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Data Analysis > Chapter 1-4 terms > Flashcards

Chapter 1-4 terms Flashcards

1
Q

descriptive statistic

A

statistic technique used to organize, summarize and communicate a group of numerical observations

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2
Q

inferential statistic

A

statistical technique that uses sample data to make estimates about the larger population.

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3
Q

sample

A

a set of observations drawn from the population of interest

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4
Q

population

A

all possible observations about which we would like to know something

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5
Q

variable

A

any observation of a physical, attitudinal or behavioural characteristic that can take on different values.

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6
Q

discrete observation

A

observed data point that can take on only specific values (eg. whole numbers}; no other values can exist between these numbers

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7
Q

continuous observation

A

observed data points that can take on a full range of values (i.e. numbers out to many decimal points}; an infinite number of potential value exists.

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8
Q

nominal variable

A

a variable used for observations that have categories, or names, as their values

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9
Q

ordinal variable

A

a variable used for observations that have rankings as their values

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10
Q

interval variable

A

a variable used for observations that have numbers as their values; the distance (or interval} between pairs of consecutive numbers is assumed to be equal.

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11
Q

ratio variable

A

a variable that meets the criteria for an interval variable but also has a meaningful zero point.

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12
Q

scale variable

A

a variable that meets the criteria for an interval variable or a ratio variable.

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13
Q

level

A

a discrete value or condition that a variable can takie on.

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14
Q

independent variable

A

a variable that we either manipulate or observe to determine its effects on the dependent variable.

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15
Q

dependent variable

A

the outcome variable that we hypothesize to be related to, or caused by, changes in the independent variable.

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16
Q

confounding variable

A

a variable that systematically varies with the independent variable so that we cannot logically determine which variable is at work; aka a confound.

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17
Q

reliability

A

the consistency of a measure

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18
Q

validity

A

the extent to which a test actually measures what it was intended to measure

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19
Q

hypothesis testing

A

the process of drawing conclusions about whether a particular relation between variables is supported by the evidence.

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20
Q

operational definition

A

the operations or procedures used to measure or manipulate a variable.

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21
Q

correlation

A

an association between two or more variables

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22
Q

random assignment

A

the protocol established for an experiment whereby every participant in a study has an equal chance of being assigned to any of the groups, or experimental conditions, in the study.

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23
Q

experiment

A

a study in which participants are randomly assigned to a condition or level of one or more independent variables.

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24
Q

between groups research design

A

an experimental design in which participants experience one, and only one, level of the independent variable.

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25
Q

within groups research design

A

an experimental design in which all participants in the study experience the different levels of the independent variable; also called a repeated measures design.

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26
Q

data ethics

A

a set of principle related to all stages of working with data - research design, data collection, statistical analyses, interpretation of analyses, and reporting of outcomes.

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27
Q

open science

A

an approach to research that encourages collaboration and includes the sharing of research methodology, data, and statistical analyses in ways that allow others to question and even to try to recreate findings.

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28
Q

preregistration

A

a recommended open-science practice in which researchers outline their research design and analysis plan before conducting a study.

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29
Q

HARKing

A

Hypothesizing After the Results are Known; an unethical practice in which researchers change their hypotheses to match their findings

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30
Q

raw score

A

a data point that has not yet been transformed or analyzed.

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31
Q

frequency distribution

A

a distribution that describes the pattern of a set of numbers by displaying a count or proportion for each possible value of a variable.

32
Q

frequency table

A

a visual depiction of data that shows how often each value occurred - that is, how many scores were at each value. Values are listed in the first column, and the numbers of individuals with scores at that value are listed in the second column.

33
Q

outlier

A

an extreme score that is either very high or very low in comparison with the rest of the scores in a sample.

34
Q

grouped frequency table

A

a visual depiction of data that reports the frequencies within a given interval rather than the frequencies for a specific value.

35
Q

histogram

A

a graph that looks like a bar graph but depicts just one variable, usually based on scale data, with the values of the variables on the x axis and the frequencies on the y.

36
Q

normal distribution

A

a specific frequency distribution in the shape of a bell-shaped, symmetric, unimodal curve.

37
Q

skewed distribution

A

a distribution in which one of the tails of the distribution is pulled away from the center.

38
Q

positively skewed

A

an asymmetric data distribution whose tail extends to the right, in a positive direction.

39
Q

floor effect

A

a situation in iwhich a constraint prevents a variable from taking on values below a certain point.

40
Q

negatively skewed

A

an asymmetric distribution whose tail extends to the left, in a negative direction

41
Q

ceiling effect

A

a situation in which a constraint prevents a variable from taking on values above a given number.

42
Q

scatterplot

A

a graph that depicts the relation between two scale variables. The values of each variable are marked along the two axes, and a mark is made to indicate the intersection of two scores for each participant.

43
Q

linear relation

A

a relation between two variables best described by a straight line.

44
Q

nonlinear relation

A

a relation between variables best described by a line that breaks or curves in some way.

45
Q

line graph

A

a graph used to illustrate the relation between two scale variables; sometimes the line represents the predicted y scores for each x value, and sometimes the line represents change in a variable over time.

46
Q

time plot/time series plot

A

a graph that plots a scale variable on the y axis as it changes over an increment of time (ex. second, day, century} labeled on the x axis.

47
Q

bar graph

A

a visual depiction of data when the independent variable is nominal or ordinal and the dependent variable is scale. The height of each bar typically represents the average value of the dependent variable for each category.

48
Q

Pareto chart

A

a type of bar graph in which the categories along the x axis are ordered from highest bar on the left to lowest bar on the right.

49
Q

dot plot

A

a graph that displays each data point in a sample, with the range of scores along the x axis and a dog for each data point above the appropriate value.

50
Q

pictoral graph

A

a visual depiction of data typically used for an independent variable with very few levels (categories} and a scale dependent variable. Each level uses a picture of symbol to represent its value on the scale dependent variable.

51
Q

pie chart

A

a graph in the shape of a circle with a slice for every level (category}, the size of each slice represents the proportion of each level.

52
Q

chartjunk

A

any unnecessary information of feature in a graph that distracts from a viewer’s ability to understand the data.

53
Q

moire vibration

A

any patterns in a graph that create a distracting impression of vibration and movement; a form of chartjunk.

54
Q

grid

A

a form of chartjunk that takes the form of a background pattern, almost like graph paper, on which the data representations, such as bars, are superimposed.

55
Q

duck

A

a form of chartjunk in which a feature of the data has been dressed up in a graph to be something other than merely data.

56
Q

defaults

A

the options that a software designer has preselected. They are the built-in decisions that the software will implement if you do not instruct it otherwise.

57
Q

violin plot

A

a graph shaped like a violin that includes information about a distribution’s middle score and overall variability.

58
Q

central tendency

A

a descriptive statistic that best represents the centre of a data set, the particular value that all the other data seem to be gathering around

59
Q

mean

A

the arithmetic average of a group of scores. It is calculated by summing all the scores and dividing by the total number of scores.

60
Q

statistic

A

a number based on a sample taken from a population; it is usually symbolized by a latin letter.

61
Q

parameter

A

a number based on the whole population; it is usually symbolized by a greek letter.

62
Q

median

A

the middle score of all the scores in a sample when the scores are arranged in ascending order. If there is no middle score, the median is the mean of the two middle scores.

63
Q

mode

A

the most common score of all the scores in a sample.

64
Q

unimodal

A

a term for a distribution that has one mode, or most common score.

65
Q

bimodal

A

a term for a distribution that has two modes, or two most common scores

66
Q

multimodal

A

a term for a distribution that has more than two modes, or most common scores.

67
Q

variability

A

a numerical way of describing how much spread there is in a distribution.

68
Q

range

A

a measure of variability calculated by subtracting the lowest score (the minimum} from the highest score {the maximum}

69
Q

interquartile range

A

a measure of the difference between the first and third quartiles of a data set.

70
Q

first quartile

A

the 25th percentile of a data set.

71
Q

third quartile

A

the 75th percentile of a data set.

72
Q

variance

A

the average of the squared deviations from the mean.

73
Q

deviation from the mean

A

the amount that a score in a sample differs from the mean of the sample; also called deviation.

74
Q

sum of squares

A

the sum of each score’s squared deviation from the mean, symbolised as SS.

75
Q

standard deviation

A

the square root of the average of the squared deviations from the mean; the typical amount that each score varies, or deviates, from the mean.

Data Analysis (5 decks)

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