biostatistics

Question 1

what is a sampling error

Answer 1

a statistical error that occurs when a selected sample does not represent the entire population
the results found in the sample do not represent those that would be found from the entire population

Question 2

what is random error

Answer 2

error by chance because we have a sample and not the whole population

Question 3

how to reduce sampling error

Answer 3

increase sample size

select a representative sampling (probability/ random sampling)

Question 4

data types

Answer 4

variable:

numerical: continuous and discrete
categorical: ordinal and nominal type

Question 5

what is the best way to summarize and analyze Numerical variables

Answer 5

histograms and box and whisker plots
summary; mean and SD, variance if symmetrical
median and IQ range if skewed

Question 6

what is the best way to summarize categorical data

Answer 6

pie charts and bar graphs frequency(relative and cumulative)and proportions

Question 7

what is a null hypothesis

Answer 7

when we assume there is no relationship between variables in the population,
it is always right until you have enough evidence to reject it

Question 8

what is an alternative hypothesis

Answer 8

that there is a relationship between variables

Question 9

type 1 error

Answer 9

reject the null hypothesis when it is actually true

Question 10

1- alpha

Answer 10

probability of making a type 1 error

Question 11

type 2 error

Answer 11

failure to reject the type 1 when it should have been rejected

Question 12

1-B

Answer 12

probability of making a type 2 error

Question 13

what does the p-value tell you

Answer 13

if p is less or equal to 0.05 we reject the null hypothesis and the p value is significant

if p is greater than 0.05 we do not reject the null
hypothesis and the p value is not significant( we do not have enough evidence to reject the null hypothesis

Question 14

factors that influence statistical power

Answer 14

sample size
big sample sizes have lots of statistical power
effect size(difference in means, proportions, odds or risk ratio)- big effect size require less power

level of significance (if we want less error then we need more power)

Question 15

when do we use a chi square test

Answer 15

for comparison of categorical data

Question 16

when do we use a t-test

Answer 16

for comparison of categorical and numerical data

Question 17

when do we use a correlation test

Answer 17

for relationship between numerical data

Question 18

what do we use the shapiro-wilks test for

Answer 18

only used with numerical data
Tests whether the distribution of the variable is different from what
we know to be a normal distribution

Question 19

parametric tests

Answer 19

for normally distributed data
compare mean
one way anova- cannot tell which specific groups are different
students t test

Question 20

non parametric tests

Answer 20

for skewed data
Tests for differences in the overall distribution of
the variable
mann-whitney
wilcoxon signed rank
kruskal wallis- cannot tell which specific groups are different

Question 21

pearson’s correlation

Answer 21

parametric

for normally distributed

Question 22

spearmans correlation

Answer 22

non parametric

for skewed data

Question 23

confidence interval

Answer 23

measure of precision
wide- lack of precision
narrow- good precision

Question 24

pros and cons of random sampling

Answer 24

pros
accurate representation of the population
ease of use
cons
if sampling frame is large, method is impractical
minority subgroups of interest in a population may not be present in sample

Question 25

cluster sampling

Answer 25

Subjects in the same cluster are different
from one another regarding the factor of
interest (heterogenous)

Each cluster is similar to other clusters
Inclusion in the
sample

Only a subset of clusters are in the sample

Question 26

stratified sampling

Answer 26

Subjects in the same stratum are
similar to one another regarding the
stratifying factor (homogenous)

Each stratum is different from other
strata

All strata are represented in the
sample

Question 27

convenience sampling

Answer 27

• Selecting participants who are close at hand, readily available, convenient

Question 28

purposive sampling

Answer 28

• Researcher selects participants because they have certain characteristics
• Often used in qualitative research when particularly interested in insights from
certain types of people

Question 29

snowball sampling

Answer 29

• Find or two eligible people and ask them to refer others to you
• Useful for difficult to access groups

Question 30

volunteer sampling

Answer 30

• Participants self-select

* Put out an advert and see who signs up