DECK 5 UNIT 3 part A

Question 1

What are the two types of observational studies?

Answer 1

Retrospective, and Prospective

Question 2

What is retrospective study?

Answer 2

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

Question 3

What’s the difference between a prospective and a retrospective study?

Answer 3

A retrospective study takes a group and looks back at its history while a prospective study watches a group for a period of time and records the data along the way into the future.

Question 4

What is prospective study?

Answer 4

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

Question 5

Is it always better to do a census or to sample?

Answer 5

depends on the availablility of the data. If the you want to look at SAT vs GPA, you may easily be able to get all of the school’s data and do that study (a census). If you have to go out and get the info, you may want to take a sample to save time and energy.

Question 6

What is a simple random sample?

Answer 6

put all of the names in a hat. every group is possible. pull the numbers

Question 7

What are the “good” sampling methods?

Answer 7

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

Question 8

What are the “bad” sampling methods.

Answer 8

convenience samples, voluntary samples

Question 9

What is random sampling?

Answer 9

When we use chance to select a sample, like rolling dice, a random number generator, or a random number table in our selection process. We use randomization in all of the “GOOD” sampling methods.

Question 10

What is systematic sampling?

Answer 10

collecting data from every nth subject.

Question 11

What is stratified sampling?

Answer 11

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

Question 12

What is cluster sampling?

Answer 12

Cluster- grab clusters of the population. each cluster should be representative ( like the population) use a few clusters.

Question 13

What is a multistage sample?

Answer 13

A sample that combines several sampling methods

Question 14

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

Answer 14

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

Question 15

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

Answer 15

Get an alphabetical list of all of the students, 2000/40=50. Randomly choose one of the first 50 students and then every 50th student after that.

Question 16

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

Answer 16

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 17

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

Answer 17

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 18

A 4 year high school of 2000 students, sampling 40 high students: Explain how stratifying has “impossible groups”

Answer 18

You couldn’t get all freshmen in your sample

Question 19

A 4 year high school of 2000 students, sampling 40 high students: Explain how systematic has “impossible groups”

Answer 19

You couldn’t get the first 40 people alphabetically (because you are taking every nth)

Question 20

A 4 year high school of 2000 students, sampling 40 high students: Explain how clustering has “impossible groups”

Answer 20

You couldn’t get 2 people from each classroom, because you would be randomly choosing classrooms and asking everyone in those classes.

Question 21

A 4 year high school of 2000 students, sampling 40 high students: Since ALL GROUPS (samples) are possible and equally likely, show some groups that you could get randomly from and SRS that would not be representative of the entire school.

Answer 21

all female, all freshmen, all seniors, all athletes.. these could happen in an SRS (but they are not likely to)

Question 22

What are the differences between the subjects in strata and the subjects in clusters?

Answer 22

the “strata” are homogeneous, or have similar traits within, but each strata are different from the other strata. The clusters may be heterogeneous, or have mixed traits within, but each cluster is similar to the other clusters.

Question 23

Suppose you want to see the relationship between gender and candy preference in squirrels. How may you do a stratified vs cluster sample

Answer 23

STRATIFIED: You can split the list of all of the squirrels in your neihborhood by gender and randomly select 20 males from th list of all of the males, and then 20 females (strata) from all of the females. CLUSTER: you can randomly choose to 5 different trees and survey all of the squirrels in those trees, assuming that there are 4 squirrels living in each tree (clusters, the trees have both M and F).

Question 24

What is the standard sampling method? (the gold standard)

Answer 24

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 25

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

Answer 25

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

Question 26

What is a weakness of a SRS?

Answer 26

Suppose you want a sample of 50 high school students, with an SRS, although unlikely you could get “all freshmen” which wouldn’t be representative.

Question 27

In which sampling methods do all subjects have the same probability of being chosen?

Answer 27

SRS, cluster, systematic and stratified all give subjects equal likelihood of being chosen.

Question 28

In which sampling methods do all GROUPS have the same probability of being chosen?

Answer 28

Only in SRS do all GROUPS have the same probability of being chosen, all of the other methods have IMPOSSIBLE GROUPS.

Question 29

Systematic, how do you find the N for every nth subject, and then how do you proceed?

Answer 29

TOTAL POP/SAMPLE SIZE= your n (round down). Then use RAND INT to Randomly choose first. RANDINT(1, n). And then take every nTH.

Question 30

What is the problem with convenience sampling?

Answer 30

The sample may not be representative as it is not randomized to include every type of person. Friends and family are convenient but they likely share similar opinions and thus the sample is not representative of a population.

Question 31

What is wrong with using volunteers in a survey?

Answer 31

(Volunteers are often upset or emotionally attached) Those who volunteer may not be like the rest of the population. An example may be, if you’re trying to find our how often people volunteer for things. So you ask for volunteers to take the survey. A question may be “when was the last time you volunteered for something?” Well. they all just volunteered for the survey!

Question 32

What’s the difference between stratified and cluster sampling?

Answer 32

Stratified- you divide the population up into groups with similar traits, called strata (homogeneous groups) and randomly choose a few from each strata.

Question 33

give an Example of a MULTISTAGE sample

Answer 33

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 34

In which sampling methods do the subjects have equal chances of being selected?

Answer 34

SRS, Stratified, Clustered, Systematic, and multistage. In all of these, the subjects have an equal chance (but groups have different chances)

Question 35

What is a quality of SRS that is not a quality of Systematic, Stratified or Clustering?

Answer 35

In an SRS, all groups are possible, and ALL POSSIBLE GROUPS have the same chance of being picked (like all senior male students.).The other methods have lots of impossible groups. SRS has no impossible groups. Example: -Stratified- an impossible group would be all girls (you’re taking some boys and girls)-Clustered- an impossible group would be all girls (each cluster has boys and girls)-systematic- an impossible group would be first 10 people that are right next to each other (you are taking every nth person, so you will skip)

Question 36

What is a sampling frame?

Answer 36

It is the frame from which you get your sample. For instance, if you call people the frame would be “people with phones”

Question 37

How is a sampling frame different from the population?

Answer 37

Suppose you are wondering how elderly people on the cape feel about a new medicare law. If you go to nursing homes and randomly sample residents, then the frame is “elderly people at those nursing homes.” Your population is still elderly people on cape cod.

Question 38

How are voluntary and convenience samples similar…

Answer 38

With voluntary, people choose them selves, with covenience, the people are just chosen by researcher, neither uses randomness and both are prone to BIAS.

Question 39

Why do you have to Stratify?

Answer 39

You don’t have to.. But you might want to if you feel that a simple random sample might not be representative of the population . You want your sample to be like the population. a representative sample (it represents the population well).

Question 40

What is a representative sample?

Answer 40

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

Question 41

What is BIAS in sampling?

Answer 41

A systematic FLAW in your method.

Question 42

Will larger samples reduce BIAS?

Answer 42

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 43

what is the best way to reduce bias?

Answer 43

randomness and good sampling methods.

Question 44

What is sampling error?

Answer 44

How far your statistic is from the parameter (how far your calculation from your sample was from the population parameter)

Question 45

Can you eliminate sampling error?

Answer 45

Only if you take a census. Larger samples have less error.

Question 46

How can you decrease sampling error?

Answer 46

Get a larger sample

Question 47

When your sampling frame is different from the population, then you risk ____

Answer 47

undercoverage

Question 48

Is sampling error a mistake?

Answer 48

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 49

What is wording bias

Answer 49

A type of response bias, When the wording of the question impacts response to it. (type of response bias)

Question 50

When we say “statistics vary” or the “variablility of statistics” are we talking about data from an individual?

Answer 50

NO… we are stating that summaries of samples (statistics) will vary from sample to sample. Statistics from one sample will differ from statistics from another sample and they will also differ from the parameters. The distance your statistic is from the parameter is called the ERROR.

Question 51

Example of wording bias

Answer 51

Do you support food assistance and nutrition programs for children living in poverty? VS. Do you approve of supporting lazy people on welfare?

Question 52

Example of undercoverage

Answer 52

You only ask people who go to Home Depot about their views on school lunches.

Question 53

Example of nonresponse bias

Answer 53

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)

Question 54

Example of response bias

Answer 54

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 55

How can the WORDING of the question lead to response bias

Answer 55

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 56

What is the difference between response bias and nonresponse bias?

Answer 56

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 57

What is response bias? How do you avoid it?

Answer 57

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 58

What is undercoverage?

Answer 58

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

Question 59

What is difference between non response bias and undercoverage?

Answer 59

You may ask someone to take a survey, they may say no. They may feel differently than the people who decide to take the survey. In this case, that is non-response bias. Undercoverage happens when you didn’t even ask some people to take the survey. The people you didn’t even ask might feel different.

Question 60

To make a survey to tell of a restaurant is good, would you ask the people coming out of the restaurant?

Answer 60

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 61

How is BIAS different from SAMLING error

Answer 61

Bias is a systematic flaw in your sampling method. Sampling error is always present even with the best methodology.

Question 62

An unbiased sampling method will eliminate error

Answer 62

No, error is always there. Error is not a mistake.

Question 63

How are statistics and parameters different?

Answer 63

A statistics is a numerical description of a sample, and a parameter is a description of a population. The difference between these is called ERROR (sampling error).

Question 64

Name types of bias

Answer 64

undercoverage, non response, response, voluntary

Question 65

How is undercoverage different from non response

Answer 65

undercoverage you don’t even ask people, non-response you ask, but they don’t answer.

Question 66

Things that cause nonresponse bias ?

Answer 66

(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,

Question 67

Suppose you sample 150 people randomly from a city to make an inference about the city, and then you sample 150 people randomly from around the country to make an inference about the entire country, which will you be more confident in????

Answer 67

It will tell you just as much about both. Same reliability (if sample is representative). Sample size determines confidence. To get more confidence you need a larger sample (not a smaller population)

Question 68

How can you use random numbers to sample?

Answer 68

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 69

How is an observational study different from an experiment?

Answer 69

In an experiment you assign treatments and manipulate the environment. In studies you just gather information.

Question 70

When choosing clusters, what do you have to check for?

Answer 70

You want to make sure the clusters are similar to each other before you randomly choose them.