Sampling Design

How do we gather data? Surveys Interviews Studies Experiments Observational Retrospective (past) Prospective (future) Experiments

Population the entire group of individuals that we want information about

Census a complete count of the population

How good is a census? Do frog fairy tale . . . The answer is 83!

Why would we not use a census all the time? Not accurate Very expensive Perhaps impossible If using destructive sampling, you would destroy population Breaking strength of soda bottles Lifetime of flashlight batteries Safety ratings for cars Look at the U.S. census – it has a huge amount of error in it; plus it takes a long to compile the data making the data obsolete by the time we get it! Since taking a census of any population takes time, censuses are VERY costly to do! Suppose you wanted to know the average weight of the white-tail deer population in Texas – would it be feasible to do a census?

Sample A part of the population that we actually examine in order to gather information Use sample to generalize to population

Sampling design refers to the method used to choose the sample from the population

Sampling frame a list of every individual in the population

Jelly Blubber Activity Select 10 Jelly blubbers that you think are representative of the population of blubbers in regards to length. Find the mean length of your sample

For the Jelly Blubber colony: = 1.941 cm = 19.41 mm

Simple Random Sample (SRS) Suppose we were to take an SRS of 100 BHS students – put each students’ name in a hat. Then randomly select 100 names from the hat. Each student has the same chance to be selected! Not only does each student has the same chance to be selected – but every possible group of 100 students has the same chance to be selected! Therefore, it has to be possible for all 100 students to be seniors in order for it to be an SRS! consist of n individuals from the population chosen in such a way that every individual has an equal chance of being selected every set of n individuals has an equal chance of being selected

Stratified random sample Homogeneous groups are groups that are alike based upon some characteristic of the group members. Suppose we were to take a stratified random sample of 100 BHS students. Since students are already divided by grade level, grade level can be our strata. Then randomly select 50 seniors and randomly select 50 juniors. population is divided into homogeneous groups called strata SRS’s are pulled from each stratum

Systematic random sample Suppose we want to do a systematic random sample of BHS students - number a list of students (There are approximately 2000 students – if we want a sample of 100, 2000/100 = 20) Select a number between 1 and 20 at random. That student will be the first student chosen, then choose every 20th student from there. select sample by following a systematic approach randomly select where to begin

Cluster Sample based upon location Suppose we want to do a cluster sample of BHS students. One way to do this would be to randomly select 10 classrooms during 2nd period. Sample all students in those rooms! based upon location randomly pick a location & sample all there

Multistage sample To use a multistage approach to sampling BHS students, we could first divide 2nd period classes by level (AP, Honors, Regular, etc.) and randomly select 4 second period classes from each group. Then we could randomly select 5 students from each of those classes. The selection process is done in stages! select successively smaller groups within the population in stages SRS used at each stage

SRS Advantages Disadvantages Unbiased Easy Large variance May not be representative Must have sampling frame (list of population)

Stratified Disadvantages Advantages More precise unbiased estimator than SRS Less variability Cost reduced if strata already exists Disadvantages Difficult to do if you must divide stratum Formulas for SD & confidence intervals are more complicated Need sampling frame

Systematic Random Sample Advantages Unbiased Don’t need sampling frame Ensure that the sample is spread across population More efficient, cheaper, etc. Disadvantages Large variance Can be confounded by trend or cycle Formulas are complicated

Cluster Samples Advantages Disadvantages Unbiased Cost is reduced Sampling frame may not be available (not needed) Disadvantages Clusters may not be representative of population Formulas are complicated

Identify the sampling design 1)The Educational Testing Service (ETS) needed a sample of colleges. ETS first divided all colleges into groups of similar types (small public, small private, etc.) Then they randomly selected 3 colleges from each group. Stratified random sample

Identify the sampling design 2) A county commissioner wants to survey people in her district to determine their opinions on a particular law up for adoption. She decides to randomly select blocks in her district and then survey all who live on those blocks. Cluster sampling

Identify the sampling design 3) A local restaurant manager wants to survey customers about the service they receive. Each night the manager randomly chooses a number between 1 & 10. He then gives a survey to that customer, and to every 10th customer after them, to fill it out before they leave. Systematic random sampling

Numbers can be read across. Random digit table Numbers can be read vertically. The following is part of the random digit table found on page 847 of your textbook: Row 1 4 5 1 8 5 0 3 3 7 1 2 4 2 5 5 8 0 4 5 7 0 3 8 9 9 3 4 3 5 0 6 3 Numbers can be read diagonally. each entry is equally likely to be any of the 10 digits digits are independent of each other

Ignore. Ignore. Ignore. Ignore. Suppose your population consisted of these 20 people: 1) Aidan 6) Fred 11) Kathy 16) Paul 2) Bob 7) Gloria 12) Lori 17) Shawnie 3) Chico 8) Hannah 13) Matthew 18) Tracy 4) Doug 9) Israel 14) Nan 19) Uncle Sam 5) Edward 10) Jung 15) Opus 20) Vernon Use the following random digits to select a sample of five from these people. We will need to use double digit random numbers, ignoring any number greater than 20. Start with Row 1 and read across. 1) Aidan 13) Matthew 18) Tracy 5) Edward 15) Opus Ignore. Ignore. Ignore. Ignore. Stop when five people are selected. So my sample would consist of : Aidan, Edward, Matthew, Opus, and Tracy Row 1 4 5 1 8 0 5 1 3 7 1 2 0 1 5 5 8 0 1 5 7 0 3 8 9 9 3 4 3 5 0 6 3

Bias A systematic error in measuring the estimate favors certain outcomes Anything that causes the data to be wrong! It might be attributed to the researchers, the respondent, or to the sampling method!

Sources of Bias things that can cause bias in your sample cannot do anything with bad data

Remember – the way to determine voluntary response is: People chose to respond Usually only people with very strong opinions respond An example would be the surveys in magazines that ask readers to mail in the survey. Other examples are call-in shows, American Idol, etc. Remember, the respondent selects themselves to participate in the survey! Remember – the way to determine voluntary response is: Self-selection!!

Convenience sampling Ask people who are easy to ask The data obtained by a convenience sample will be biased – however this method is often used for surveys & results reported in newspapers and magazines! Ask people who are easy to ask Produces bias results An example would be stopping friendly-looking people in the mall to survey. Another example is the surveys left on tables at restaurants - a convenient method!

People with unlisted phone numbers – usually high-income families Undercoverage some groups of population are left out of the selection process People without phone numbers –usually low-income families Suppose you take a sample by randomly selecting names from the phone book – some groups will not have the opportunity of being selected! People with ONLY cell phones – usually young adults

Suppose we wanted to survey high school students on drug abuse and we used a uniformed police officer to interview each student in our sample – would we get honest answers? Response bias occurs when the behavior of respondent or interviewer causes bias in the sample wrong answers Response bias occurs when for some reason (interviewer’s or respondent’s fault) you get incorrect answers.

Wording of the Questions The level of vocabulary should be appropriate for the population you are surveying Questions must be worded as neutral as possible to avoid influencing the response. wording can influence the answers that are given connotation of words use of “big” words or technical words – if surveying Podunk, TX, then you should avoid complex vocabulary. – if surveying doctors, then use more complex, technical wording.

Source of Bias? 1) Before the presidential election of 1936, FDR against Republican ALF Landon, the magazine Literary Digest predicting Landon winning the election in a 3-to-2 victory. A survey of 2.8 million people. George Gallup surveyed only 50,000 people and predicted that Roosevelt would win. The Digest’s survey came from magazine subscribers, car owners, telephone directories, etc. Undercoverage – since the Digest’s survey comes from car owners, etc., the people selected were mostly from high-income families and thus mostly Republican! (other answers are possible)

Convenience sampling – easy way to collect data 2) Suppose that you want to estimate the total amount of money spent by students on textbooks each semester at SMU. You collect register receipts for students as they leave the bookstore during lunch one day. Convenience sampling – easy way to collect data or Undercoverage – students who buy books from on-line bookstores are included.

(other answers are possible) 3) To find the average value of a home in Plano, one averages the price of homes that are listed for sale with a realtor. Undercoverage – leaves out homes that are not for sale or homes that are listed with different realtors. (other answers are possible)