A study wanted to compare the 50 states food expenditures. The researchers measured the amount spent by the state's entire population for food in grocery stores and total amount spent on restaurant food. From their 50 data points (Washington DC not in the study), the researchers calculated a correlation of 0.988. Based on this study, can we say that individuals who spend a lot on groceries also spend a lot at restaurants?

What possible lurking variable is there in this study?

A. The amount of money spent on food varies from person to person
B. How much money a person makes
C. The population of a state
D. Type of restaurant - fast food or more expensive
E. Alcohol costs

D - Type of restaurant - fast food or more expensive.

Step-by-step explanation:

By a lurking variable we mean or refer to any variable that is unknown and not controlled for or out of individual control. When there is one or more lurking variables in any study it could results in accidental bias. According to Soares (1985), lurking variables are intrinsic and they are not actually caused by “accidents” in real sense. Hence he suggests that “lurking-variable bias” is a more suitable name for accidental bias.

Concluding that individuals who spend a lot on groceries also spend a lot at restaurants could be misleading in the sense that, groceries may have a more uniform price than restaurant regardless of your social class. For instance, type of restaurant could determine food cost. At some restaurant, food is quite expensive at another food is quite affordable. I may not to go any groceries store in a month but I patronize restaurant to eat daily.

It is also possible I don't patronize restaurants! And yet, I am frequent at groceries store.

In real sense, what I spent at groceries might be nothing compare to what I spend at restaurant and vice versa. Hence, the possible lurking variable is type of restaurant - fast food or more expensive which is unknown and not controlled for.

linear pair postulates

x= 3^y

step-by-step explanation: