Study design

Material based on Chapter 2 Introduction to Modern Statistics

Review

• Types of data collection
  • Experimental vs observational
• Tidy data
• Variables
  • Explanatory vs response variables
  • Associated vs independent
  • Type
    • Numeric: discrete vs continuous
    • Categorical: nominal vs ordinal
• Summary statistics

Learning objectives

You should be able to:

• identify target population for your question
• identify individual case from target population
• describe difference between a census and a sample
• describe difference between sample statistic and a population parameter
• describe anecdotal evidence
• detail why random sampling is important
• describe how bias can be introduced into a sample

Identify the target population for your research question

• Who was the target population for the marketing study?

• What was an individual case from the target population

• Was the sample the same as the target population (census)

Difference sample statistic and population parameter

• Population parameter is what you want to know

• Sample statistic is your estimate of of it based on your sample

Example - E1a

American households spent an average of about $52 in 2007 on Halloween merchandise such as costumes, decorations, and candy.

• To see if this number had changed, researchers conducted a new survey in 2008 before industry numbers were reported.

• The survey included 1,500 households and found that average Halloween spending was $58 per household.

• Identify the population mean and the sample mean

Your turn: E2 Sleeping in college.

• A recent article in a college newspaper stated that college students get an average of 5.5 hours of sleep each night.

• A student who was skeptical about this value decided to conduct a survey by randomly sampling 25 students.

  • On average, the sampled students slept 6.25 hours per night

• Identify the population mean and the sample mean

Your turn: E8 Cats on YouTube

• Want to estimate the percentage of videos on YouTube that are cat videos.

• Use a random video picker to select 1000 videos.

• You find that 2% of these videos are cat videos.

• Determine which of the following is an observation, a variable, a sample statistic (value calculated based on the observed sample), or a population parameter.

  • Percentage of all videos on YouTube that are cat videos.
  • 2%.
  • A video in your sample.
  • Whether a video is a cat video.

Principles of experimental design

• Control - for any differences between groups (treatment and control)

• Randomization - sample into groups to control for confounding factors

  • What could be a confounding factor with the marketing example

• Replication

  • Single study - replicate by collecting a large enough sample
    • Pseudo-replication - fake replication multiple email addresses one person, multiple measurements one person
  • Another study - should be able to replicate results

Observational studies

• Prospective: data in the future identify sample and follow

• Retrospective: data from the past

Your turn E11

• Describe the relationship between life expectancy and percentage of internet users.

• What type of study is this?

• State a possible confounding variable that might explain this relationship and describe its potential effect.

Anecdotal evidence

• A personal story or example that is not based on research or evidence

Bias in sampling

• Non-response bias
  • People who don’t respond are different from those who do
    
• Convenience sampling
  • People who are easy to reach are different from those who are not

Summary

• Identify target population for your question
• Identify individual case from target population
• Describe difference between a census and a sample
• Describe difference between sample statistic and a Population parameter
• Describe anecdotal evidence
• Detail why random sampling is important
• describe how bias can be introduced into a sample

Quiz

• One question on a dataset from an OpenIntro Data Set

• Two questions on definitions in Chapter 2 Study design