Influence of collected data
Bias: Already being in favour of one side, Ex: Most people agree that smoking is bad for you and could kill you, do you agree?
Use of Language: Wording a sentence in an easy to understand way. Ex: Are sweatshops good or bad?
Ethics: Are you trying to show the truth? Ex: If there was a poll for the best shoe companies and you can check more than one, but the companies says that 80% of people check yours so you say that but, they also check other things.
Cost: Does it cost more to make the survey than what you get back?
Time and timing: The information is collected at an inappropriate time that would impact the people’s choice. Ex: If you asked Fort McMurray residents if the government should increase fire support.
Privacy: Is the graph kept confidential, do the people have a right to refuse answering the question
Cultural sensitivity: Maybe the graph had a question that offended people from different cultures
Explain the difference between a population and a sample:
Population: A population is a group of objects that have things in common which is relevant to the data being collected. The point of a statistical population is to collect information about a chosen population
Sample: A sample is a set of objects chosen from a complete sample in a random order example: choosing every 10th person who walks through the door. The point of a sample is to collect data that is unbiased.
Explain the different types of sampling methods and the benefits of each
Convenience sample: Made up of people who are easy to reach or contact. Benefit is that the survey will probably be finished quickly. Ex: a survey interviews shoppers at a local mall. If the mall was close to the surveyors business this would be considered a convenience sample.
Random: Chosen in a random order or way. Names in a hat then the person is blindfolded and picks a name. A good thing is that the data will be random and not biased.
Voluntary response: This type of response can easily become bias because the sample members are self-selected for example on the radio when you hear people call in to talk about things like gun control, of course they will chose to be against it because that was what the show was talking about.
Stratified sample: The population is separated into groups based on similar things, then ask a few people from that group. (Ex: male and females, children and adults, similar interests)
Systematic sample: This is where you divide the population size by the desired sample size. This can be bias because they can choose only people who agree with the company. For example: A shoe company starts a poll to see who their favourite shoe company is but, they only ask from the people who frequent their store.
). Give examples. Explain how choosing an inappropriate sampling method may bias the data. Give Examples
Explain the difference between theoretical and experimental probability.
Theoretical Probability: The number of ways a situation could play out, divided by the total number of outcomes. Basically it’s what are the odds of an event happening. What is expected to happen based on the outcomes. Example: a shoebox has 10 red shoelaces, 8 blue shoelaces, and 2 yellow shoelaces. What is the theoretical probability of picking a blue shoelace?
Experimental Probability: The ratio of the amount of times a situation occurs to the total number of times the event is performed. The result of a situation after a number of trials. Example: a box contains 10 pink stuffed animals, 8 purple stuffed animals, and 2 blue stuffed animals. What is the experimental probability of picking a blue marble?
Find 3 examples (different from the examples already discussed in class) of misleading statistics used in the media and explain why they are misleading
This statistic was obviously made by someone who is either selling houses or works in the industry because they are trying to show that the prices barely moved in scale but in reality prices went up 10 000
This statistic makes it seem like Clinton was way worse than Bush for unemployment but if you look at the numbers they are barely different they did not start the numbers at 0.
This statistic is misleading because they started the graph at 7% if it started at 0 it would look like a lot less, they zoomed in on the top.
