Mean and Variability in Data

The video tutorial explores the concept of variability in data distributions, focusing on temperature data from New York City and San Francisco. It compares the means and variability of these cities using dot plots. The tutorial also analyzes student travel times and variability in jelly bean counts from different candy manufacturers, emphasizing the importance of understanding variability in data.

What is the main factor Robert is considering when deciding between New York City and San Francisco?

• Job opportunities

• Cost of living

• Climate

• Proximity to family

How is the mean temperature for a city calculated?

• By finding the median of the temperatures

• By adding all monthly temperatures and dividing by 12

• By taking the highest and lowest temperatures and averaging them

• By using the temperature of the hottest month

What is the mean monthly temperature for New York City?

• 65°F

• 64°F

• 63°F

• 62°F

Which city has a wider range of temperatures throughout the year?

• Both have the same range

• New York City

• San Francisco

• Neither city has a wide range

If Robert prefers a city with less temperature variability, which city should he choose?

• Neither city

• San Francisco

• New York City

• Either city

In the student travel time exercise, what is the mean time for the morning commute?

• 12 minutes

• 18 minutes

• 14 minutes

• 16 minutes

Which distribution of student travel times has more variability?

• Neither has variability

• Morning

• Afternoon

• Both have the same variability

For which candy manufacturer is the mean a better indicator of a typical value?

• Yum

• Best

• All Good

• Delight

What is the mean number of green jelly beans for each candy manufacturer?

• 46

• 42

• 40

• 44

Which candy manufacturer has the greatest variability in the number of green jelly beans?

• Sweet

• Delight

• Best

• All Good