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biostats 23 > exam 1 > Flashcards

exam 1 Flashcards

1
Q

population

A

entire collection of all elements in which we are interested

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1
Q

sample

A

portion of population collected under homogenous conditions

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2
Q

simple random sample

A

-every member of the population has the same chance of being included in the sample
-members of the sample are chosen independently of eachother

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3
Q

t/f? categorical/ qualitative data can only be ordinal

A

false. categorical data can be ordinal or non-ordinal (nominal)

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4
Q

nominal variables are the (lowest/highest) level qualitative variable and the (lowest/highest) level of measurement

A

lowest, lowest

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5
Q

nominal measures

A

simply name, group, type, classify or categorize values of a variable
-only categorized

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6
Q

ordinal variables

A

-second level of measurement and highest level of qualitative variables
-typically used to order/ rank values of variables in addition to naming values
-categorized and ranked

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7
Q

ordinal scales

A

have all characteristics of nominal variables but also order/ rank data

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8
Q

example of ordinal

A

-agreement: strongly agree, agree, neither agree nor disagree, disagree, strongly disagree
-taste: scrumptious, okay, bland, a dog wouldn’t eat it

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9
Q

Discrete data

A

numerical type of data that includes whole concrete numbers with specific and fixed data values determined by counting
-concrete fixed numbers

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10
Q

continuous data

A

numerical type of data that includes complex numbers and varying data values measured over a particular time interval.
-always varying

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11
Q

example discrete data

A
  • number of boys in a family
    -number of deer killed on I-79
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12
Q

examples continuous data

A

-time
-weight
-height

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13
Q

variables of interest denoted by

A

capital letters

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14
Q

actual values denoted by

A

lower case letters/ subscript characters

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15
Q

ungrouped frequency

A

normally used for categorical data

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16
Q

grouped frequency

A

quantitative data combined in 5-15 classes depending on the amount of data

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17
Q

how should frequency distributions be graphed

A

as a histogram (bar chart)

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18
Q

frequency distribution

A

number of occurrences of each value in data set

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19
Q

relative frequency distributions

A

-frequency divided by the sample size
-tells you percentage in each class

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20
Q

cumulative frequency distribution

A

-counts the number of values at or below the upper class limit of each grouping

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21
Q

cumulative relative frequency

A

-percentage of values at or below the upper class limit

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22
Q

5 columns of complete frequency table

A

-group
-frequency
-relative frequency
-cumulative frequency
-cumulative relative frequency

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23
Q

how to find relative frequency

A

frequency/total

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24
Q

how to find cumulative frequency

A

adding up relative frequency

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25
Q

how to find cumulative relative frequency

A

add up relative frequency

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26
Q

symmetric frequency distribution shape

A

left half of graph mirror image of left half of graph

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27
Q

positive skew

A

tail of graph to right

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28
Q

negative skew

A

tail of graph to left

29
Q

bimodal

A

two peaks on graph

30
Q

where is mean median and mode on skewed graph

A

mode at peak on graph
-median after mode towards tail
-mean after median towards tail

31
Q

statistically unethical diversion

A

-changing scales on one or both axes
-truncating frequency axis and starting frequency axis at number greater than zero

32
Q

mean

A

average, point of balance on data

33
Q

median

A

-middle value of sorted data (lowest to highest)

34
Q

median is (greater than/ less than) mean when there is right skewed data

A

less than

35
Q

symbol for mean

A

y with straight line above

36
Q

symbol for median

A

y with tilde above

37
Q

how to get trimmed mean

A

-delete upper and lower 10 percent of range and recalculate mean

38
Q

measures of dispersionn

A

-range
-Q0
-Q1
-Q2
-Q3
-Q4
-IQR

39
Q

how to find range

A

largest observation - smallest observation

40
Q

Q1

A

median of first half of data

41
Q

Q2

A

median of data

42
Q

Q3

A

median of second half of data

43
Q

Q0

A

minimum

44
Q

Q4

A

maximum

45
Q

IQR

A

Q3-Q1

46
Q

how to find upper and lower fence

A

upper: Q3 +1.5(IQR)
lower: Q1 - 1.5(IQR)

47
Q

how does one indicate an outlier

A

with an asterisks

48
Q

what is standard deviation used to measure

A

typical distance of observations from the mean

49
Q

which form of standard deviation is most accurate

A

computational standard deviation

50
Q

what is the formula for coefficient of variation

A

(standard deviation/ mean ) x 100%

51
Q

what does the coefficient of variation measure

A

-the amount of variability relative to the value of the mean
-usually used for comparisons of two data sets measured on different scales

52
Q

what is the empirical rule

A

for unimodal unskewed distributions:
- 68% observations within 1 sd of the mean
-95% of observations within 2 sd of the mean
-greater than 99% observations within 3 sd of the mean

53
Q

what is statistical inferencing used for

A

-drawing conclusions about a population based on observations in a sample

54
Q

density curves

A

-a smooth curve re[resenting a frequency distribution

55
Q

what is the total area of a density curve

A

1

56
Q

two variables of proportion statistic estimate parameters

A

p hat (sample proportion) is about equal to p (population proportion)

57
Q

two variables of mean statistic estimate parameters

A

y with bar above (sample mean) about equal to mu (fancy u = population mean)

58
Q

two variables of standard deviation statistic estimate parameters

A

s (sample standard deviation) is about equal to sideways 6 aka sigma (population standard deviation)

59
Q

three methods of counting techniques

A

-multiplication rule of counting
-permutations
-combinations

60
Q

Multiplication rule of counting

A

-if event A can occur n ways and event B can occur m ways, then in sequence they can occur in mn ways
-ex: A=5 B=3 C=4, probability of ABC= 60

61
Q

permutations

A

-number of ways to arrange in order n distinct objects, taking them r at a time
ex: 5 people in 3 chairs
-5 ppl could sit in chair 1, 4 in 2, 3 in 3
-still have 2 people left over so formula = 5!/(5-3)!

62
Q

combinations

A

-the number of unordered ways to pick n distinct objects taking them r at a time
-formula: n!/(r!(n-r)!)
-ex: 6 ppl sitting in 3 chairs, how many ways can three people be chosen in any order:
-permutations/ # ways people can be arranged:
-(6x5x4)/(6)= 120/6=20

63
Q

probability

A

numerical quantity that expresses likelihood/ chance that particular event will occur

64
Q

P(E)

A

-number of ways event E can happen/ total possibilities

65
Q

Notation of P(E)

A

-P(E)-probability of event E happening
-E={O1, O2, O3 etc} where Oi= outcome i
-outcomes mutually exclusive (cant occur at same time)
– P(E)= P(O1)+(PO2)+…
-probability event always between 0-1
-s denotes sample space: all possible outcomes
-P(E^c)= 1-P(E)

66
Q
  • 5% of the population has a certain
    disease
  • Test for the disease has an 80% chance of
    detecting a person actually has it.
  • And a 90% chance of detecting a person
    that does not have it.
  • Q: Given that a person tests positive,
    what is the probability they have the
    disease?
A

probability tree
-Yes(have disease .05), No (dont have disease .95)
-Yes (test positive .8), Yes (test negative .2)
-No (test positive .1), No (test negative .9)
-have disease : .05 .8= .04
- test positive = yes(+) no (+)= (.05.8)(.1*.95)= .135
-have disease: .04
-probability= .04/.135= 29.6%

67
Q

density curve x probability

A

for any two numbers a and b, Area under density curve between a and b is equal to the proportion of Y values between a and b

68
Q

random variable

A

variable whose outcome depends on outcomes of chance operation
-probability distribution-list of random variable and probabilities associated with possible outcomes

69
Q

requirements for binomial model

A

-series of n trials
-each trial is identical and can result in success or failure
-probability of success remains constant trial to trial
-each outcome is independent of other outcomes
-

70
Q

Carrier of TB has a 10% chance of passing
disease to anyone in close contact. Suppose the
carrier comes in close contact with 10 people
what is the probability that 4 get TB?

A

(10!)/(4! (10-4)!) x (.10)^4 x (.90)^6= .01116

biostats 23 (1 decks)

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