Chapter 11: Statistics Partner Project
Explain how bias, use of language, ethics, cost, time and timing, privacy, cultural sensitivity on may influence the collection of data. Give examples.
Bias is when the question/statement is favouring one side, usually the writer’s opinion.
Example: With the extreme amount of crime and gang killings occurring recently, do you think that there should be a legalization passed to stop gun ownership?
Use of language uses words to make one side more favourable than another side. The question needs to be understandable to people being asked, and people need to release how the data was collected.
Example: Pepsi made the statement “Most people prefer Pepsi over Coke” after surveying people. However, most could just mean over 50% of people prefer Pepsi. The results could have been 51% prefer Pepsi and 49% prefer Coke, but Pepsi had more so they said most. This is an example of how people can use language to manipulate people into thinking everyone prefers Pepsi over Coke.
Ethics is when you go beyond the appropriate or acceptable behaviour, disrupting or making people feel uncomfortable about the questions you are asking or the way you ask.
Example: You get a call asking if you would like to take a survey. You say that you are busy at the moment and they keep bothering you to answer. This is an example of being unethical. An example of being ethical would be understanding people’s choice of not wanting to answer, and leaving them alone.
Cost can affect the amount of data collected. If it costs a lot to collect data or ask people a survey, they may not ask as many people as they should, compared to the population size. There needs to be a balance between people asked and the population.
Example: “100% of people prefer chocolate ice cream over vanilla.” But, only 1 person was asked. They didn’t ask enough people to get the accurate data, possibly because it costed to much.
Time and timing should be considered when asking a survey. If you ask a survey at a certain time, people may be more likely to pick one answer more than another and the results would be biased.
Example: If you asked people in Texas who are currently experiencing major flash floods if they should have more flood insurance, they are more likely to say “yes” rather than “no.” This is an example of how someone could manipulate the data using timing.
Privacy when collecting data is important because people need to know if what they’re being asked will be confidential. They also need to know that they should have a choice if they want to answer the survey or not.
Example: “Who are you voting for in the presidential election?” should be an anonymous question, because it’s something personal for each person.
Example: If someone asks you to answer a survey but you don’t want to, they should let you say no and move on.
Cultural sensitivity is when you have a question that could be offensive to others with religious or cultural beliefs.
Example: “A woman should never get an abortion because they are wrong. Would you agree or disagree?” This could make people offended if they believe that abortion is fine or they themselves have had one, or it might go against their beliefs.

Explain the difference between a population and a sample. Give examples.
A population is where you ask the entire group of people. It is not always the most effective or cheapest way to collect data, but its more accurate than asking a sample.
Example: You ask the entire school (every single person) if they should make lunch an hour long.
A sample is when you ask a smaller portion of the whole population. There are many different types of samples. It’s cheaper and more effective than a population, but you wouldn’t get as accurate results as if you asked the whole population.
Example: You could do a voluntary sample if they should make lunch an hour long, so anyone who wants to answer the question can.
Explain the different types of sampling methods and the benefits of each. (Convenience sample, random sample, stratified sample, systematic sample and voluntary response sample). Give examples. Explain how choosing an inappropriate sampling method may bias the data. Give examples.
A convenience sample is choosing people to survey that are easy to access. The benefit is that it’s easy to get the information you need.
Example: You ask everyone who leaves the ice cream shop what their favourite flavour of ice cream is.
Random sample is when you collect answers from a randomized portion of the whole population. This means that each person in the whole population has an equal chance of being asked the survey questions.
Example: The government takes a random list of people, and sends each person on the list a letter asking if they would like to take a quick survey.
A stratified sample is a type of random sample where the population gets divided into groups, and then choosing the same fraction of people in each group to get your data from. The benefit of this is you don’t need to survey the entire population but still be able to get data that can be used to make predications about the entire population, with each group having an appropriate amount of say based on how many people there are.
Example: You split the school into grades, with 200 grade 12 students, 400 grade 11 students, 100 grade 10 students, and 300 grade 9 students. You randomly select ¼ of the students in each grade. This would mean you would survey 50 grade 12’s, 100 grade 11’s, 25 grade 10’s, and 75 grade 9 students.
Systematic sample is when a list of people in the whole population is taken and every certain amount of people on the list is chosen to take the survey.
Example: Riverside takes a list of every kid that has been or is in an honours class. They then take every tenth person on the list and ask those select few what their thoughts are on the schools honours program.
A voluntary response sample is where you leave it open for whoever wants to participate to do so. They can pick if they want to participate or not. The benefit of this is it’s easy, and you’ll only get responses from people who actually want to participate and take it seriously.
Example: You make an announcement that you are having a survey asking people what they think of the technology program, and if they would like to participate they can come to the office to fill out the survey.
Explain the difference between theoretical and experimental probability. Give examples.
Theoretical probability is what you think will happen based on the math you used to find it.
Example: You flip a coin, and you expect it will land on heads ½ or 50% of the time.
Experimental probability is the actual outcome when you perform the experiment.
Example: You flip the coin 20 times, and it lands on heads 8/20 times and land on tails 12/20 times.

Find 3 examples (different from the examples already discussed in class) of misleading statistics used in the media and explain why they are misleading.

1. By looking at this chart, you would think that their goal was way off from how many people actually enrolled in Obamacare by the end of the month. But really, its not as big as a difference than you would think by looking at it. This Y-axis doesn’t start at 0, making 6 000 000 look three times smaller than 7 066 000.

2. By looking at the graph, it seems like the amount of people getting cancer screening & other prevention services have gone way down, and the amount of people getting abortions have gone way up, and even passed each other over 7 years.
But if you actually look at the numbers, you’ll see this graph is way off. They make 327 000 abortions look bigger than 935 573 screenings. This graph misleads people into thinking cancer screenings have gone way down, when it really didn’t go down that much, and that abortions have gone way up, when really it only went up 37 250.

3. By looking at the graph, it makes it look like the number of gun deaths after the “Stand Your Ground” law was passed had dropped increasingly.
But if you look at the Y-axis, you could see that it’s upside down, with 0 at the top. So really, the amount of gun deaths hadn’t gone down after the “Stand Your Ground” law was passed, it actually went up by a lot.

By Alyson Vance and Gracyn Kerfers