Lecture 5: Descriptive Stats Flashcards

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1
Q

variable (noun)

A

an element , feature, or factor that is liable to vary or change

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2
Q

two types of variables

A

math & computing

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3
Q

math variable

A

quantity during calculation is assumed to vary

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4
Q

computing variable

A

data item that may take on more than 1 value during the run time of the program

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5
Q

scales of measurement: data types

A
  1. nominal
  2. ordinal
  3. continuous
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6
Q

nominal measurement scale

A

based on the classification of an observation according to the group to which it belong – a process of categorization

EX: gender, political party, marital status

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7
Q

ordinal measurement scale

A

based on the classification of an observation according to its relationship to other observations

EX: poor-fair-good scale

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8
Q

types of continuous measurement scales

A

interval & ratio

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9
Q

continuous interval measurement scale

A

equal units of measurements, distance between two numbers are known, 0 is arbitrary

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10
Q

uneven interval measurement scale

A

number used but they do NOT have to represent ‘true numbers’ that can be added/subtracted

nominal or ordinal

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11
Q

continuous ratio measurement scale

A

equal units of measurement & a TRUE 0 at its origin

EX: mass & time

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12
Q

population

A

greek symbols

constant

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13
Q

samples

A

roman characters

variable

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14
Q

mode

A

most often

best for: nominal

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15
Q

median

A

in the middle

best for: ordinal

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16
Q

mean

A

average

best for: interval/ratio

17
Q

range

A

=X max - X min

18
Q

inter-quartile range

A

= X 25th percentile - X 50th percentile

19
Q

variance (S^2, MS)

A

average of square of deviations from mean divided by degrees of freedom (N-1)

20
Q

standard deviation (SD)

A

“positive variance”

square root of variance (MS^1/2)

21
Q

coefficient of variation (CV)

A

percentage of spread (unit-less)

=100% x (SD/mean)

22
Q

central limit theorem

A

the sample distribution of the mean of any independent, random variable will be normal if the sample size is large enough (30-40)

23
Q

conditions for more sample points

A

more close samples to normal distribution

24
Q

conditions for less sample points

A

more close original population to normal distribution

25
Q

standard error mean (SE)

A

standard deviation of sample means from population mean

= SD/(N^1/2)

26
Q

SD VS SE

A

SD- measures variability of individual subjects around mean

SE- assessed how accurate a sample mean reflects population mean