You decide to conduct a similar experiment with 59 toddlers. The results are as follows: Observed Frequencies for Package Preference by Food Type

	Food
Packaging	Hamburger	French Fries	Chicken Nuggets	Baby Carrots	Totals
McDonald's wrapper	12	6	14	10	42
Unbranded wrapper	7	3	5	2	17
Totals	19	9	19	12	59

Chi square analysis does have limitations. What is the potential violation of these limitations with this particular chi square distribution?

There is no problem with this chi square distribution.

The categories are not distinct enough.

There is at least one cell with an observed frequency (fo) of 5 or fewer.

There is at least one cell with expected frequency (fe) of 5 or fewer.

Would the Yates correction for continuity help? If so, why? If not, why not?

Yes, the Yates correction for continuity is the safest course to take corrective action whenever any of the cells have frequencies of 5 or fewer.

No, the Yates correction for continuity works only for 2 2 tables.

No, there is no need for the Yates correction for continuity, because there is no problem with this chi square distribution

.

You want to figure out what it is about the wrapper that the children are recognizing, so you are thinking of adding the chocolate shakewhich is highly recognizableand using several forms of packaging: completely plain packaging, completely branded packaging, packaging with the McDonald's colors, packaging with the McDonald's logo but not the McDonald's colors, and packaging from another fast food chain that does not advertise on television.

What could be a problem with the chi square analysis for this design?

There is no difficulty with a chi square analysis for this design.

There is no difficulty because the children will be getting an opportunity to drink chocolate shakes.

The categories are not distinct enough.

Chi square tests become difficult to interpret when the variables have many categories.