Lesson1

Question 1

Describe summary statistic

Answer 1

a single number summarizing a large amount of data

Question 2

Describe numerical and categorical variables.

Answer 2

Numerical= quantitative: numbers that can be ordered and calculated

Categorical= qualitative: non-numeric values

Question 3

What is a discrete variable?

Answer 3

A numerical variable with only whole numbers or only certain values, ie shoe sizes or “numbers with jumps”

Question 4

What is a continuous variable?

Answer 4

A numerical variable that can take on an infinite number of values ie temperature

Question 5

What is an ordinal variable?

Answer 5

A type of categorical variable, where the possible values are ordered, ie grade level

Question 6

Describe a data matrix.

Answer 6

A spreadsheet where the rows are “cases,” and the columns are “variables.”

Question 7

What is it called when two variables show a connection?

Answer 7

Association or dependence

Question 8

Observational study

Answer 8

Collect data in a way that does not interfere with how the data arise, no treatment. Eg surveys, medical records, or follow a cohort of many similar individuals

Question 9

Define experiment

Answer 9

Studies where researchers assign treatments to cases, the experiment is randomized when the treatments are assigned randomly

Question 10

What can an experiment show that an observational study cannot?

Answer 10

Causation. An observational study only shows correlation.

Question 11

What do you call an observational study where the data points take place in the future? The past?

Answer 11

Prospective: future (as events unfold)
Retrospective: past

Question 12

Is a survey an observational study or an experiment?

Answer 12

Observational study

Question 13

Why does an experiment show causal relationship?

Answer 13

The random assignment of treatment to the subjects. In an observational study, you can’t show the treatment is randomly assigned.

Question 14

What is the difference between a positive or negative correlation?

Answer 14

A positive correlation (pos slope) is when both variables go up. If one variable goes down but the other variable goes up (neg slope), its considered a negative correlation.

Question 15

What do you call two variables that are NOT associated

Answer 15

Independent.
No pair of variables can be both independent and associated

Question 16

Define confounding variable

Answer 16

extraneous variables that affect both the explanatory and the response variable, making it seem like there is a relationship between them
eg. sun exposure affect on whether sunscreen prevents skin cancer

Question 17

Define response variable

Answer 17

When we suspect one variable might causally affect another, we say the explanatory variable might affect the response variable

Question 18

Define explanatory variable

Answer 18

When we suspect one variable might affect another, we say the explanatory var might affect the response var

Question 19

How can sampling show a better measure than taking a census?

Answer 19

Some individuals could be harder to measure, populations rarely stand still

Question 20

Define inference

Answer 20

When you sample to show something is happening in a population

Question 21

Name potential sources of sampling bias

Answer 21

Convenience sample: easily accessible individuals
Non-response: surveys
Voluntary response: people with strongest opinions might respond (no initial random sample)

Question 22

Name some sampling methods

Answer 22

Simple random sample SRS
Stratified sample
Cluster sample
Multistage sample

Question 23

What is a simple random sample SRS

Answer 23

When each case in a population is equally likely to be sampled and knowing that a case included in a sample does not provide useful info about which other cases are included

Question 24

What is a stratified sample

Answer 24

Divide the sample into homogeneous strata(groups into similar cases), then randomly sample
Allows for controlling for potential confounders
Useful when cases in each stratum are very similar with respect to the outcome of interest, downside is that analysis is more complex than SRS

Question 25

What is a cluster sample?

Answer 25

Break up population into many groups called clusters, then sample a fixed number of clusters and include all observations from each cluster in the sample
Downside is that more advanced technique is needed for analysis.

Question 26

What is a multistage sample?

Answer 26

Divide the population clusters, randomly select a few clusters , then randomly sample within these clusters eg financial basis for neighborhood sampling avoids need to travel to all neighborhoods
Downside is that more advanced technique needed for analysis

Question 27

What are the steps to experimental design?

Answer 27

Control
Randomize
Replicate
Block

Question 28

What does it mean to control in exp design?

Answer 28

Try to control for any other differences in the randomly assigned treatments, eg ask patients to drink 12oz of water with pill, rather than whatever amount they want

Question 29

What is randomization in study design?

Answer 29

Randomize cases into treatment groups to account for variables that cannot be controlled, eg some patients might be more susceptible to a disease due to their diet, randomization also prevents accidental bias

Question 30

What does it mean to replicate an experiment design?

Answer 30

Replicate is creating a sufficiently large sample or replicate the entire study to verify an earlier finding.

Question 31

What does it mean to block for an experimental design?

Answer 31

Block for variables known or suspected to affect the outcome ie, when testing energy gel, the pro status of an athlete might affect results, so you would assign equal number of pro and amateur, and randomly assign each group to gel or no gel

Question 32

Define blocking or explanatory variables (factors)

Answer 32

conditions we can impose on experimental unit
eg: response variable- exam performance, block variable- gender (known or suspected to affect outcome), explanatory variables- light and noise (might be affecting the outcome)

Question 33

Define treatment groups vs control group

Answer 33

Treatment group receives the drug, or treatment, control does not

Question 34

What is a double blind exp?

Answer 34

When both experimental units and experimenters don’t know treatment

Question 35

What is random sampling?

Answer 35

Each subject is equally likely to be selected- likely generalizable to population at large

Question 36

What is random assignment?

Answer 36

When differently characterized subjects are represented equally, it allows us to make causal conclusions, this is only in experimental situations

Question 37

Is the experiment causal or generalizable? if:
random assignment
random sampling

Answer 37

Causal and generalizable

Question 38

Is the experiment causal and generalizable? if:
random sampling
no random assignment

Answer 38

not causal but generalizable

Question 39

Is the experiment causal and generalizable? if:
No random sampling
Random assignment

Answer 39

causal but not generalizable

Question 40

Is the experiment causal and generalizable? if:
no random assignment
no random sampling

Answer 40

neither causal nor generalizable

Question 41

Does random assignment affect causation or association?

Answer 41

If random assignment is used, then causation is measured
If no random assignment, then association is measured

Question 42

How does random sampling affect generalizability?

Answer 42

With random sampling, the data is generalizable, without random sampling it is not

Question 43

Is observational data causal and generalizable?

Answer 43

not causal but generalizable

Question 44

What sampling and assignment does an ideal experiment include?

Answer 44

Random sampling and random assignment- not often possible.

Question 45

What is a variable’s levels?

Answer 45

If a variable is categorical, the possible values are called the variables levels

Question 46

Define lurking variable

Answer 46

Similar to confounding variable in that its a variable that affects the results of a study but lurking variables are unknown and unmeasured.

Question 47

Define multistage sampling

Answer 47

Divide population into cluster samples and then collect a random sample from selected clusters.