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Pharm > Statistics - Exam 4 > Flashcards

Statistics - Exam 4 Flashcards

1
Q

definition of statistics

A

the science of assembling, classifying, tabulating, and analyzing data of a numerical nature to present significant information about a given subject

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2
Q

definition of descriptive statistics

A

a way of summarizing data from population or sample

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3
Q

definition of statistical inference

A

comparison of data (outbound of objectives)

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4
Q

definition of data

A

a collection of information; a set of values of qualitative or quantitative variables

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5
Q

definition of qualitative data

A

non-numeric data

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6
Q

definition of quantitative data

A

numeric data

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7
Q

definition of measurement

A

assigning numbers to observations according to preset rules

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8
Q

definition of variable

A

a measured characteristic that can have various values or levels

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9
Q

definition of discrete variables

A

quantitative, can have only certain values (whole numbers)

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10
Q

definition of continuous variables

A

quantitative, can have any value (whole numbers or fractions)

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11
Q

definition of binary variables

A

have only 2 possible values (yes/no)

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12
Q

what are the 2 types of variables

A

qualitative and quantitative

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13
Q

what are the 3 types of qualitative variables

A

binary, nominal, ordinal

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14
Q

example of qualitative binary variable

A

death yes or no, presence of blood in urine

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15
Q

example of qualitative nominal variable

A

type of husbandry building in the farm

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16
Q

example of qualitative ordinal variable

A

score of judges at a dog show

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17
Q

what are the 2 types of quantitative variables

A

discrete & continuous

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18
Q

example of quantitative discrete variable

A

RBC count, parity of cattle, litter size of dogs

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19
Q

example of quantitative continuous variable

A

weight of calves at birth, girth of bulls, blood pressure of cats

20
Q

definition of population

A

an entire group of observations that might have at least one characteristic in common

21
Q

definition of sample

A

a group of elements selected from the total population

22
Q

definition of parameter

A

a characteristic of a population

23
Q

definition of statistic

A

a characteristic of a sample

24
Q

descriptive statistics include

A

text & graphs

25
Q

definition of absolute frequency

A

total number of observations/events (exact number of something counted)

26
Q

definition of relative frequency

A

proportion of observations/events (percentage)

27
Q

definition of tabular cumulative frequency distribution

A

frequency of the scores including the frequency of the previous scores, should be used for quantitative/ordinal variables only

28
Q

definition of data distribution

A

graphical representation of the frequency distribution (i.e.: histogram)

29
Q

the normal distribution is

A

Gaussian distribution, shaped like a bell, symmetric

30
Q

quantitative data can be described with only 2

A

parameters (location- measure of central tendency & dispersion)

31
Q

definition of a mean

A

the numerical average of a dataset

32
Q

definition of a median

A

the middle value of a data set. It is the actual middle number with an odd number of data points, and it is the mean of the middle two numbers with an even number of data points

33
Q

definition of a mode

A

the most frequent value in a dataset. can have more than one mode or no mode at all

34
Q

3 main measures of variability

A

range, variance, standard deviation

35
Q

definition of range

A

the range is the difference between the highest data value and the lowest value (difference with the book)

36
Q

definition of variance

A

how far the distribution is spread out from the mean

37
Q

definition of standard deviation

A

square root of the variance, variability of the variable distribution for the sample or for the population

38
Q

standard deviation equation (SD) =

A

square root of sigma ^2

39
Q

normal distribution (specificity) =

A

vertical symmetry, mean=median=mode, 50% greater than and 50% less than

40
Q

definition of standard error

A

standard deviation of the variable “mean”; allows us to estimate the confidence interval of the mean

41
Q

histogram used to represent

A

grouped frequency data

42
Q

equation for variance (sigma^2) =

A

sum (x-mu)^2 / N

mu = mean

43
Q

pie graph used to represent

A

a categorical variable; same data as a bar plot, plot frequency of 1 category

44
Q

boxplot used to

A

plot difference of quantitative variables between several/different categories

45
Q

scatter plot used to

A

plot 2 quantitative continuous variables (one point is one observation)

46
Q

line plot used to

A

plot evolution of a quantitative variable in “time”, continuous

Pharm (15 decks)

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