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Research Design Human Movement 2032 > WEEK #3 - research methods > Flashcards

WEEK #3 - research methods Flashcards

1
Q

how many levels of measurement are there ?

A

4

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2
Q

what are the four levels of measurement ?

A
  • nominal
  • original
  • interval
  • ratio
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3
Q

define nominal data :

A
  • categorial data with no implicit ordering
  • cannot be added, subtracted, multiplied or divided
  • can be summarized using mode only
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4
Q

define ordinal data :

A
  • categorial data with implicit (or explicit) ordering
  • unequal distance between points
  • cannot be added, subtracted, multiplied or divided
  • can be summarized with median or mode
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5
Q

define interval data :

A
  • continuous (equal distance between points)
  • no meaningful zero
  • can be added or subtracted
  • cannot be multiplied or divided
  • can be summarized with mean, median or mode
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6
Q

define ratio data :

A
  • continuous (equal distance between points)
  • meaningful zero
  • can be added, subtracted, multiplied and divided
  • can be summarized with mean, median, or mode
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7
Q

give an example of nominal data :

A

“25 animals” (10 dogs and 15 cats)

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8
Q

give an example of ordinal data :

A

“positions in a race : 1st, 2nd, 3rd”

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9
Q

give an example of interval data :

A

temperature in celcius

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10
Q

give an example of ratio data :

A

temperature in Calvin

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11
Q

which level of measurement has no meaningful zero ?

A

interval data

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12
Q

which level of measurement has a meaningful zero ?

A

ratio data

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13
Q

when might you be able to treat ordinal as interval data ?

A
  • you are aggregating multiple items
  • the underlying construct is continuous
  • the measurement instrument is reliable
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14
Q

what are the three M’s of central tendency ?

A

mean, median and mode

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15
Q

what is mean ?

A

the arithmetic average of the data

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16
Q

what is median ?

A

the point that divides the data in half and the 50th percentile

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17
Q

what is mode ?

A

the most frequently occurring value

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18
Q

which central tendency is “ total all the results and divide the number of units or “n” of the sample” ?

A

mean

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19
Q

which central tendency is “the exact middle score in a data-set and list all scores in numerical order, and then locate the score in the centre of the sample”

A

median

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20
Q

does median ignores the outliers compared to a average ?

A

yes ignores the outliers

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21
Q

which central tendency is “the most repeated score in the set of results, 15 is the most repeated score and is labeled the mode and if you have a “tie” for “most repeated score”, you will have more than one mode”

A

mode

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22
Q

in regards to normality and central tendency, what does it mean if the distribution is normal ?

A

the mean, median and mode are all equal (bell-shaped)

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23
Q

what are the three factors of dispersion ?

A
  • range
  • standard deviation
  • coefficient of variation
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24
Q

why do we use range :

A

good for an intuitive description of minimum and maximum values in a data set

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25
Q

why do we use coefficient of variation ?

A

a useful way of comparing standard deviations across populations with different means or units

25
Q

why do we use standard deviation ?

A

more accurate/detailed description of dispersion the takes “outliers” into account

26
Q

define range :

A

the range is the difference between the highest and th lowest scores within a variable

27
Q

define standard deviation :

A

a value that shows the relation the individual scores have to the mean of the sample

(if scores are said to be standardized to a normal curve, then there are several statistical techniques that can be used to analyze the data set)

28
Q

TRUE OR FALSE

SD is calculated across all scores as the square root of the sum of the squared deviations from the mean, divided by the number of scores

A

TRUE

29
Q

what do we represent the population value with ?

A

the greek letter sigma Σ

30
Q

what do we represent the sample value with ?

A

the letter “s”

31
Q

TRUE OR FALSE

the standard deviation of a measure is dependent upon its scale (the magnitude of the values within the data)

A

TRUE

32
Q

what is distributional shape ?

A

Measures of shape describe the distribution (or pattern) of the data within a dataset

33
Q

what is normal distribution ?

A
  • sometimes called a “bell curved”
  • upper and lower halves perfectly symmetrical
  • most common normal distribution is the standard normal distribution
34
Q

TRUE OR FALSE

for a normal distribution we see a mean, median and mode of 0 and standard deviation of 1

A

TRUE (only the case in standard normal distributions)

35
Q

what is the empirical rule ?

A

a statistical rule that states that almost all observed data for a normal distribution will fall within three standard deviations

36
Q

describe the three points of the empirical rule :

A
  • 68% of the data falls within 1 SD of the mean
  • 95% of the data falls within 2 SD of mean
  • 99.7% of the data falls within 3 SD of mean
37
Q

TRUE OR FALSE

causation does equal correlation

A

FALSE

it does not

38
Q

describe the statement “causation doesn’t equal correlation”

A

refers to the inability to legitimately deduce a cause-and-effect relationship between two events or variables solely on the basis of an observed association or correlation between them

39
Q

what does SD stand for ?

A

standard deviation

40
Q

what are skewness ?

A

a measure of the asymmetry of the distribution

41
Q

what does the skewness graph look like ?

A

extent to which one “tail” is longer than the other

42
Q

what does a positive skew look like ?

A

right tail longer

43
Q

what does a negative skew look like ?

A

left tail longer

44
Q

generally with a - skew ; what does the mean with median and mean ?

A
  • skew = median > mean
45
Q

generally with a = skew ; what does that mean with the median and mean

A

= skew = mean > median

46
Q

what is kurtosis ?

A

measures the peak

47
Q

what are the three kurtotic distributions have non-normal “peaks” :

A
  • platykurtotic
  • leptokurtotic
  • mesokurtotic
48
Q

what does “platykurtotic” mean ?

A

“flat” : highly negative kurtosis

49
Q

what does “leptokurtotic” mean ?

A

“pointed” : highly positive kurtosis

50
Q

what does “mesokurtotic” mean ?

A

“no” kurtosis - ‘normal’ distribution

51
Q

describe in simple terms the difference between kurtosis and skewness :

A

skewness measures the tails of the distribution, and kurtosis measures the peak

52
Q

TRUE OR FALSE

kurtotic distributions have non-normal “peaks”

A

TRUE

53
Q

what are outliers ?

A

are values that fall substantially outside the range of most other values in the data

54
Q

how does one identify outliers ?

A

recall that the empirical rules states that 99.7% of the data will fall within 3 SD of the mean

55
Q

what are the three graphical summaries of data ?

A
  • bar graphs and histograms
  • line graphs
  • box plots
56
Q

what is a histogram ?

A

compares multiple measurements of the same variable (e.g. describing the age range in sample)

57
Q

what is a bar graph ?

A

compares multiple variables (e.g. the relative frequency of test usage within a group of practitioners)

58
Q

in simplest terms whats the difference between a histogram and a bar graph ?

A

a histogram has same one variables while a bar graph has multiples variables

59
Q

what is stem and leaf ?

A
  • basically contracted as a vertical histogram
  • shows raw data and gives rough idea of dispersion
  • very old school
  • print bar graphs back in the day
60
Q

when do we use and see line graphs ?

A

often used to convey temporal information

61
Q

TRUE OR FALSE

line graphs should not be used for discrete variables ?

A

TRUE

Research Design Human Movement 2032 (11 decks)

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