Simple Random Sampling
  2. Systematic Random Sampling
  3. Stratified Random Sampling
  4. Cluster Random Sampling
44
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

45
Q

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

A

Sample size

46
Q

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

A

population size

47
Q

This sampling for example, if we need to select 5 students from a class of 50 (target population), we write each of the 50 names on a separate piece of paper. Then, we place all 50 names in a bowl and mix them thoroughly. Next, we draw 1 name randomly from the bowl. We repeat this experiment four more times. The 5 drawn names make up a simple random sample with a sample size of 5.

A

Lottery or fishbowl sampling

48
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

49
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

50
Q

stratum in singular

A

strata

51
Q

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

A

Cluster random sampling

52
Q

Clusters are also called?

A

Primary units

53
Q

A variable may be classified as?

A

quantitative or qualitative

54
Q

are variables that can be measured numerically.

A

Quantitative or Numeric variables

55
Q

Quantitative variables are also called?

A

Numeric variable

56
Q

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

A

discrete variable

57
Q

is a variable that can assume any numerical value between two numbers.

A

continuous variable

58
Q

are variables that cannot be measured numerically can be divided into different categories.

A

Qualitative or categorical variables

59
Q

Qualitative variables are also called?

A

categorical variables

60
Q

If we are considering the timing of the collection of data, data can be classified as either?

A

cross-section or time-series data

61
Q

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

A

Cross-section data

62
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

CMMW (3 decks)

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