Research Nursing question paper
PDF link is there at the
end of this paper
1. What is the goal of statistics?
Figure out if what we observe is the
result of the factor studied or a background of normal variation. Evaluate what
the numbers actually mean represent them in a way that communicates their
meaning to others
2. What is a variable?
A characteristic that varies between
individuals
3. What is a nominal qualitative variable?
EX: Colour (Categories)
4. What is an ordinal qualitative variable?
EX: Body condition (Categories)
5. What are some biological variations?
Genetics, Environment, Gender, Age
6. What are two types of technical errors?
Human errors Instrument errors
7. What is a population?
All representatives in a group
8. What is a sample?
A subgroup of the population
9. What are descriptive statistics used for
Used to summarize data in diagrams,
tables, mean, variance.
10. What is inferential statistics?
To generalize from the sample
something that can be applied to the whole population Estimation of a
population’s parameter Hypothesis testing (to investigate a theory about the
data)
11. Which types of diagrams are used to represent
qualitative data?
Bar charts Pie charts
12. Which types of diagrams are used to represent
quantitative data?
Dot diagram Histogram Stem and leaf
diagram Box and whisker plot Scatter diagram
13. What are the averages taken of central tendency?
Mean Median Mode
14. What is used to measure dispersions (spread?)
Range Variation Standard deviation
15. What is the price we pay by using sampling
instead of questioning the whole population?
The price we pay for sampling is that
we cannot make statements of absolute certainty about the population. The doubt
is expressed as a probability. The larger the sample, the more representative
it is.
16. What are the six types of studies?
Observational vs experimental ¤
Cross-sectional vs longitudinal ¤ Cohort vs case-control
17. What are six things to consider when trying to
increase precision of the estimates?
¤ Replication¤ blocks¤ independent vs
pairing¤ Confounders & Interaction ¤ Outliers¤ Missing data
18. Why is it impossible to prove something with statistics?
Because of the sampling error. We are
not directly measuring a population
19. What is a null hypothesis?
A hypothesis proving that there is no
difference
20. What is an alternate hypothesis?
The opposite of the null hypothesis:
there is a difference
21. What is the P value?
Probability. Value that makes you
decide if you reject Ho or not.
22. What does it mean if your P value is very small?
It is unlikely that we could have
obtained the observed results if the null hypothesis were true, so we reject
Ho. There is a small probability that Ho is true.
23. What does it mean if your P value is very large?
There is a high chance that we could
have obtained the observed results if the null hypothesis were true, and we do
not reject Ho. There is a large probability that Ho is true.
24. What does an A value of 0.01 mean?
Even more certain to have truly taken
the right decision to reject Ho
25. What does an A value of 0.05 mean?
Generally accepted
26. What is a type 1 error?
False negative
27. What is a type 2 error?
False positive
28. What is simple randomization?
We would use a computer to generate
the sequence, or a table of random numbers, or flip a coin
29. What is the drawback to simple randomization?
The main drawback is that, with a
small sample size, there could be a severe imbalance in the numbers assigned to
each treatment.
30. What is sampling error?
The sampling error is an error in the
estimation of the POPULATION parameter, because we are using a SAMPLE of the
population and not measuring the whole population.
31. What are the two types of sampling errors?
Sampling error in relation to the
mean and sampling error in relation to a proportion.
32. Give an example of qualitative nominal
The nominal scale is composed of
categories of things that can be assigned a name and are not in any particular
order (coat colour, white blood cells, type of diet (wet-dry)).
33. Give an example of qualitative ordinal
The ordinal scale is composed of categories
that CAN be given an order, but there is not a consistently defined interval
(body condition, toxic changes in neutrophils (1+, 2+, 3+))
34. Give an example of quantitative continuous
The continuous scale is composed of
values on a continuum (age, haematocrit).
35. Give an example of quantitative discontinuous
The discontinuous scale is composed
of integer3 values values (# of puppies in a litter, results of rolling a
dice))
36. The rate of a particular enzyme reaction
Numerical, continuous
37. Number of offspring per litter
Numerical, discontinuous (discrete)
38. Coat colour in horses
Categorical, nominal
39. Disagree, neutral, agree, somewhat agree
Categorical, ordinal
40. What is a measure of location used for?
To measure the central tendency of
the data set.
41. What are the measures of location?
Mean, median, mode
42. What is a measure of dispersion?
To measure how widely scattered the
observations are in either direction from that average.
43. What are the measures of dispersion?
Range, interquartile range, variance,
standard deviation
44. What is a variance a measure of?
Dispersion
45. What is range a measure of?
Dispersion
46. What is mode a measure of?
Location
47. What is interquartile range a measure of?
Dispersion
48. What type of data is best represented by a pie
chart?
Pie chart: circle divided into
segments with each segment portraying a different category of the qualitative
variable. For categorical data.
49. What type of data is best represented by a bar
chart?
Bar chart: diagram in which every
category of the variable is represented. Thelenght of each bar (width is
constant) depicts the # or % of individuals belonging to that category. For:
categorical data.
50. What type of data is best represented by a dot
diagram?
Dot diagram: each observation is a
dot within horizontal and vertical axis calibrated in the units of measurement.
For quantitative data (small size)
51. What type of data is best represented by a
histogram?
Histogram: Two-dimensional diagram
with (usually) the unit of measurement on the horizontal axis and the height is
proportional to the frequency (vertical axis is frequency). * The rectangles
are contiguous (no space between each bar) because the numerical variable is
continuous (compared to a bar chart). For quantitative variable (frequencies).
52. What type of data is best represented by a stem
and leaf diagram?
Stem and leaf diagram: modified
histogram. Row of number that represents the observations instead of a
rectangle (vertical). (Not used very often - you do not need to study)
53. What type of data is best represented by a box
and whisker plot?
Box-and-whisker plot (box plot): The
scale of measurement of the variable is usually drawn vertically. The diagram
comprises a box with horizontal limits defining the upper and lower quartiles
and representing the interquartile range, enclosing the central 50% of the
observations, with the median marked by a horizontal line within the box. The
whiskers are vertical lines extending from the box as low as the 2.5th
percentile and as high as the 97.5th percentile (sometimes the percentiles are
replaced by the minimum and maximum values of the set of observations). Very
common. For quantitative variables.
54. What type of data is best represented by a
scatter diagram?
Scatter diagram: effective way of
presenting data when we are interested in examining the relationship between
two variables which may be numerical or ordinal. The diagram is a
two-dimensional plot in which each axis represents the scale of measurement of one
of the two variables. Using this rectangular co-ordinate system, we relate the
value for an individual on the horizontal scale (the abscissa) to the
corresponding value for that individual on the vertical scale (the ordinate) by
marking the relevant point with an appropriate symbol. For quantitative
variables.
55. What is an outlier?
Outlier: An outlier is an observation
whose value is highly inconsistent with the main body of the data. An outlier
with an excessively large value will tend to increase the mean unduly, whilst a
particularly small value will decrease it.
56. (T/F and Why) A qualitative variable comprises
two categories which may be ordinal or numerical.
Qualitative (categorical) —>
nominal or ordinal scale; Numerical (quantitative) is the opposite category of
qualitative.
57. (T/F and Why) an ordinal variable comprises
categories that cannot be ordered.
Ordinal (scale) is, by definition,
composed of categories that CAN be ordered.
58. (T/F and Why) The age groups ‘young’, ‘middle
aged’ and ‘old’ relate to a nominal categorical variable.
It is in the categorical
(qualitative) variable group, but since we can give an order to the categories,
it is part of the ordinal scale.
59. (T/F) Blood group is classified as a nominal
categorical variable.
True
60. The number of eggs per clutch is a _____
variable
The number of eggs per clutch is an
Numerical (quantitative) - discontinuous (discrete) variable
61. What are the 3 ways a researcher can deal with
an outlier?
1. include them and proceed as
originally planned, recognizing that the distribution assumptions of the
analysis may not be met.2. Include them in the analysis but adopt a procedure
that is appropriate for the data.3. Perform a sensitivity analysis by analysing
the data both with and without the outliers to determine the effect, if any, of
removing them.4. Exclude them from the analysis (this is a high-risk strategy,
and, before you do so, you should thoroughly investigate the reason for their
presence. Beware that some computer packages will automatically eliminate
outliers from the analysis.
62. Write a short explanation of what is meant by
Evidence Based Veterinary Medicine.
Conscientious, explicit and judicious
use of current best scientific evidence to inform clinical judgements and
decision making with a view to improving clinical outcome in veterinary care.
63. What is Random sampling (Simple Randomization?)
Computer or random number table used.
Does not have any restrictions or refinements (see other methods). Similar to
flipping a coin for each subject. Problems: there is a small probability of
assigning the same number of subjects to each treatment group. A severe
imbalance in the numbers assigned to each treatment is a critical issue can
result with this method with small sample sizes. This can lead to imbalance
among the treatment groups with respect to prognostic variables that affect the
outcome variables
64. What is Restricted (blocked) randomization:
The experimenter divides subjects
into subgroups called blocks. Then, subjects within each block are randomly
assigned to treatment conditions. Compared to a completely randomized design,
this design reduces variability within treatment conditions and potential
confounding, producing a better estimate of treatment effects. This is done to
achieve similar # in each groups.
65. What is Stratified sampling?
The population is divided into strata
according to main cofounding variable (egg if we study arthritis in dogs, the
strata are dog size (small, medium or large breed)). Within each strata, simple
randomization is done. Restricted randomization could also be incorporated in
each strata (see restricted (blocked) randomization).
66. What is Group or cluster randomization?
The experimental unit is the smallest
unit in an experiment to which a treatment can be assigned, and whose response
is independent of the responses of the other units. Generally, in human
medicine, clinical trials take the individual person as the experimental unit
although, occasionally, clusters of individuals, such as households, are used.
However, we often regard the group as the most appropriate experimental unit in
the veterinary and animal sciences. This is because food, drugs and vaccines
are often administered to a group of animals in a litter, pen, paddock or barn,
or to a complete herd or to all the fish in a tank. In this case, we apply the
randomization procedure to the groups (i.e. group or cluster randomization), so
that all animals or fish within each group receive the same treatment. The
clusters are selected randomly.
67. What is Systematic sampling?
The researcher first randomly picks
the first item or subject from the population. Then, the researcher will select
each not subject from the list. The procedure involved in systematic random
sampling is very easy and can be done manually. The results are representative
of the population unless certain characteristics of the population are repeated
for every not individual, which is highly unlikely. For example, the researcher
has a population total of 100 individuals and need 12 subjects. He first picks
his starting number, 5. Then the researcher picks his interval, 8. The members
of his sample will be individuals 5, 13, 21, 29, 37, 45, 53, 61, 69, 77, 85,
93.
68. What is an observational study?
In an observational study, we merely
observe the animals in the study and record the relevant measurements on those
animals. We make no attempt to intervene, for example, by administering
treatments or withholding factors that we feel may affect the course of the
disease. Clearly, we cannot randomly allocate animals to treatment groups in an
observational study. A particular type of observational study is a survey in
which we examine an aggregate of animals in order to derive values for various
parameters in the population.
69. What is a population Survey?
A population survey which includes
the entire population, e.g. a census.
70. What is a sample survey?
A sample survey in which we examine a
representative sample of animals so that we may draw conclusions about the
whole population of animals.
71. (t/f in an observational study) Random allocation
is usually performed.
No, it is not possible because we do
not intervene.
72. (t/f in an observational study) will include a
sample survey but not a population survey.
No, it includes both the sample
survey and the population survey.
73. (T/f in an observational study) will include
laboratory experiments and clinical trials.
No, it cannot since we do not
intervene.
74. (T/f in an observational study) the observation
of a certain number of animals allows to draw conclusion about the whole population.
Yes, such as in a sample survey
75. Animals are randomly assigned to the treatment
groups in clinical trials: To ensure that there is no allocation bias
Yes
76. Animals are randomly assigned to the treatment
groups in clinical trials: To ensure that all animals have the same chance of
receiving any treatment
Yes
77. Animals are randomly assigned to the treatment
groups in clinical trials: So that a control group can be incorporated into the
design
No, it is not because you do
randomization that you need a control group. Control group permits us to be
comparative
78. Animals are randomly assigned to the treatment
groups in clinical trials: So that the treatment groups are comparable with
respect to any variables that are likely to influence response
Yes, this is why we do randomization.
79. What is the goal of randomization?
a) All animals have same chance of
receiving txt. b) The assignment of one animal has no influence on the
assignment of any other animal. c) We cannot know in advance the txt that each
animal is to receive. d) Permits us to use statistical inference (based on concept
of random sampling). Randomization prevents allocation bias.
80. A study was conducted into the influence of
spaying of bitches on their subsequent development of urinary incontinence.
Young adult bitches presenting for spaying were randomly allocated into
immediate ovariohysterectomy or to a deferred operation 6 months later. The
bitches were followed during the 6 months period. Was this: A cross-sectional
or longitudinal study and why?
Longitudinal study, because changes
were investigated over time.
81. What is a cross sectional study?
Cross-sectional: All measurements
done at one point in time. Does not take into account temporal relationship
between risk factors and disease state. Is descriptive.
82. What is a longitudinal study?
Longitudinal: Investigate changes
over time. If prospective: values are measured after the start of the study. If
retrospective: previous values are examined.
83. A study was conducted into the influence of
spaying of bitches on their subsequent development of urinary incontinence.
Young adult bitches presenting for spaying were randomly allocated into
immediate ovariohysterectomy or to a deferred operation 6 months later. The
bitches were followed during the 6 months period. Was this: An experimental or
an observation study, and why?
Experimental, because we intervene,
and measure the effects of the intervention.
84. What is an experimental study?
Experimental: We intervene in a
study. We observe and measure the effects of our intervention. Animals must be
randomly assigned - there must be a control group as well as a treatment
group(s). Laboratory experiments and clinical trials.
85. What is an observational study?
Observational (see above also):
Observe animals and make measurements of whatever values we are interested in.
There is no intervention. Since there is no intervention, there is no control
or treatment group.
86. A study was conducted into the influence of
spaying of bitches on their subsequent development of urinary incontinence.
Young adult bitches presenting for spaying were randomly allocated into
immediate ovariohysterectomy or to a deferred operation 6 months later. The
bitches were followed during the 6 months period. Was this: A case control
study, a cohort study, or neither. Why?
Neither, since both are observational
studies
87. What is a case control study?
Case-control study: In a case-control
study of disease aetiology, we start by defining the groups of diseased and
healthy animals; these are the cases and the controls, respectively. Then we
assess whether the animals in the two groups have differences in past exposure
to various risk factors. Retrospective because we have to go back in time in
order to determine an animal’s exposure to the risk factor.
88. What is a matched design case control study?
We choose the controls so that each
control animal is matched with a case with respect to variables that may
influence the development of disease, (breed, sex and/ or age) (matched
design).
89. What is an unmatched design case control study?
Unmatched design in which the
disease-free or control animals are selected from the population, but without
any attempt at matching.
90. What is the advantage to a case control study?
Advantage: quick, easy and less
expensive, can be used when the disease outcome is rare.
91. What is the disadvantage to a case control study?
Disadvantage: losses to follow-up
and, recall bias (there is a differential ability between carers in remembering
relevant facts about cases and controls relating to exposure), not suitable
when exposures to the risk factor are rare.
92. What is a cohort study?
Cohort study: In a cohort study of
disease aetiology, we start by defining groups (cohorts) of disease-free
animals according to the exposure of the animals in the groups to the factor(s)
of interest. Generally, we follow these groups forward in time to see which
animals develop the disease under investigation. (Prospective).
93. What is the advantage to a cohort study?
Advantage: can be used to collect
information on exposure to a wide range of factors, even rare ones, and on
different outcomes.
94. What is the disadvantage to a cohort study?
Disadvantage: If the disease outcome
is rare, its time span can be quite long, it tends to be expensive and may
suffer from inconsistencies.
95. What is a control group?
Control group: In an experiment, a
control group is a baseline group that receives no treatment, a placebo or a neutral
treatment (or the standard procedure). To assess treatment effects, the
experimenter compares results in the treatment group to results in the control
group.
96. State the type of study this is: Study of the
prevalence of feline leukaemia in a cat colony
Cross-sectional
97. State the type of study this is: Review
comparison of drug treatment vs radiation treatment for feline hyperthyroidism
at a Referral centre over last 10 years
Retrospective
98. State the type of study this is: Survey of cat
owners on attitude to declawing.
Cross-sectional
99. Concerning a Case-Control study: are the
following statements true or false. And explain why: We start with groups of
diseased and healthy animals
Yes (that is the definition) as
opposed to cohort (starts with two disease-free groups).
100. Concerning a Case-Control study: are the
following statements true or false. And explain why: Case control studies are
prospective studies
No, they are retrospective. The
cohort study is prospective.
101. Concerning a Case-Control study: are the
following statements true or false. And explain why: We can determine relative
risk
No, this concept (relative risk) is
related to the cohort study.
102. What is the true risk of something?
We usually analyse data from cohort
studies by estimating the true risk of the disease in the populations of
animals that have been ‘exposed’ and ‘unexposed’ to the factor. The true risk
of disease is the proportion of animals in a population of susceptible animals
that develop the disease in the time interval under consideration;
103. What is the relative risk of something?
The relative risk (RR), the ratio of
the disease risks in the exposed and unexposed groups, provides a measure of
the strength of the association between the disease and the exposure to the
factor.
104. Concerning a Case-Control study: are the
following statements true or false. And explain why: We can determine the odds
ratio
Yes, the concept of odds ratio is
related to the case-control study
105. What is the odds ratio?
The ratio of two odds, usually the
odds of disease in the group exposed to the factor divided by the odds of
disease in the group not exposed to the factor.
106. Which of the following is not a type of Bias
to avoid in a Clinical trial? Allocation bias
Yes, avoided with randomization
107. Which of the following is not a type of Bias
to avoid in a Clinical trial? Assessment bias
Yes, avoided by blinding and having a
control group
108. Which of the following is not a type of Bias
to avoid in a Clinical trial? Selection bias
Yes, avoided with randomization
109. 22. A new surgical implant is to be tested on
dogs prior to human trials.
a) why must the control dogs have the surgery done
(except the implant is not put in)?
To negate the effect of the surgical
procedure (and separate the effect of the surgery from the effect of the
implant). (To remove one possible confounding variable).
110. b) If the carer and the assessor of the
animals do not know which group the dogs belong to,
We say this is a Double blinded
study.
111. What is a double blinded study?
Double-blinded: neither the carer(s)
of the animals nor the assessor of response to treatment (test or control) is
aware of which treatment each animal is receiving.
112. What is a single blinded study?
Single-blinded: only one of these two
parties, the carer or the assessor, is blind. If the response to treatment is
objective, then it may be sufficient to have only the carer blind; if it is
possible to distinguish the test and control regimens, perhaps because of
experimental procedures, then it may not be feasible to make the carer blind.
113. What is meant by a positive control?
A positive control group is a group
of experimental units that receive a treatment that is known to cause an effect
on the response.
114. What is meant by a negative control?
A negative control group is a group
that receives a neutral or standard treatment, and the standard treatment may
simply be nothing.
115. What are dependant variables?
Dependant variable: A dependent
variable is what you measure in the experiment and what is affected during the
experiment. The dependent variable responds to the independent variable. It is
called dependent because it "depends" on the independent variable. In
a scientific experiment, you cannot have a dependent variable without an
independent variable. Example: You are interested in how stress affects heart
rate in humans. Your independent variable would be the stress and the dependent
variable would be the heart rate. You can directly manipulate stress levels in
your human subjects and measure how those stress levels change heart rate.
116. What are confounding variables?
Confounding variables: Sometimes, we
find that two or more variables are related to each other as well as to the
response of interest, so that it is impossible to separate the effects of these
variables on the response. The variables are then called confounders and the
process is called confounding.
117. What is anthology?
An anthology is a collection of
literary works chosen by the compiler. It may be a collection of poems, short
stories, plays, songs, or excerpts
118. What is a clinical trial?
Clinical trial: any planned
experiment that involves human or animal subjects, and is designed to assess
the effectiveness of one or more treatments or preventive measures such as
vaccines.
119. What is clinical pathology?
Clinical pathology supports the diagnosis
of disease using laboratory testing of blood and other bodily fluids, tissues,
and microscopic evaluation of individual cells.
120. What is epidemiology?
The study of disease patterns and
their determinants in the population
121. (T or F) the null hypothesis for a test to
compare two means states that :( a) the sample means are equal. T or F...
False: the null hypothesis concerns
the population means.
122. (T or F)The null hypothesis for a test to
compare two means states that:(b) There is no significant difference between
the population means. T or F...
True
123. (T or F) the null hypothesis for a test to
compare two means states that: (c) There is no significant difference between
the population means. T or F...
False: it is only the result of the
test which is or is not significant, not the null hypothesis
124. How is a P-value obtained and how do we
use/interpret this P-value?
A P value is obtained by
running/calculating a statistical test. The P value indicates a probability, we
use it to decide if we reject Ho or not. A very small P-value indicates that it
is unlikely that we could have obtained the observed results if the null
hypothesis were true, so we reject Ho.
125. What is descriptive statistics?
Descriptive statistics are used to
summarize data by using visual aids (graphs, diagrams and tables) and numerical
measures to describe central location (mean, median, and mode) and spread (eg.
variance, standard deviation)
126. What are inferential statistics?
- Inferential statistics are used to
generalize from the sample something that can be applied to the whole
population (estimation of a population’s parameter and hypothesis testing (to
investigate a theory about the data))
127. Which is false?(a) Sampling error makes it
“impossible” to prove something with statistics(b) If the difference between
the sample mean and the population (true) means due to pure chance, we do not
reject Ho(c) We can never accept Ho(d) Not rejecting Ho is equivalent to saying
we accept Ho
(d) Not rejecting Ho is equivalent to
saying we accept Ho (FALSE)
128. What is the sensitivity of a test? How is it
determined? Give an example of a disease where we need a high sensitivity.
The sensitivity of a test is how well
that test can it identify animals that have the disease. Sensitivity is
determined with the following formula: true positives/ (true positives false
negatives). We need a high sensitivity when we need to perform an exclusion
test (such as urinary cortisol ratio for Cushing’s) or when there is a great
disadvantage to not diagnosing a disease early (basal cortisol level for Addison).
129. When talking about sensitivity and
specificity, what is a gold standard? Give one example of a gold standard test
for a specific disease.
A gold standard is a diagnostic test
with proven 100% sensitivity & specificity. Egg. Kidney disease (renal
clearance of a substance), Parvovirus (histology & IFA), Heartworm ds
(necropsy).
130. What is the negative predictive value (NPV)?
Why is it an interesting information to have for your clients?
Negative predictive value is the
proportions of negative results in statistics and diagnostic tests that are
true negative results. NPV = True negatives / (True negatives + False
negatives). So a NPV indicates how likely is it that this patient really does
not have the disease given that the test result is negative (how reassured your
client should be)
131. What should you know about prevalence?
What you should know is that with a
low prevalence, you have an increased risk of having a false positive result. A
positive heartworm test in kuujjuak (in a dog that has not travelled) has a lot
of chances of being a false positive.
132. Which two graphs can you use to evaluate if
your data is normally distributed?
Histogram and box plot
133. What does it mean when we say a statistical
test is robust?
It means it is able to tolerate a
certain deviation from the assumptions (for example, if the data is not quite
normal, you can still use the test if it is robust).
134. Give an example where we would need to use a one
sample t-test.
Any example involving one set of data
that you want to compare to a known population mean.
135. What are the assumptions for the one sample
t-test?
Normal distribution
136. Give an example where we would need to use an
ANOVA
Any example where there is 3 or more
sets of data.
137. What are the assumptions for the ANOVA?
Normal distribution, homoscedasticity
138. What do we mean when we say two sets of observations
are dependent?
Animal or individual result that are
related to any other, either within or between groups
139. If we have more than two samples to compare,
why don’t we use multiple two- sample t-tests?
Because if we do multiple t-tests, we
get multiple P-values so we increase our chance of finding a significant result
by chance. (For one of those test we might be in the 5% chances of being wrong
by rejecting Ho category)
140. What is a type I error?
It’s rejecting a true Ho (finding a
significant difference where there is none).
141. What is the sampling error, why is it an
important concept to understand when using the ANOVA?
The sampling error is the chance
difference between a sample estimate and the true value of the population
caused by random sampling. The ANOVA can estimate that sampling error and then
uses this to tell us if there is a significant difference between the means of
the samples we are testing.
142. Why do we need a second test (such as the
Bonferroni or Tukey) after performing the ANOVA on our data?
The ANOVA tells us there is a
significant difference somewhere between some of the groups, the second test
pin points where.
143. What do we use the Pearson’s correlation
coefficient for?
We use it to tell us if there is a
(linear) relationship between two variables and to what degree does that
relationship exist.
144. What does a correlation coefficient of 1 tell
us, of -1, of 0?
If it is zero, there is no
correlation (or some nonlinear relationship); if it is ± 1, it is perfect
correlation (perfect positive or negative slope).
145. What does the slope of the linear regression
tell us?
It is the slope of the line, gives
the average change in y for a unit change in x
146. Why is it important to observe the scatter
diagram when doing correlation and
To identify outliers, atypical
distribution or a non-linear relationship.
147. Why do we need non-parametric tests?
To enable us to run statistical tests
on non-normally distributed data.
148. What is the disadvantage of using a
non-parametric test?
Because we transform the data into
ranks, we lose some precision.
149. What is PICO?
It the acronym that helps to ask a
good answerable question in evidence based medicine. Patient or Population,
Intervention, Comparison/control, Outcome.
150. What is a CAT (critically appraised topic)?
It is the systematic evaluation of
clinical research papers in order to answer a clinical question.
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