Kap 1 - Introduction to data

Question 1

Randomized Experiment

Answer 1

When individuals are randomly assigned to a group.

Question 2

Anacdotal evidence

Answer 2

Lítið av data, kann vera . Um man hevur eitt data og persónurin doyr eftir at hava tikið medisinið, kann tað vera ein ekstrem case av medisinum, meðan tað kann gott vera eitt gott medisin alíkavæl.
Be careful of data collected in a haphazard fashion. Such evidence may be true and veriable,
but it may only represent extraordinary cases.

Question 3

What is a summary statistic?

Answer 3

A summary statistic is a single number

summarizing a large amount of data.

Question 4

What is variables?

Answer 4

Columns represent characteristics, called variables.

Question 5

What is a data matrice?

Answer 5

A table. A convenient and common way to organize data, especially if collecting data in a spreadsheet. Each row of a data matrix corresponds to a unique case
observational unit), and each column corresponds to a variable.

Question 6

What is a case or observational unit?

Answer 6

Ein rekkja í einari talvu.

Question 7

What is a numeric variable?

Answer 7

numerical variable since it can take a wide

range of numerical values, and it is sensible to add, subtract, or take averages with those values.

Question 8

What is a discrete variable?

Answer 8

Discrete variables are whole integers in a specific range.

Question 9

What is a continuous variable?

Answer 9

It is numeric and can be all numbers.

Question 10

What is a categorical variable?

Answer 10

Usually categories. Usually text. The possible values in a category is called the variable’s levels.

Question 11

What are ordinal and nominal variables?

Answer 11

An ordinal variable is a categorical variable but the levels have a natural ordering, while a regular categorical variable without this type of special ordering is called a nominal variable.

Question 12

What is a scatterplot?

Answer 12

Scatterplots are one type of graph used to study the relationship between two numerical variables.

Question 13

What is it called when two variables show some connection with one another?

Answer 13

When two variables show some connection with one another, they are called
associated variables. Associated variables can also be called dependent variables and vice-versa.

Question 14

What is it called when two variables don’t have a connection with one another?

Answer 14

Independent

Question 15

explanatory and response variables?

Answer 15

When we suspect one variable might causally affect another, we label the frst variable the
explanatory variable and the second the response variable.
For many pairs of variables, there is no hypothesized relationship, and these labels would not
be applied to either variable in such cases.

Question 16

What is an observational study?

Answer 16

Researchers perform an observational study when they collect data in a way that does not
directly interfere with how the data arise. For instance, researchers may collect information via
surveys, review medical or company records, or follow a cohort of many similar individuals to form
hypotheses about why certain diseases might develop. In each of these situations, researchers merely
observe the data that arise. In general, observational studies can provide evidence of a naturally
occurring association between variables, but they cannot by themselves show a causal connection.
observational studies are generally only sucient to show associations or form
hypotheses that we later check using experiments.

Question 17

What is an experiment?

Answer 17

When researchers want to investigate the possibility of a causal connection, they conduct an
experiment. Usually there will be both an explanatory and a response variable. For instance, we
may suspect administering a drug will reduce mortality in heart attack patients over the following
year. To check if there really is a causal connection between the explanatory variable and the
response, researchers will collect a sample of individuals and split them into groups. The individuals
in each group are assigned a treatment.

Question 18

What is a randomized experiment?

Answer 18

When people are randomly picked into a group of an expermient

Question 19

What is a placebo?

Answer 19

Fake treatment.

Question 20

What is a sample

Answer 20

Often times, it is too expensive
to collect data for every case in a population. Instead, a sample is taken. A sample represents
a subset of the cases and is often a small fraction of the population. For instance, 60 swordsh
(or some other number) in the population might be selected, and this sample data may be used to
provide an estimate of the population average and answer the research question.

Question 21

What is the problem with selecting samples by hand?

Answer 21

When selecting samples by

hand, we run the risk of picking a biased sample, even if their bias isn’t intended.

Question 22

What is a simple random sample?

Answer 22

The most basic random sample is called a simple random sample, and which is
equivalent to using a raffle to select cases. This means that each case in the population has an equal
chance of being included and there is no implied connection between the cases in the sample.

Question 23

What is the problem if the non-response rate is high?

Answer 23

if only 30% of the people randomly sampled for
a survey actually respond, then it is unclear whether the results are representative of the entire
population. This non-response bias can skew results.

Question 24

What is a convenience sample?

Answer 24

where individuals who are easily accessible

are more likely to be included in the sample.

Question 25

What is a confounding variable?

Answer 25

A variable that is correlated with both the explanatory and response variables. While one method to justify making causal conclusions from observational studies is to exhaust the search for confounding variables, there is no guarantee that all confounding variables can be examined or measured.

Example:
Some previous research tells us that using sunscreen actually reduces skin cancer risk, so maybe
there is another variable that can explain this hypothetical association between sunscreen usage and
skin cancer. One important piece of information that is absent is sun exposure. If someone is out
in the sun all day, she is more likely to use sunscreen and more likely to get skin cancer. Exposure
to the sun is unaccounted for in the simple investigation.

Question 26

What is a prospective study?

Answer 26

identies individuals and collects information as events unfold. For instance, medical
researchers may identify and follow a group of patients over many years to assess the possible in
uences
of behavior on cancer risk.

Question 27

What is a retrospective study?

Answer 27

Retrospective studies collect data after events have taken place, e.g. researchers may review past events in medical records.

Question 28

What are the four random sampling techniques?

Answer 28

simple, stratified, cluster, and multistage sampling

Question 29

What is a simple random sampling?

Answer 29

In general, a sample is referred to as \simple random”
if each case in the population has an equal chance of being included in the nal sample and knowing
that a case is included in a sample does not provide useful information about which other cases are
included.

Question 30

What is stratified random sampling?

Answer 30

Stratied sampling is a divide-and-conquer sampling strategy. The population is divided
into groups called strata. The strata are chosen so that similar cases are grouped together, then a
second sampling method, usually simple random sampling, is employed within each stratum. In the
baseball salary example, the teams could represent the strata, since some teams have a lot more
money (up to 4 times as much!). Then we might randomly sample 4 players from each team for a
total of 120 players.
Stratied sampling is especially useful when the cases in each stratum are very similar with
respect to the outcome of interest. The downside is that analyzing data from a stratied sample
is a more complex task than analyzing data from a simple random sample. The analysis methods
introduced in this book would need to be extended to analyze data collected using stratied sampling.

Question 31

What is a cluster sample?

Answer 31

In a cluster sample, we break up the population into many groups, called clusters. Then
we sample a xed number of clusters and include all observations from each of those clusters in the
sample.
Sometimes cluster or multistage sampling can be more economical than the alternative sampling
techniques. Also, unlike stratied sampling, these approaches are most helpful when there is a lot of
case-to-case variability within a cluster but the clusters themselves don’t look very different from one
another.

Question 32

What is a multistage sample?

Answer 32

A multistage sample is like a cluster sample,
(In a cluster sample, we break up the population into many groups, called clusters. Then
we sample a xed number of clusters and include all observations from each of those clusters in the
sample), but rather than keeping all observations in
each cluster, we collect a random sample within each selected cluster.
Sometimes cluster or multistage sampling can be more economical than the alternative sampling
techniques. Also, unlike stratied sampling, these approaches are most helpful when there is a lot of
case-to-case variability within a cluster but the clusters themselves don’t look very different from one
another.

Question 33

Randomized experiments are generally built on which four principles?

Answer 33

Controlling, randomization, replication and blocking.

Question 34

What is the controlling principle about?

Answer 34

Researchers assign treatments to cases, and they do their best to control any other
differences in the groups.27 For example, when patients take a drug in pill form, some patients
take the pill with only a sip of water while others may have it with an entire glass of water. To
control for the eect of water consumption, a doctor may ask all patients to drink a 12 ounce
glass of water with the pill.

Question 35

What is the randomization principle about?

Answer 35

Researchers randomize patients into treatment groups to account for variables
that cannot be controlled. For example, some patients may be more susceptible to a disease
than others due to their dietary habits. Randomizing patients into the treatment or control
group helps even out such differences, and it also prevents accidental bias from entering the
study.

Question 36

What is the replication principle about?

Answer 36

The more cases researchers observe, the more accurately they can estimate the effect
of the explanatory variable on the response. In a single study, we replicate by collecting a
suffciently large sample. Additionally, a group of scientists may replicate an entire study to
verify an earlier finding.

Question 37

What is the blocking principle about?

Answer 37

Researchers sometimes know or suspect that variables, other than the treatment, influence the response. Under these circumstances, they may rst group individuals based on this
variable into blocks and then randomize cases within each block to the treatment groups. This
strategy is often referred to as blocking. For instance, if we are looking at the eect of a drug
on heart attacks, we might rst split patients in the study into low-risk and high-risk blocks,
then randomly assign half the patients from each block to the control group and the other half
to the treatment group, as shown in Figure 1.16. This strategy ensures each treatment group
has an equal number of low-risk and high-risk patients.

Question 38

What is a blind study?

Answer 38

When researchers keep the patients uninformed about if they are in the treatment- or the control group.

Question 39

What is a double-blind study?

Answer 39

The patients are not the only ones who should be blinded: doctors and researchers can accidentally
bias a study. When a doctor knows a patient has been given the real treatment, she
might inadvertently give that patient more attention or care than a patient that she knows is on
the placebo. To guard against this bias, which again has been found to have a measurable eect
in some instances, most modern studies employ a double-blind setup where doctors or researchers
who interact with patients are, just like the patients, unaware of who is or is not receiving the
treatment.