2.1-2.4 Stats Quiz Review

Telephone surveys made through pg 100 random-digit dialing used to exclude cell-phone num- bers. If the opinions of people who have only cell phones differ from those of people who have landline service, the poll results may not represent all adults. The Pew Research Center interviewed a sample of cell- only and landline telephone users who were younger than 30 years old. Here’s what Pew found about how these people describe their political-party affiliation. Use the graph to determine if there is an association between type of phone use and political affiliation for the members of the sample.

• There is no association between Phone status and Political party.

• There is no correlation between the two.

• There is an association since the distribution is not the same for each phone status.

• There is an association since the blue and red are really close to the same size.

Favorite vehicle colors may dif- fer among countries. The side-by-side bar chart shows data on the most popular colors of cars in a recent year for the United States and Europe. Based on the graph, is there an association between color preference and where you live? Explain your reasoning. If there is an association, briefly describe it.

• There is an association because the color preference is no the same for the US and Europe.

• There is an association because yellow/gold are basically the same.

• There is an association because silver is really high.

• There is no association.

What is the explanatory variable in this situation? The yield of corn in bushels per acre and the amount of rain in the growing season.

• Yield of corn in bushels per acre

• The amount of rain in the growing season

What is the response variable in this situation? The arm span and the height of the high school seniors.

• The arm span

• The height

• Either one could be it

• Neither makes sense

What do you need to make sure you answer when describing a scatterplot?

• VSCO - Variability, Spread, Center Outliers

• DFOS - Direction, Form, Outliers, Strength

• DFSO - Direction, Form, Spread, Outliers

• VSCO - Variability, Strength, Center, Other

How would you describe this scatterplot?

• Positive, Linear, Moderately strong, 2 outliers at (20,500) and (87,460)

• Negative, nonlinear, moderately weak, no outliers

• Negative, nonlinear, moderately strong, 2 outliers at (20,500) and (87,460)

• No pattern, weak, no outliers

For a long time, the South has lagged behind the rest of the United States in the performance of its schools. Efforts to improve edu- cation have reduced the gap. Does the South stand out if we look at state average SAT Math scores? The figure enhances the scatterplot in Exercise 9, but plots 12 southern states in red.

What does the graph suggest about the southern states?

• Southern states tend to do better on SAT Math than other states.

• Southern states tend to have more students taking the SAT math test.

• Northern states typically have higher mean SAT Math scores than other students with a similar percent of students taking the SAT.

• Southern states typically have lower mean SAT Math scores than other states with a similar percent of students taking the SAT.

One of nature’s patterns connects the percent of adult birds in a colony that return from the previous year and the number of new adults that join the colony. Research on 13 colonies of sparrowhawks shows a linear relationship between these two variables, with a correlation of r = -0.75 Interpret this value.

• For the 13 colonies of sparrowhawks, the correlation is moderately strong and negative.

• For all of the colonies of sparrowhawks, the correlation is moderately strong and negative.

• There is a pretty strong relationship evident.

• The correlation is almost perfectly negative.

Do customers who stay longer at buffets give larger tips? Charlotte, a statistics student who worked at an Asian buffet, decided to investigate this question for her second-semester project. While working as a hostess, she obtained a random sample of receipts, which included the length of time (in minutes) the party was in the restaurant and the amount of the tip (in dollars). Here is a scatterplot of these data.

Does increasing the amount of time spent in the restaurant cause an increase in the amount of the tip?

• Yes because they spend more money.

• Yes because they eat more.

• No, because there may be other factors that affect the tip.

• Not enough information given.