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EPI LEC > Lesson 1-10 > Flashcards

Lesson 1-10 Flashcards

1
Q

Defining who or what is going to be studied means defining the

A

population

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2
Q

is a smaller set or a subset of the population

A

sample

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3
Q

occurs when certain members of the population are chosen so that the sample systematically misrepresents the population

A

biased sample

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4
Q

must be created where respondents are
listed and assigned a unique number.

A

sampling frame

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5
Q

Each subject in the population has the same chance of being selected

A

Simple random sampling

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6
Q

The sampling frame is divided into subgroups or strata and simple random samples are
conducted within the strata.

A

Stratified random sampling

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7
Q

The sampling frame is ordered, and a number s is selected so that every sth subject is
selected to be in the sample.

A

Systematic random sampling

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8
Q

is how information on the subjects will be collected.

A

Study Designs

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9
Q

Subjects are identified and followed for a specific period of time.

A

Prospective study

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10
Q

a type of medical research used to investigate the causes of disease and to establish links between risk factors and health outcomes.

A

Cohort study

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11
Q

An outcome is identified, after the data have already been collected.

A

Retrospective study

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12
Q

Study where previously collected
data are reviewed to determine whether any characteristics impacted the outcome.

A

Retrospective study

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13
Q

Study where Existing data are then obtained to determine what factors were
related to subjects becoming either a case or a control.

A

Case control study

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14
Q

those having the outcome

A

Case subjects

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15
Q

those not having the
outcome

A

control subjects

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16
Q

Data are collected at a particular time point and represent a cross-section of time.

A

Cross-sectional study

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17
Q

Variables whose measurements represent a limited set of possible values.

A

discrete variables

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18
Q

values can be expressed in either?

A

Numbers, characters, words

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19
Q

These are variables with different levels or categories whose order matters. Examples
include pain scores, stages of cancer, and educational attainment

A

Ordinal

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20
Q

These are categorical variables with different levels or categories whose order does
not matter. Examples are tooth color, marital status, and political affiliation.

A

Nominal

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21
Q

These are variables that can have only two levels.

A

Dichotomous

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22
Q

True or false: Sex is an example of Dichotomous variable

A

True

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23
Q

Variables whose measurements represent an unlimited set of possible values.

A

Continuous

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24
Q

These variables can take on only positive, whole number values.

A

Count

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25
Q

True or false: Continuous variables can have only numeric values.

A

True

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26
Q

The total number of subjects with a particular category or level

A

Counts

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27
Q

is simply the count for a category divided by the total number of subjects.

A

Proportions

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28
Q

is the proportion times 100

A

Percentages

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29
Q

It provides a description of the average response

A

measure of center

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30
Q

It provides a description of how varied the responses are

A

measure of spread

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31
Q

This is commonly used to describe the center of the responses.

A

Mean

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32
Q

True or false:
when extremely large or small values are present, the mean is a better measure of the center.

A

False, median is a better measure

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33
Q

These are numerical summaries that describe the sample.

A

Parameters

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34
Q

are the numerical
summaries that an investigator wants but cannot obtain directly because collecting data on the
entire population is not feasible.

A

Parameters

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35
Q

These are numerical summaries that describe the sample.

A

Statistics

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36
Q

What are the the basic sciences of public health.

A

Epidemiology and biostatistics

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37
Q

is about the understanding of disease development and the methods used to uncover the etiology, progression, and treatment of the disease.

A

Epidemiology

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38
Q

is collected to investigate a question

A

Information (data)

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39
Q

variable consists of a summary of the possible values the variable can have and the number of subjects with each of
these values.

A

distribution

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40
Q

distribution that uses counts to describe the number of subjects with a particular
value

A

frequency distribution

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41
Q

distribution that uses proportions to describe the
number of the subjects with a particular value

A

probability distribution

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42
Q

Two types of graphs are used to summarize categorical variables

A

pie charts and bar graphs.

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43
Q

can be presented using frequencies or proportions

A

Pie charts

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44
Q

describes how the pieces relate to the whole

A

Pie charts

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45
Q

They demonstrate how the categories within a variable relate to each other

A

Pie charts

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46
Q

are used to describe the
distributions of categorical variables.

A

Bar graphs

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47
Q

are used when a data has a variable with two options.

A

Binomial distributions

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48
Q

Binomial distributions are what type of variables

A

dichotomous

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49
Q

best describe the distribution of a continuous variable

A

Histograms

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50
Q

is a graphical representation of a variable in which the observed values are categorized, a bar is drawn for each category, and the number of participants in each category is represented by the height of the bar.

A

Histograms

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51
Q

It provides a quick picture of the distribution of a variable and it can be presented with counts or
proportions of participants.

A

Histograms

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52
Q

They provide information about how spread out the
responses are, which responses are common, which responses are in the center, and the overall
shape of the distribution.

A

Histograms

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53
Q

can be folded in half so that each half is close to a mirror image of the other

A

Symmetric distributions

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54
Q

This distribution has one mode or one most common value

A

unimodal

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55
Q

A distribution with two peaks can be

A

bimodal

56
Q

When the histogram is bell-shaped, unimodal, and symmetric, with the mean, median, and
most common value at the center at the peak, the data come from a _____

A

normal distribution.

57
Q

can be used to determine if observations are common or
extreme

A

empirical rule

58
Q

normal distribution is ___ skewed when the distribution has a tail that extends longer to
the left, that is, there is a set of observations with lower values than those of the majority of the
observed responses.

A

left

59
Q

A distribution is ___ skewed when the distribution has a tail that extends
longer to the right, that is, there is a set of observations with higher values than those of the
majority of the observed responses.

A

right

60
Q

is a discrete probability distribution whose possible values are whole numbers from 0 to infinity.

A

Poisson distribution

61
Q

are percentages of all the observations that are less than the value of interest.

A

Percentiles

62
Q

It is used to determine whether a particular value is common or rare.

A

Percentiles

63
Q

measurements occurs when multiple measurements are taken on the subject.

A

Variability

64
Q

If there is little measurement variability, the measurement has?

A

reliability

65
Q

The idea that samples may be different

A

sampling variability

66
Q

The value of the statistics and the number of times the statistics occur from all the possible samples is known as the?

A

distribution of samples or the sampling distribution

67
Q

It provides a description of all possible statistics obtained from samples

A

sampling distribution

68
Q

is the characterization of all sample means

A

central limit theorem

69
Q

According to this theorem, the distribution of the means obtained from all possible samples will result in a normally shaped distribution, in which the center of the distribution is the true parameter and one standard
deviation of the sampling distribution is the standard error of the mean.

A

central limit theorem

70
Q

This theorem holds true for large sample size.

A

central limit theorem

71
Q

is a basic and commonly used type of predictive analysis.

A

Linear regression

72
Q

It may be called an outcome variable, criterion variable, endogenous variable, or regressand.

A

dependent variable

73
Q

It can be called exogenous variables, predictor variables, or regressors

A

independent variables

74
Q

is the portion of the total variation in the dependent variable that
is explained by variation in the independent variable

A

Coefficient of Determination

75
Q

is often useful to attempt to represent data with the equation of a straight line in
order to predict values that may not be displayed on the plot.

A

line of best fit

76
Q

determined by the correlation between the two variables on a scatter plot

A

line of best fit

77
Q

is a statistical technique that can show whether and how strongly pairs of variables
are related.

A

Correlation

78
Q

If the correlation is greater than 0, then the variables are

A

positively correlated.

79
Q

If the correlation is less than 0, then the variables are said to be

A

negatively correlated

80
Q

If the correlation is exactly 0, such as for birthweight and birthday, then the variables are said to be

A

uncorrelated

81
Q

exists when high scores in one variable are associated with high scores in the second variable or low scores in one variable are associated with low scores in the other

A

POSITIVE CORRELATION

82
Q

exists when high scores in one variable are associated with low scores in the second or vice versa.

A

NEGATIVE CORRELATION

83
Q

exists when the points on the scatter diagram are spread in a random manner

A

ZERO CORRELATION

84
Q

all points lie on a straight line

A

PERFECT CORRELATION

85
Q

True or false:
A key thing to remember when working with correlations is never to assume a correlation
means that a change in one variable causes a change in another

A

True

86
Q

It seeks to find the relationship between two variables.

A

Correlation

87
Q

is commonly used for testing relationships between categorical variables.

A

Chi Square statistic

88
Q

The _______ of the Chi-Square test is that no relationship exists on the categorical variables in the population; they are independent.

A

null hypothesis

89
Q

The Chi-Square statistic is most commonly used to evaluate _________ when using a crosstabulation (also known as a bivariate table).

A

Tests of Independence

90
Q

________ presents the
distributions of two categorical variables simultaneously, with the intersections of the categories of the variables appearing in the cells of the table.

A

Crosstabulation

91
Q

The ___________ assesses whether
an association exists between the two variables by comparing the observed pattern of responses
in the cells to the pattern that would be expected if the variables were truly independent of each
other

A

Test of Independence

92
Q

Is student status (in-state versus out-of-state) associated with one’s eventual graduation
outcome (graduating versus not graduating)?
Answer: Chi-Square test of _____ _ ________

A

Independence

93
Q

To test a theory that people have no preference among four different outdoor activities,
you ask 100 people to select among jogging, bicycling, hiking, or swimming.
Answer: Chi-Square test of _____ _ ________

A

Goodness of fit

94
Q

A biostatistician would like to determine if the ratio of the blood type in the storage for
transfusions should be different in Hawaii from the main land. She collected a sample of
blood types of 10,000 people in Hawaii and that of 100,000 people in the mainland. She
wishes to see if the breakdown of blood types (A, B, AB and 0) is the same for both
populations.
Answer: Chi-Square test of _____ _ ________

A

Homogeneity

95
Q

A researcher wants to determine if scoring high or low on an artistic ability test depends
on being right or left-handed.
Answer: Chi-Square test of _____ _ ________

A

Independence

96
Q

A national organization wants to compare the distribution of level of highest education
completed (high school, college, masters, doctoral) for Republicans versus Democrats.
Answer: Chi-Square test of _____ _ ________

A

Goodness of fits

97
Q

A preservation society has the percentages of five main types of fish in the river from 10
years ago. After noticing an imbalance recently, they add some fish from hatcheries to the
river. How can they determine if they restored the ecosystem from a new sample of fish?
Answer: Chi-Square test of _____ _ ________

A

Goodness of fit

98
Q

is a way to find out if survey or experiment results are significant. In other
words, they help you to figure out if you need to reject the null hypothesis or accept the alternate
hypothesis

A

ANOVA test

99
Q

is used to compare two means from two independent (unrelated) groups using
the F-distribution

A

one way ANOVA

100
Q

null hypothesis for the test one way ANOVA is that the ______

A

two means are equal

101
Q

True or false: one way ANOVA will tell you that at least two groups were different from each other And which groups were different.

A

False, it won’t tell you which groups were different

102
Q

If the computed F value is greater than the tabulated F value, then the null hypothesis is

A

rejected

103
Q

If the computed F value is less than the tabulated F value, then the null hypothesis is

A

accepted

104
Q

is used when the research question involves the comparisons of means from more than two independent groups.

A

ANOVA

105
Q

It provides a statistical
test for determining whether there is enough evidence to reject the null hypothesis that all the
means are equal.

A

ANOVA

106
Q

It is the probability of the occurrence of a disease or other health outcome of interest during a specified period, usually one year

A

Risk

107
Q

is calculated by dividing the number who got the disease during the defined period by the total population of interest during that period.

A

Risk

108
Q

is the calculated ratio of incidence rates of a health condition or outcome in two groups of people, those exposed to a factor of interest and those not exposed.

A

Relative risk

109
Q

used to determine if exposure to a specific risk factor is associated with an increase, decrease, or no
change in the disease or outcome rate when compared to those without the exposure.

A

Relative risk

110
Q

is a statistical measure of the strength of the association between a risk factor and an
outcome.

A

Relative risk

111
Q

fundamental comparison of rates using a ratio in epidemiology is known as the

A

rate ratio

112
Q

rates being compared are incidence rates, epidemiologists call those comparisons ____

A

risk ratios

113
Q

risk ratios is also referred to as

A

relative risk (RR)

114
Q

is a measure of association that provided the strength of association between exposure and outcome in a population

A

relative risk

115
Q

True or false: Relative risk is not a flexible tool.

A

False

116
Q

When the relative risk is above 1, the interpretation is that those in the exposed group are __________ the outcome than those in the nonexposed group

A

more likely to have

117
Q

The larger the number, the _______ the relationship between being exposed and having the outcome.

A

stronger

118
Q

Relative Risk = 1

A

Null value; No relationship exists

119
Q

Relative Risk > 1

A

Positive association; more likely to have the outcome

120
Q

Relative Risk < 1

A

Negative association; less likely to have the outcome

121
Q

is a measure of association that provides strength of association between exposure and outcome in a population.

A

RELATIVE RISK

122
Q

is a measure association that provides the strength and direction of the association between exposure and outcome in a population.

A

odds ratio

123
Q

odds ratio greater than 1 indicates a ______ between exposure and outcome

A

positive association

124
Q

odds ratio less than 1 indicates a _____ between exposure and outcome.

A

negative association

125
Q

odds in those with the outcome to the exposure odds in those without outcome

A

Exposure

126
Q

odds in those with exposure to the outcome odds in those without exposure.

A

Outcome

127
Q

first way that the odds ratio can be calculated

A

Exposure Odds Ratio

128
Q

Formula for exposure OR

A

𝑎/𝑐
𝑏/𝑑

129
Q

Formula for Outcome OR

A

𝑎𝑑/𝑏𝑐

130
Q

second way that the odds ratio can be calculated

A

Outcome Odds Ratio

131
Q

measure of association that provides strength and direction of the association between existing exposure and outcome in the population.

A

Prevalence Ratio

132
Q

a measure of association between exposure and outcome, provides strength and direction using two incidence densities

A

Incidence Density Ratio

133
Q

a measure association that provides the strength and direction of the association between exposure and outcome in a population.

A

Odds ratio

134
Q

is another tool used for testing population mean when the variance is unknown and/or the sample size is small (n < 30).

A

T-test

135
Q

is used to test the hypothesis involving the mean of a study.

A

T-test

EPI LEC (2 decks)

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