Data Collection Methods

Used to test the effectiveness of a new treatment or drug.
A large group of subjects is divided into two groups:
- Experimental Group: Receives the new drug.
- Control Group: Receives a placebo (a pill that looks identical to the drug but has no active ingredients).
Participants are unaware of which group they are in to eliminate bias.
The researcher monitors the groups over time to see if there's a difference in outcomes (e.g., fewer incidents of heart disease).
Statistics are used to analyze the data and determine if the drug is effective.
Ethical considerations:
- It is unethical to conduct experiments that could harm participants (e.g., telling pregnant women to smoke).

Used when it's unethical or impractical to manipulate the environment.
Researchers observe and collect data without intervening or influencing participants' behavior.
Participants make their own decisions, and researchers record what happens, such as taking a thousand pregnant women and noting which ones of them smoke
Example: Studying the effects of smoking on pregnant women and their children.
Researchers note which women smoke and observe the outcomes for their children.
Statistical analysis helps draw conclusions about the effects of smoking on pregnant women.

A common method for gathering data about a large population.
A small subset of the population, called a sample, is selected to participate in the survey.
Participants are asked questions about their opinions, behaviors, or characteristics.
The results from the sample are used to draw conclusions about the entire population.
Example: Surveying voters to determine their voting preferences.
Potential issues:
- Conclusions may not be valid if the sample is not representative of the population.

Convenience Sample
- Researchers survey people who are easily accessible or convenient to reach.
- Example: Surveying people on a street corner or making random telephone calls.
- Problem: Often biased because it doesn't represent the entire population.
- Some segments of the population may be ignored (e.g., people who are working or people who look suspicious).
Self-Selection (Voluntary Sample)
- Participants volunteer to take the survey.
- Problem: People with strong opinions are more likely to participate, leading to biased results.
- Example: Student evaluations of instructors, where students with very positive or negative experiences are more likely to respond.
Systematic Sample
- Researchers select participants in a systematic way (e.g., every tenth person on a list).
- Aim is to represent the entire population from A to Z.
Simple Random Sample
- The best method for conducting a survey.
- Researchers use a computer or calculator to generate random numbers to select participants.
- Each person in the population has an equal chance of being selected.
- Example: Numbering students from 1 to 1500 and using a random number generator to select participants.
- $RANDINT(1, 1500)$
- This method eliminates bias because the selection process is random and not controlled by the researcher or participants.