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

WEEK #3 - research methods Flashcards

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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
why do we use coefficient of variation ?
a useful way of comparing standard deviations across populations with different means or units
25
why do we use standard deviation ?
more accurate/detailed description of dispersion the takes "outliers" into account
26
define range :
the range is the difference between the highest and th lowest scores within a variable
27
define standard deviation :
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
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
TRUE
29
what do we represent the population value with ?
the greek letter sigma Σ
30
what do we represent the sample value with ?
the letter "s"
31
TRUE OR FALSE the standard deviation of a measure is dependent upon its scale (the magnitude of the values within the data)
TRUE
32
what is distributional shape ?
Measures of shape describe the distribution (or pattern) of the data within a dataset
33
what is normal distribution ?
- sometimes called a "bell curved" - upper and lower halves perfectly symmetrical - most common normal distribution is the standard normal distribution
34
TRUE OR FALSE for a normal distribution we see a mean, median and mode of 0 and standard deviation of 1
TRUE (only the case in standard normal distributions)
35
what is the empirical rule ?
a statistical rule that states that almost all observed data for a normal distribution will fall within three standard deviations
36
describe the three points of the empirical rule :
- 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
TRUE OR FALSE causation does equal correlation
FALSE it does not
38
describe the statement "causation doesn't equal correlation"
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
what does SD stand for ?
standard deviation
40
what are skewness ?
a measure of the asymmetry of the distribution
41
what does the skewness graph look like ?
extent to which one "tail" is longer than the other
42
what does a positive skew look like ?
right tail longer
43
what does a negative skew look like ?
left tail longer
44
generally with a - skew ; what does the mean with median and mean ?
- skew = median > mean
45
generally with a = skew ; what does that mean with the median and mean
= skew = mean > median
46
what is kurtosis ?
measures the peak
47
what are the three kurtotic distributions have non-normal "peaks" :
- platykurtotic - leptokurtotic - mesokurtotic
48
what does "platykurtotic" mean ?
"flat" : highly negative kurtosis
49
what does "leptokurtotic" mean ?
"pointed" : highly positive kurtosis
50
what does "mesokurtotic" mean ?
"no" kurtosis - 'normal' distribution
51
describe in simple terms the difference between kurtosis and skewness :
skewness measures the tails of the distribution, and kurtosis measures the peak
52
TRUE OR FALSE kurtotic distributions have non-normal "peaks"
TRUE
53
what are outliers ?
are values that fall substantially outside the range of most other values in the data
54
how does one identify outliers ?
recall that the empirical rules states that 99.7% of the data will fall within 3 SD of the mean
55
what are the three graphical summaries of data ?
- bar graphs and histograms - line graphs - box plots
56
what is a histogram ?
compares multiple measurements of the same variable (e.g. describing the age range in sample)
57
what is a bar graph ?
compares multiple variables (e.g. the relative frequency of test usage within a group of practitioners)
58
in simplest terms whats the difference between a histogram and a bar graph ?
a histogram has same one variables while a bar graph has multiples variables
59
what is stem and leaf ?
- 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
when do we use and see line graphs ?
often used to convey temporal information
61
TRUE OR FALSE line graphs should not be used for discrete variables ?
TRUE
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