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GEOG 271 > Term Test 1 > Flashcards

Term Test 1 Flashcards

1
Q

A set of mathematical procedures and principles that are used to gain information and make decisions with some certainty

A

Statistics

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2
Q

Involves collecting, summarizing, and presenting data using numerical and graphical techniques

A

Descriptive statistics

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3
Q

Involves making estimates, decisions, predictions, or other generalizations about data using a sample

A

Inferential statistics

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4
Q

Method of drawing conclusions after observing facts and/or cause and effect scenarios, is less accurate, goes from specific to general information

A

Inductive reasoning

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5
Q

Method of drawing conclusions by producing an explanation and then testing it by observing facts, is more accurate, goes from general information to specific conclusions

A

Deductive reasoning

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6
Q

When researchers use statistics to pursue knowledge-gathering, they are employing a

A

Scientific methodology

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7
Q

The process of trying to prove theories and hypotheses wrong, involved in the process of deduction

A

Falsification

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8
Q

AKA the scientific method, using reasoning, observation, and experimentation to test a hypothesis

A

Hypothetico-deductive method

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9
Q

A forecast or extrapolation of what is to come, the less simple the better

A

Prediction

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10
Q

A controlled investigation designed to evaluate incomes

A

Experiment

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11
Q

The combining of a body of scientifically collected fact into a simple statement

A

Idealization

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12
Q

Relating apparently unconnected information or phenomena to the same concept

A

Unification

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13
Q

Can be quantitative or qualitative, information and/or observations about something

A

Data

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14
Q

A collection of information that consists of observations and variables for some phenomenon

A

Dataset

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15
Q

The measurement of the quality of something, non-numerical

A

Qualitative

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16
Q

The measurement of the quantity of something, numerical

A

Quantitative

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17
Q

A hypothesis or set of equations that provides a simplified explanation of something being studied

A

Model

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18
Q

An unproven statement concerning cause-and-effect that can be tested

A

Hypothesis

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19
Q

A hypothesis that has repeatedly been proven correct

A

Law

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20
Q

A number of interrelated laws, explains why phenomena occur

A

Theory

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21
Q

A characteristic that can be measured for an observation of data, something that can vary

A

Variable

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22
Q

The act of knowing and recording something that has measurable characteristics or variables

A

Observation

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23
Q

Changes in the quantitative or qualitative measure of observations for a variable, suggests uncertainty

A

Variation

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24
Q

A complete set of measurements, objects, or outcomes related to some phenomena under study

A

Statistical population

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25
Q

A subset of observations from a population

A

Sample

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26
Q

Numerical characteristic of a population

A

Parameter

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27
Q

Determined by chance, without pattern or plan

A

Random

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28
Q

The probability that a statistical conclusion is correct

A

Significance

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29
Q

Manipulation or effect applied to observations being used in an experiment

A

Treatment

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30
Q

The collection of data from a subset of a population without using any treatments

A

Observational study

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31
Q

Description, prediction, explanation, and control

A

The four goals of science

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32
Q

Data collected directly from an original source by a researcher

A

Primary data

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33
Q

Data collected by others, often has issues with unknown data errors

A

Secondary data

34
Q

Value of data is determined by assigning qualitative units of measurement, ex. political party affiliation

A

Nominal measurement scale

35
Q

Value of data is numerical and determined in rank order, but have no meaningful mathematical distance between rankings ex. ranked lists (10 best cities to live in Canada)

A

Ordinal measurement scale

36
Q

Value of data is numerical and determined in rank order, and there are meaningful units of distance to separate numbers but no absolute zero ex. temperature scales

A

Interval measurement scale

37
Q

Value of data is numerical and determined in rank order, there are meaningful units of distance to separate numbers and there IS an absolute zero ex. comparing precipitation amount and 0 means 0 precipitation

A

Ratio measurement scale

38
Q

Refers to how close measurements are to each other

A

Precision error

39
Q

Refers to how close measurements are to the ‘true’ value being measured

A

Accuracy error

40
Q

Refers to when the variable is not appropriate to answer the question of the experiment

A

Validity error

41
Q

Refers to errors that can develop when measurements are made across time and/or space

A

Reliability error

42
Q

Data is classified into equal-width intervals

A

Equal intervals based on range

43
Q

Data is classified based on convenience or practical decisions

A

Equal intervals not based on range

44
Q

Data is classified into intervals that contain the same number of data observations

A

Quantile breaks

45
Q

Data is classfied based on natural intervals in the data

A

Natural breaks

46
Q

Data is classfied based on natural intervals in the data

A

Natural breaks

47
Q

Graph with a number line covering the range of data values for one variable

A

Dot plot

48
Q

Chart with categorical non-numerical data for a single variable grouped into class intervals placed along the x-axis and frequency count along the y-axis

A

Bar chart

49
Q

Chart with categorical data for a single variable arranged as portions within a circle

A

Pie chart

50
Q

Graph that displays the shape of the numerical data of a single variable; x-axis shows the range and y-axis displays the frequency. These can be unimodal or bimodal

A

Histogram

51
Q

Chart that plots numerical frequency data as points that are connected by a line

A

Frequency plot (or polygon)

52
Q

Chart that plots numerical frequency data in a format with successive additions of the values in each increasing interval

A

Cumulative frequency plot (or ogive)

53
Q

Chart that summarizes numerical data in a table with unique data elements on the left side and all of the final numbers in the right side next to their appropriate unique element

A

Stem-and-leaf diagram

54
Q

Graphic that displays the median, first quartile, and third quartile, with two whiskers extending above and below commonly showing the min and max values

A

Box plot

55
Q

Graph used to plot data with paired observations for two different variables, usually with dots

A

Scattergram (or scatterplot)

56
Q

The average value of the data

A

Mean

57
Q

The value that occurs most often in the data

A

Mode

58
Q

The value in the middle of the data

A

Median

59
Q

Skewness in which most of the data is right of the mean. The mean is smaller than the median which is smaller than the mode.

A

Negative skewness

60
Q

Skewness in which most of the data is left of the mean. The mean is larger than the median which is larger than the mode.

A

Positive skewness

61
Q

The difference between the highest and lowest values in a set of data

A

Range

62
Q

The ordered classification of data into quartiles, quintiles, etc

A

Quantiles

63
Q

The distance from the 25th percentile value to the 75th percentile value

A

Interquartile range (IQR)

64
Q

A type of box plot but with dots, used to display the distribution of the data points relative to the median and interquartile range

A

Dispersion diagram

65
Q

Refers to the variability of observations found in data

A

Dispersion

66
Q

In a box plot- can be the max & min or can be calculated based on the the 1st and 3rd quartiles plus 1.5 times the IQR

A

Whiskers

67
Q

The difference of a particular observation value relative to the mean for a dataset

A

Individual deviation

68
Q

An observation that lies an abnormal distance from other values

A

Outlier

69
Q

Most common measure of dispersion of values

A

Standard deviation

70
Q

Measure of dispersion, the square of standard deviation

A

Variance

71
Q

Measures the shape of the data frequency relative to the mean

A

Skewness

72
Q

It defines specific areas under the normal distribution

A

The importance of standard deviation

73
Q

A measure of relative variability; the standard deviation divided by the mean

A

Coefficient of variation

74
Q

Measures the flatness and peaked-ness of a data frequency distribution

A

Kurtosis

75
Q

A statistic that examines the shape of the frequency distribution by comparing the median with the mean

A

Pearson’s skewness

76
Q

Statistic that measures the central tendency for a distribution of points in two-dimensional space; output in coordinates

A

Mean center

77
Q

The weighted determination of central tendency in two dimensions, employing frequency counts of some phenomenon associated with the data points

A

Weighted mean center

78
Q

Measure of central tendency in two-dimensional data, measures the sum of straight-line distance of data points to the center of the data’s distribution (center of minimum travel)

A

Euclidean mean (or median center)

79
Q

Two-dimensional equivalent of standard deviation, uses mean center and Euclidean mean to calculate

A

Standard distance

80
Q

Spatial equivalent of weighted standard deviation, uses weighted mean center and Euclidean mean to calculate

A

Weighted standard distance

81
Q

Spatial analog to coefficient of variation, allows for direct comparisons of dispersion or two or more distribution patterns

A

Relative distance

GEOG 271 (1 decks)

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