Unit 1: Introduction Statistical Biology Flashcards

1
Q
  • A vital language and tool in almost all aspects of our daily life.
  • 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

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

A

Mathematical/Theoretical statistics

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5
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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6
Q

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

A

Descriptive statistics

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7
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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8
Q

Examples of Descriptive statistic

A
  • Bar charts, pie charts, and line charts.
  • Numerical tables.
  • Rates.
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9
Q

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

A

Statistical Biology/Biostatistics

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10
Q
  • 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 observational unit.
A

Element or member of a sample or population

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11
Q

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

A

Variable

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12
Q

The value of a variable for an element.

A

Observation or Measurement

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13
Q

A collection of observations on one or more variables.

A

Data set

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14
Q

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

A

Univariate data

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15
Q

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

A

Bivariate data

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16
Q

Results when more than two variables are measured.

A

Multivariate 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

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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19
Q

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

A

Census

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20
Q

The collection of information from the elements of a sample.

A

Sample survey

21
Q

A numerical measure that summarize data for an entire population.

A

Parameter

22
Q

A a numerical measure that summarize data from a sample.

A

Statistcs

23
Q

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

A

Random sampling

24
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

25
Q

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

A

Convenience sampling

26
Q

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

A

Judgement sampling

27
Q

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

A

Sampling error

28
Q

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

A

Non-sampling errors

29
Q
  • The error that occurs because the sampling frames is not representative of the population.
  • 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.
A

Selection error

30
Q
  • The error that occurs because many of the people included in the sample do not respond to a survey.
  • The sample are representative of the population, nonresponse error may occur because many of the people included in the sample may not respond to the survey.
A

Non-response error

31
Q
  • Occurs when people included in the survey do not provide correct answers.
  • This or bias occurs when the answer given by a person included in the survey is not correct.
A

Response error

32
Q
  • The polls conducted based on samples of readers of magazines and newspapers suffer from voluntary response error or bias.
  • 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

33
Q

Used to obtain a random sample that represents the target population.

A

Random sampling techniques

34
Q

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

35
Q

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

A

Sample size

36
Q

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

A

Population size

37
Q

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

38
Q

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

39
Q

A sampling technique in which the entire population is divided into smaller groups that are not overlapping and represent the entire population.

A

Stratified Random Sampling

40
Q

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

A

Cluster random sampling

41
Q

May be classified as quantitative or qualitative.

A

Variable

42
Q

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

43
Q

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

A

Discrete variable

44
Q

A variable that can assume any numerical value between two numbers.

A

Continuous variable

45
Q

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

A

Qualitative or categorical variables

46
Q

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

A

Cross-section data

47
Q

A data collectedonthesameelementof the same variable at different points or for different period of time.

A

Time-series data

48
Q

A manual computations in statistics involve a lot of adding all values of the variable.

A

Summation notation.

49
Q

Used to denote the sum of all values.

A

Uppercase Greek letter Σ (pronounced sigma)