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### Course: Statistics and probability>Unit 6

Lesson 2: Sampling and observational studies

# Reasonable samples

To make a valid conclusion, you'll need a representaive, not skewed, sample. Created by Sal Khan.

## Want to join the conversation?

• At , why would asking the whole class be less efficient? Wouldn't the class be the only relevant demographic in this case?
• u still want the answer?... its been 6 years
• I have no idea what your supposed to do to solve this! THIS ISNT EVEN MATH! Can someone tell me how this is math?
• there samples bruh
• So what percent of a number is reasonable. So like if there were 60,000 students in a school, is 50 students a reasonable amount of students to ask their opinions'?
• Rather than a exact percentage, the more important requirement is a random sampling, so 50 may be a reasonable amount if it is truly a random sampling. Think about a presidential race, there is no easy way to get even close to 1% of possible voters (138+ million people voted in 2016, so 1 percent is 1.3 million people, .1% is 138,000, and .01 is still 13,800 voters which is still a lot), so they have to define the parameters of who they chose as opinions.
Statistics can be misleading if it is not random such as the number of toothpaste brands that 4 out of 5 dentists recommend.
• nah this is a riddle bro
• I thought when using a computer to generate something random, that it's not truly random? Rather pseudo-random?
• You are right, but for the purpose of the exercise, it is random.
• What is the main difference between random and systematic?
• in a statistical context

systematic means there is a time or spatial interval of sampling datapoints (say every o'clock to check the humidity in a room) which is predictable (1 hour interval)

random means we have no predictable or biased way to draw a sample (say pick out 6 balls from 45 possible balls in a veiled box)

but some sampling can be complicated and created by combining both (say pick every odd place in the decimals of pi; 3.'1' 4 '1' 5 '9' 2 and so forth)

above case seems systematic since it has a predictable interval, but random too cause after some (quite long) sequences of picking you have no way to predict the next digit of pi thus it is random in some sense

in a word, predictibility is the key difference between random sampling and systematic one
• im sorry huhhh?
• i didn't understand it
• I'm confused. I will always be confused :')
• What is the main difference between systematic and random
• Random sampling involves selecting individuals from a population in such a way that each member has an equal chance of being chosen, ensuring that the sample is representative of the entire population. This method is unbiased and helps to minimize selection bias. On the other hand, systematic sampling involves selecting individuals at regular intervals from a population list or sequence, which can be more efficient but may introduce bias if there is a pattern or periodicity in the population that aligns with the sampling interval. Therefore, while random sampling ensures greater representativeness, systematic sampling requires careful consideration to avoid bias.