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Biometrics > Lectures 1-3 > Flashcards

Lectures 1-3 Flashcards

1
Q

What is biometrics?

A

biology statistics

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2
Q

what is an entire collection of measurements from all of the organisms that a researcher is interested in

A

population

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3
Q

What is the numerical summary of the population

A

Parameter, can RARELY be calculated, very large = not feasible to obtain

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4
Q

What is a parameter estimated by?

A

a statistic

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5
Q

How is a parameter represented?

A

greek letters

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6
Q

Examples of parameters

A

mean and standard deviation

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7
Q

What is the subset of a population

A

Sample

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8
Q

Samples need to be

A

random and interspersed

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9
Q

random (sampling)

A

if every individual in the population has an equal chance of being represented in the sample

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10
Q

interspersed (sampling)

A

representative of entire populations/areas (i.e.: few fish from deep end and few from shallow end)

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11
Q

What are samples that are not random/interspersed, do not accurately reflect the population of interest

A

Biased samples

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12
Q

What happens if randomly-selected samples are not interspersed?

A

it is not representative, a grid is usually used

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13
Q

What is the numerical summary of a SAMPLE

A

Statistics

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14
Q

What are estimates of population parameters?

A

statistics

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15
Q

What is the difference between the sample statistic and the population parameter

A

sampling error

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16
Q

how is objectivity achieved?

A

by statistical conclusions having a bias in probability

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17
Q

which parts of the scientific method does biometrics focus on?

A

analysis of the results and drawing a conclusion based on your statistical analysis

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18
Q

What are numerical facts, pieces of info

A

Data (datum = one piece of data)

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19
Q

the relationship between statistics and data

A

both are numerical info but statistics is more used

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20
Q

What are objects defined by a set of data

A

individuals

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21
Q

What are characteristics of the individuals (i.e.: weight, height, hair color)

A

variables

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22
Q

relationship between data, individuals, and variables

A

calculate statistics and then used for parameter

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23
Q

types of variables (data) scales

A

nominal, ordinal, ratio, interval

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24
Q

What type of data are qualitative (description/categories)

A

nominal scale data

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25
Q

What type of data are quantitative, ranked data due to unequal increments between successive values | non-parametric tests

A

ordinal scale data

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26
Q

Which type of data is quantitative, equal increments between successive values (measured values), NO biologically meaningful zero

A

interval scale data (i.e.: temperature)

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27
Q

Which type of data is quantitative, equal increments between successive measured values, HAS biologically meaningful zero

A

ratio scale data (i.e.: lbs, concentration, ft.)

28
Q

what is important for employing appropriate statistic

A

making the distinction between these types of data

29
Q

two types of statistics

A

inferential and descriptive

30
Q

What are estimations of population parameters

A

inferential statistics

31
Q

What are the numeral summary of statistics

A

descriptive statistics

32
Q

two types of descriptive statistics

A

measures of: central tendency and dispersion

33
Q

what are parts of measures of central tendency

A

mean, median, mode

34
Q

what appropriate measure of central tendency is used for ratio-interval scale data, most common for interval

A

mean (average)

35
Q

what is mean of several means

A

grand (weighted) mean

36
Q

What measure of central tendency is used for ordinal-scale data

A

median, middle value in an ordered set of data

37
Q

what measure of central tendency is used for nominal-scale data

A

mode, number that occurs most frequently in the data set

38
Q

what is measures of dispersion

A

variability used for ratio-interval scale data

39
Q

what is range?

A

difference between the largest and smallest value

40
Q

in which type of data is range used for?

A

ordinal-scale

41
Q

what are diversity indices

A

used for nominal-scale data

42
Q

What shows measured values (data) arranged from smallest to largest on the x-axis, and the frequency that these values occur on the y-axis

A

frequency distributions

43
Q

what are bar graphs used in?

A

nominal scale data

44
Q

how can frequency distributions be represented?

A

histograms or probability curves

45
Q

what are frequency distributions useful for?

A

determining the probability of obtaining certain values

46
Q

What is the frequency distribution that most complex variables (biological variables) follow

A

normal distributions

47
Q

what are properties of a normal distribution

A

symmetrical at the mean, bell-shape curved

48
Q

what defines the location/center of a normal distribution

A

the mean

49
Q

what defines the shape/spread of a normal distribution

A

the standard deviation

50
Q

how many normal distributions are there?

A

infinite due to infinite mean and standard deviation combinations

51
Q

skewness

A

asymmetry of a distribution curve

52
Q

what skew represents a higher frequency of larger values

A

right skew

53
Q

what skew represents higher frequency of lower values

A

left skew

54
Q

what describes higher “peakness” in a frequency distribution curve

A

kurtosis

55
Q

what is leptokurtosis

A

all of the values occur right at the mean – all other values are basically nonexistent

56
Q

what is platykurtosis

A

the greatest frequency on all the values – basically all the values have the same frequency

57
Q

purpose of proportions of a normal distribution

A

to determine the probability of obtaining certain values

58
Q

what has a mean of 0, and a standard deviation of 1, values are standardized by converting them into Z-scores

A

the standard normal distribution

59
Q

what are data distributions

A

the frequency distribution of raw data

60
Q

What is the standard deviation of several means values

A

standard error of the mean (SE)

61
Q

What is the frequency distribution of the means of the raw data (many means)

A

sampling distributions

62
Q

what is the best estimate of what we could get if we could get samples over and over

A

standard error of a single sample

63
Q

(central limit theorem) what does it mean if the samples of any size are taken from a normally distributed population

A

the means of these samples will be normally distributed as well

64
Q

(central limit theorem) what will samples taken from any distribution have?

A

means that approach normal distributions as the sample sizes increase

65
Q

(central limit theorem) what is the relationship between the standard error and sample size

A

standard error will decrease as the sample sizes increase

Biometrics (9 decks)

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