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Public Health > Biostats 1- Basic Concepts > Flashcards

Biostats 1- Basic Concepts Flashcards

1
Q

This is the variation in the values of a sample statistic when multiple samples are taken from the same population.

A

Random sampling variation

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2
Q

This is the selection of subjects from a population to participate in a study.

A

Sampling

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3
Q

What is the goal of sampling?

A

To obtain a representative sample that mimics characteristics of the population.

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4
Q

This is the type of sampling where each individual in the population has an equal chance of being selected to participate.

A

Random sampling

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5
Q

This is the table you use in random sampling where u assign each person a # from 100 and then to randomly select from it.

A

Random # table

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6
Q

This is the type of sampling where u select a starting point and then select every K element in the population.

A

Systematic sampling

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7
Q

To do a systematic sampling, how do arrange individuals?

A

In some ordering scheme and then selecting at regular intervals through that ordered list.

like interviewing every 5th pt for 1 week in a study.

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8
Q

This is the type of sampling where u subdivide the population into subgroups that share the same characteristic, and then draw a random sample from each stratum.

A

Stratified sampling

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9
Q

This is the type of sampling where u use results that are readily available or easily accessible, like phone calls and mall questionairres.

A

Convenience sampling

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10
Q

This is the type of sampling where u divide the population into sections and then randomly select some of those clusters (choose all members of the selected cluster)

A

Cluster sampling

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11
Q

So what’s the difference between stratified and cluster sampling? both take sections of a popualtion…

A

in cluster, you sample ALL of the people in the selected strata

in stratified, you select a few from each strata.

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12
Q

What are the 2 ways u can classify data into variables?

A

Sacle of measurement

Arrangement in a study design

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13
Q

What are the 2 ways to split up the scale of measurement when classifying data?

A

Qualitative and quantitative

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14
Q

Further down the rabbit hole… What are the 2 ways to split up the qualitative (categorical) variables?

A

Nominal and ordinal.

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15
Q

Which categorical (qualitative) variable does this belong under (nominal or ordinal)?

Republican, Democrat, Green party

A

Nominal

theres no order to the political parties

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16
Q

Which categorical (qualitative) variable does this belong under (nominal or ordinal)?

Hotness of a chili pepper, age group, pain rating

A

Ordinal

theres an order, so u rank the values in order.

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17
Q

If there is a categorical (qualitative) version, what is the other type of scale of measurement when classifying data?

A

Continuous (quantitative) variables

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18
Q

What are the 2 subsections of quantitative variables?

A

Intervals and Ratios

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19
Q

Which continuous (quanitative) variable does this belong under (Interval or Ratio)?

Temperature

A

Interval

can be negative

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20
Q

Which continuous (quanitative) variable does this belong under (Interval or Ratio)?

BPM, BP, height, weight

A

Ratio

never negative

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21
Q

Which values are the input and manipulated in a study design (independent or dependent variables)?

A

Independent variables

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22
Q

Which axis are independent variables always placed on a graph (X or Y)?

A

X-axis

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23
Q

This is the extento to which an instrument will provide the same values when repeatedly re-measuring.

A

Reliability

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24
Q

This is the subtype of reliability where there is different people, same test.

A

Inter-rater reliability

between people, like people checking their weight

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25
Q

This is the subtype of reliability where there is the same people, same test, different times.

A

Test-retest

like checking ur own weight every morning on the same scale

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26
Q

This is the subtype of reliability where there are different questions, same constuct

A

Internal consistency

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27
Q

This is the extento to which a measurement, tool, or study is an accurate representation of the concept it is intended to measure.

A

Validity

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28
Q

Can validity be quantified?

A

No

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29
Q

This is the subtype of validity where the extent to which the actual measurements made by investigators are truly representative of what they are observing and measuring

A

Internal validity

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30
Q

So to whom does external validity apply?

A

Populations, settings, or treatments.

31
Q

This is the type of bias where there is systematic deviation form reality, and the samples or relsults are NOT representative of the population.

A

Statistical bias

32
Q

This is the type of statistical bias which occurs when the sample isnt representative of the population (not equal change of being selected), which lowers external validity.

A

Selection bias

Dewey defeats Truman

33
Q

What are the 2 ways of having selection bias?

A 
Migration bias (drop out)
non-response bias (dont participate)
34
Q

THis is the type of statistical bias which lacks proper blinding (investigator bias).

A

Review bias

like the MMR/autism study

35
Q

What is the most common way of having review bias?

A

Where only 1 person collects data/test results

reader/verification bias

36
Q

This is the type of statistical bias where hte pt or subject skews results due to knowledge of being tested.

A

Response/artificial bials

37
Q

What are the 3 preventative measure against bias?

A

Randomization
Double-blind experiments
Proper training in research

38
Q

This is a variable or factor that is anything other than the treatment that can cause or preclude the outcome of interest.

A

Confounding variable/factor

like in stress vs BP, know that other things that can change BP, so u wana reduce confounding factors

39
Q

This is the deviation of a measured value from the true meaning.

A

Measurement error.

40
Q

Which type of measurement error is harder to correct, random or systematic errors?

A

Random errors cuz u dont know whats causing the problem

41
Q

This is the discrepancy between the observed result and the true value.

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity
A

D. measurement error

42
Q

This is the lack of error, getting the correct result.

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity
A

A. accuracy

43
Q

This is the absence of a random error.

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity
A

E. precision

44
Q

This is a systematic error- independent of study size.

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity
A

B. bias

45
Q

This is the absence of bias (or absence of all error)

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity
A

G. validity

46
Q

These influence the outcome of interest.

A. Accuracy
B. Bias
C. Confounding
D. Measurement error
E. Precision
F. Reliability
G. Validity`
A

C. Confounding

47
Q

This is a table listing all the possible values and the # of occurences of each value in the sample.

A

Frequency distribution

48
Q

What kind of chart can u use to visualize the freuqency distribution for categorical variables?

A

Bar chart

49
Q

How many slices should a pie chart not exceed?

A

5-6

50
Q

This is the graph that can depict frequency distributions for quantitative data.

A

Histograms

51
Q

What plot can visualize the replationship between 2 quantitative variables?

A

Scatter plot

52
Q

Should you use stem and leaf plots for large or small data sets?

A

Small data sets

53
Q

In a box plot, what is depicted by the ends of the box?

A

interquartile range

54
Q

In a box plot, what is depicted by the midline inside the box?

A

Median

55
Q

In a box plot, what is depicted by the + symbol in the box?

A

Mean

56
Q

In a box plot, what is depicted by the whiskers?

A

2 SD from the mean

57
Q

In a box plot, what is depicted by the dots beyond the whiskers?

A

Outliers

58
Q

This is the measure where u add up all the data and divide by the total.

A

Mean

59
Q

This is the measure where u find the 1/2 way pt, where there is an equal # of variables on both sides.

A

Median

60
Q

This is the measure of the most frequent data in a set.

A

Mode

61
Q

This is the measure of how much variation exists in the data, and is comprised of the range, interquartile range, and the variance.

A

Measure of Dispersion

62
Q

What is the eqn for the variance?

A

E(obs - mean)^2/n

63
Q

If you take the square root of the variance, what do u get?

A

standard deviation

64
Q

This is the amt of variation in means of samples when repeated sampling is used from a popualtion.

A

Standard error

65
Q

What % of data is included within 1 SD in a bell curve?

A

68%

66
Q

What % of data is included within 2 SDs in a bell curve?

A

95%

67
Q

What % of data is included within 3 SDs in a bell curve?

A

99.7%

68
Q

If a distribution curve has a long right tail, is it a positive or negative skew?

A

Positive

69
Q

Which do u report in a skew: mean, median, or mode?

A

Median

70
Q

This is the measure of peekedness of a curve.

A

Kurtosis

71
Q

What is it called when a curve is peeked > 0?

A

Leptokurtic

72
Q

What is it called when a curve has 0 kurtosis?

A

Mesokurtic

73
Q

What is it called when a curve is peeked < 0?

A

Platykurtic

like a platypus. cuz it’s flat.

74
Q

What are the 5 abuses of descriptive statistics?

A 
Bad samples
Small samples
loaded questions ("does this dress make me look fat?")
Misleading graphs
Precise numbers

Public Health (14 decks)

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