MAP4C: Statistical Literacy: Survey ProjectDue Dates: Choice of variables ______

Questionnaire: ______

Name: ______Collection method: ______

Name of partners : ______Final Project:______

Self & peer evaluation: ______

Goal: To prepare and use a survey that compares 2 variables.

Survey & Report:For this project you will be defining a population, selecting an appropriate sample size, designing the questions and layout for your survey. You will be collecting primary dataon an issue that interests you and then reporting on this issue using tables, graphs etc as well as a written report(one /group.)

Method:Work in groups of 2 to 3 people.

  • Choose 2 variables to compare. ______& ______
  • Clearly define the population you will sample.
  • Decide what your sample size should be to get valid results(minimum of 10).

Justify your choice.

  • Determine which sampling technique you need to use to get a representative sample.

Justify your choice.

  • Clearly define the purpose of your survey. What do you want to find out about the population? Whatdata do you need to collect to get that information?
  • Design a questionnaire that will enable you to gather the data you need.
  • Make sure your questions are clear, precise unbiased.(Min of 10 questions & a Max of 15.)
  • Decide on an acceptable method of collecting your data
  •  Discuss your method with your teacher to get approval.
  • Distribute and conduct your survey. Record your results (collect your data)
  • Display your data in a table on a graph. If possible also give an equation of the line of best fit & a correlation coefficient.
  • Analyse your data;
  • What does the data mean?
  • Can any significant conclusions be drawn from your data?
  • If yes – what are these conclusions?
  • What improvements could be made to your questionnaire &/or data gathering techniques etc to give more incite regarding the relationship between the two variables chosen? (IeHow could your survey be improved?)
  • Use of quantitative tools to analyse your data should be considered.
  • (correlation coef, mean, median, mode, range, percent)
  • YourReport (one /group) will include;
  • A title page
  • An introduction which explains your topic and why you chose it?
  • (define the purpose of your survey)
  • An explanation of how you arrived at the different survey questions,
  • Who took the survey and where you did the survey.
  • (Population, sample, sampling technique)
  • A blank copy of your survey.
  • The raw data organized in your tally chart.
  • Your graphs neatly done including title, labels, units(axis etc).
  • A conclusion to the overall survey. Were there any problems with the survey? Explain. What (if anything) would you do differently next time?

Resources:

Text ch 4 & 3; Glossary etc;Internet; other; The following terms/definitions/considerations:

Types of Data

  • Numerical Data
  • Discrete:consists of whole numbers (ex. Number of trucks)
  • Continuous:measured using real numbers (ex. Measuring temperature.)
  • Collecting Data
  • Primary:collected by yourself
  • Secondary:collected by someone else
  • Organizing Data
  • Micro Data:information about an individual
  • Aggregate Data:grouped data about a group; summarized data.
  • Other Terms
  • Population:entire group of people being studied
  • Sample:the part of the population being studied
  • Inference:conclusion made about the population based on the sample

Sampling Techniques –

Characteristics of a good sampleEach person must have an equal chance to be in the sample

Sample must be large enough to represent the population

  • Simple Random:each member has equal chance of being selected
  • Ie, picking members randomly apartments
  • Sequential Random:go through population sequentially and select members
  • Ie, Selecting every 5thperson
  • Stratified Sampling:a strata is a group of people that share common charactoristics
  • Constraints the proportion of members in the strata from the population in the sample
  • Ie, Each strata is represented based on their proportion in the population
  • Cluster Sampling:random sample of 2 representative group
  • Ie, picking 1 floor of people and survey them
  • Multi-Stage Sampling:several levels of sampling
  • Ie, Randomly selecting provinces, random cities, then random people.
  • Voluntary Response Samples:invite members of the entire population to participate in the survey
  • Ie, Sending the survey to everyone in the hotel
  • Convenience Sample:easily accessible members are selected
  • Ie, Asking people at the mall who walks closest to you

Types of Bias: Good survey Questions are simple, specific, ethical, free of bias, and respects privacy

  • Survey questions should not use jargon, abbreviations, negatives, leading questions, and insensitivity
  • Sampling Bias:occurs when the chosen sample doesn’t reflect the population
  • Ie, Asking basketball players about math issues
  • Non-Response Bias: occurs when particular groups are under-represented in a survey because they chose not to participate.
  • Ie, when respondents don’t respond, it leads the surveyor to make up their own thoughts
  • Measurement Bias:occurs when the data collection method consistently under- or overestimates a characteristic of the population
  • Leading questions also cause data over/under estimation
  • Ie, police radar gun measuring for average speed of the road
  • Response Bias:when participants in a survey give false or misleading answers
  • Question quality might lead to response bias
  • Ie, A teacher asks class to raise their hands if they have completed their homework

Cause and Effect

  • Cause and Effect
  • A change in X causes a change in Y (ex. Time and tree trunk diameter)
  • Common Cause
  • An external factor causes two variables to change in the same way
  • ex. Correlation between ski sales, and video rentals  Where it’s caused by colder weather
  • Accidental Relationships
  • A correlation without any casual relationship between the variables
  • Ie Increase in SUV sales causes increase in chipmunk population
  • Presumed Relationship
  • A correlation that does not seem to be accidental even though no cause-and-effect or common cause relationship is apparent
  • Ie. A correlation between the person’s level of fitness & the # of action movies they watch.
  • Critically Thinking about Data; When analyzing data, we should ask:
  • Source:How reliable/current is the source?
  • Sample:Does the sample reflect the population?Was the sampling technique free from bias?
  • Graph:Is the graph accurately portrayed?
  • Correlation:Is the correlation between the variables strong enough to make inferences?
  • Is the causation assumed just because there is a correlation?
  • Are there extraneous variables impacting the results?