UNIT 3 FAQ SHORT

Question 1

A 4 year high school of 2000 students, sampling 40 high students: Describe a simple random sample

Answer 1

Number students 1-2000. Use rantom number generator to get 40 unique integers from 1 to 2000.

Question 2

A 4 year high school of 2000 students, sampling 40 high students: Describe a stratified sample

Answer 2

Stratify by year. Randomly choose 10 FR, 10 SO, 10 JU and 10 SENIORS

Question 3

A 4 year high school of 2000 students, sampling 40 high students: Describe a convenience sample

Answer 3

Ask the first 40 students coming to the locker rooms after school. This is problematic because athletes may not have the same preferences as non athletes.

Question 4

A 4 year high school of 2000 students, sampling 40 high students : Describe a systematic sample.
2000/40=50. You need 1 out of each 50.

Answer 4

Get an alphabetical list of all of the students. Randomly choose one of the first 50 students and then every 50th student after that.

Question 5

A 4 year high school of 2000 students, sampling 40 high students: Describe a cluster sample

Answer 5

Imagine that all of art classes have 10 students and they are mixed with fr, so, jr and srs… You would randomly choose 4 classes and survey everyone in each of the 4 classes.

Question 6

What is the standard sampling method?

Answer 6

A Simple Random Sample (SRS) is our standard. Every possible group of n individuals has an equal chance of being our sample. That’s what makes it simple. Put the names in a hat.

Question 7

give an Example of a MULTISTAGE sample

Answer 7

Suppose you want to poll urban, suburban and rural citizens, you can divide a map into those strata, and then randomly choose neighborhoods or streets in each and ask everyone on those streets. Here you stratified by community type and then clustered by street.

Question 8

What are the two types of observational studies?

Answer 8

Retrospective, and Prospective

Question 9

What is cluster sampling?

Answer 9

Cluster- grab clusters of the population. Go to a random class and survey everyone, or go to random street and survey everyone.

Question 10

What is retrospective study?

Answer 10

A retrospective study is a study that looks backwards in time (or at the present moment).

Question 11

What is systematic sampling?

Answer 11

collecting data from every nth subject.

Question 12

What is prospective study?

Answer 12

Prospective study is when you study the experimental unit’s present and future.

Question 13

What is a representative sample?

Answer 13

A sample that looks like the population. It has similar characteristics.

Question 14

What is stratified sampling?

Answer 14

When you break the population into groups with similar attributes and randomly select from each strata.

Question 15

What are the “good” sampling methods?

Answer 15

SRS (simple random sample), stratified, clustered, systematic, multistage

Question 16

What are the “bad” sampling methods.

Answer 16

convenience samples, voluntary samples

Question 17

What is a weakness of SRS?

Answer 17

If you SRS a high school, you could randomly get ALL FRESHMEN.. which wouldn’t be representative. So you would stratify to make sure you get some from each grade.

Question 18

Give four examples of an SRS of size 20 from a population of 650.

Answer 18

1. Number subjects 1-650 and use RANDINT(1,650) and use first unique 20.
2. Number subjects 001-650 and use a random number table. Take 3 digits at a time. Ignore 000 and 651-999. Use the first unique 20.
3. Write names on 650 identical index cards, shuffle them. Choose 20.
4. Write names on 650 identical tennis balls, put them in a cement mixer for 7 hours. Dive in blindfolded and toss 20 out to your friend. Use those 20.

Question 19

What is wording bias

Answer 19

A type of response bias, When the wording of the question impacts response to it. (type of response bias). Often language that invokes emotions. For example. “Do you want to support starving children in America?” vs “Do you support giving welfare money to people who don’t work ?”

Question 20

What is BIAS in sampling?

Answer 20

A systematic FLAW in your method. Under coverage, Wording, Voluntary, Convenience, Comfort (psychological), Response, Non-response BIAS. Even with a larger sample, you will still have bias.

Question 21

What is a sampling frame?

Answer 21

It is the frame from which you get your sample. For instance, if you call people the frame would be “people with phones,” if FOX news takes a poll, the sampling frame is “fox news watchers”

Question 22

When sampling, what kind of sample are we striving to get?

Answer 22

A representative sample, we want our sample to have similar charactaristics as the population

Question 23

To make a survey to tell of a restaurant is good, would you ask the people coming out of the restaurant?
If you had to, what might you add?

Answer 23

People at the restaurant are probably there because they already like it. If you asked the question “Is this your first time dining here?” and if they say “yes” you survey them, that would be a better method. But then again.. the people wouldn’t go into an Italian restaurant if they didn’t like that type of food.

Question 24

What is undercoverage?

Answer 24

Undercoverage is when a group of the population is not represented in the sample (didn’t have a chance). When the sampling frame isn’t representative.

Question 25

What is response bias? How do you avoid it?

Answer 25

Response bias is any influence that may sway the respondent e.g wording of the question, interviewer’s behavior/background. Therefore, in a survey, ask questions that allow respondents to answer comfortably and honestly. Keep the wording “indifferent” or neutral in some way in order to unduly favor one response over another.

Question 26

Things that cause nonresponse bias ?

Answer 26

(remember non response is that the people you ask, or try to ask don’t respond) Lazy researcher, shy survey takers, who is the questioner, environment, person might not want to be judged.

Question 27

What is statistically significant?

Answer 27

When an observed difference is too odd for us to believe that it is likely to have occurred naturally (or just randomly). Basically it is Statistically Significant when we don’t think it happened randomly. when you think “something’s up” or “something’s fishy”

Question 28

How can you use random numbers to sample?

Answer 28

Number the subjects 00-99 (if less than 100) or 000-999 (if less than 1000) or 0000 to 9999 etc.. then use a random number table taking one, two, three or four numbers at a time. Throw out repeats.

Question 29

Name types of bias

Answer 29

undercoverage, non response, response, voluntary

Question 30

How is BIAS different from SAMPLING error

Answer 30

Bias is a systematic flaw in your sampling method. Sampling error is always present even with the best methodology- it is the natural variablility of sample statistics. Different samples give different statistics.

Question 31

name some differences between experiments and observational studies:
(can you remember two of these?)

Answer 31

Here are five.
1. Experiments can prove causation (studies can’t) . 2. In experiments, you assign treatments (studies you just watch) 3. In experiments you can use volunteers (in studies you want representative samples). 4. In experiments you make inference about treatment (In studies you make inference about population). 5. In experiments you randomly assign treatments (in studies you randomly choose subjects).

Question 32

What is the difference between response bias and nonresponse bias?

Answer 32

Response is when the person’s response is influenced by the question or questioning method (like if a parent asks if you use drugs, as opposed to a friend… there is only one answer to this, but one might respond differently to them), non response is is when the people who don’t respond might have different opinions/views than the people who did.

Question 33

Example of response bias

Answer 33

A teenager goes to the doctor’s office with their parents. The doctor asks the teen if they vape. The teen may say “no” because their parent’s are there, even though they do vape.

Question 34

What is the main purpose of a placebo ?

Answer 34

To blind the subject that is being experimented on to avoid influence to the given variable therefore altering the response variable . When people think they’re getting help, they often improve anyway..

Question 35

Example of undercoverage

Answer 35

You only ask people who go to Home Depot about their views on school lunches.
You only ask people in the library about school lunches.
(you only cover people who go to these places)

Question 36

Example of nonresponse bias

Answer 36

In a survey, a person does not answer a few questions (or a person is on your list and you can’t get a hold of them).
You go to someone’s home and they aren’t there.
You tried to ask.. but got no response.

Question 37

How can you decrease sampling error?

Answer 37

Get a larger sample

Question 38

Is sampling error a mistake?

Answer 38

IT IS NOT A MISTAKE!!! Because the data in samples are generally different, the statistics calculated from one sample to another vary and are generally not equal to the parameter. This variablilty of STATISTICS is called sampling error.

Question 39

Can you eliminate sampling error?

Answer 39

Only if you take a census.
Larger samples tend to have less error, but you can never get rid of sampling error when you take a sample.

Question 40

Will larger samples reduce BIAS?

Answer 40

No, bias is a systematic flaw, even large samples will still have bias. If you ask more people outside of McDonalds, you still only get answers from people who eat at McDonalds (large samples can reduce error, however)

Question 41

How can the WORDING of the question lead to response bias

Answer 41

Words or phrases that impact your feelings tend to influence responses. Look for “devastating, horrific, wonderful etc.” Sometimes there is a background story like “Many americans lose jobs to illegal aliens every year, do you feel this is fair”

Question 42

Obs Study vs. Experiment- when do you manipulate environment?

Answer 42

In an observational study, you just collect data observe things. In an experiment you are manipulating the environment.

Question 43

Obs study vs Experiment.What are you making inferences about?

Answer 43

In studies, you are making inferences about the population, in an experiment you are making and inference about a treatment.

Question 44

Obs Study vs. Experiment: How do you use random numbers?

Answer 44

In studies, you are randomly selecting a sample from a population. In a study you are randomly assigning treatments to subjects or subjects to treatments.

Question 45

Obs Study vs. Experiment: Causation?

Answer 45

You can only prove causation in an Experiment. In a study you can just find an association or a correlation.

Question 46

4 INGREDIENTS TO EXPERIMENTS

Answer 46

Compare, control , randomization, replication (and BLOCKING when you need to)

Question 47

4 ingredients: What is “control?”

Answer 47

You want to control the environment as best as you can so that the only difference between groups is the treatment, and the treatment only. Everything else should be similar.

Question 48

4 ingredients: What is “replication?”

Answer 48

Having enough subjects. You don’t want to test fertilizer on just one plant. You want a few plants, or subjects, in each treatment group.

Question 49

4 ingredients: What is “compare?”

Answer 49

Having something to compare your treatment with helps you see its effectiveness. This is why we usually have control groups.

Question 50

4 ingredients: What is “BLOCKING?”

Answer 50

If you think different groups of subjects may respond differently to treatments because of location, gender, age, then you make BLOCKS, and make sure that each block gets all of the treatments - compare within each block. (which med worked best for females?).

Question 51

What are the (three) types of experiments?

Answer 51

1. Completely randomized
2. Randomized block
3. Matched pairs, but matched pair is blocking with 2 in each block.

Question 52

What is a control group?

Answer 52

The group that doesn’t get a treatment (or gets the old treatment). It helps us see the impact of the environment. It gets the placebo or standard care but goes through all of the motions

Question 53

Factors and Levels:
Give medications example

Answer 53

Factor: medication.
Levels: 50mg, 100mg and 200mg.

Question 54

Factors and Levels:
give “sleep” example

Answer 54

Example. For the Factor “SLEEP” the, level(s) would be how many hours the subjects were alowed to sleep.. 4 hours, 6 hours, 8 hours.. 3 levels

Question 55

4 ingredients: What is “randomization?”

Answer 55

You want to randomly assign subjects to treatment groups. (or treatments to subjects)

Question 56

Factors vs Levels:
give example with diets.

Answer 56

DIET PLAN would be a factor and levels could be: low carb, low fat, and no diet

Question 57

Give example of a confounding variable

Answer 57

If you are doing a fertilizer experiment on cloned tomatoes, and fertilizer A is on left, fertilizer B is on right side of room. You find that fert B has larger tomatoes, but then notice they were closer to the windows/sunlight. Now sunlight is a confounding factor- was it the sunlight or was it the fertilizer?

Question 58

A weight loss plan has three diets (A. low carb B. low fat C. no change) and three exercise plans (1. walking 2. weights, 3. no change). What are the factors? The levels? many treatments are there? Can you name the treatments?

Answer 58

Factors: Diet and Exercise
3 levels of DIET: A, B C
3 levels of EXERCISE: 1, 2, 3
9 treatments:
A1, A2, A3
B1, B2, B3
C1, C2, C3

Question 59

Give and example of when you may stratify

Answer 59

If there are different types of subjects in the population, you may want to make sure you get each type. For instance, you may be looking for average tree diameter, so you want to be sure to get some of each tree type in the location. Or if you are sampling students, you may want to make sure you get males and females, so you would break the population up and randomly choose some of each.

Question 60

How is blocking different from stratifying?

Answer 60

Blocking breaks up subjects into pre-existing groups and then you randomly assign the subjects from each group to all of the treatments. This helps you reduce confounding variables.
Stratifying break the population up in to groups, then you randomly sample from each group- this helps you get a more representative sample.

Question 61

Give examples of when you may block

Answer 61

If you are studying fertilizer, you may block by plant type, making sure each veggie gets both fertilizers. Or you may block by proximity to sunlight, a “close to window” group and a “far from window” group. For migraine medicine, you may block according to gender, so that both males and females get each of the treatments. You block when you think underlying characteristics might impact the response.

Question 62

What is a response variable in an experiment?

Answer 62

WHAT YOU ARE MEASURING/comparing!
-mean weight loss
-increased percent participation
-change in mean anxiety score

Question 63

What is wrong with using volunteers in an experiment?

Answer 63

Not much. In an experiment, we are not looking for a sample that is like the population. We just want to see the effectiveness of a treatment. It is fine if the subjects are all similar. In fact it is best sometimes when they are!