A member of the park service believes the average number of cacti per square km in tucson, az in the year 2001 is less than the average number of cacti per square km in tucson, az in the year 1970. for this study, he will make use of data from a 1970 study in which a random sample of 15 plots of land (each 1 square km) was taken around tucson, az. the park service researcher goes back to those exact same plots, and re-measures the number of cacti per square foot for each plot. below are the results from the analysis of this data.

Question Continuation

a. What is a subject in this study?

b. What is the explanatory variable and what type of variable is it?

c. Which type of test is most appropriate?

See Explanation Below

Explanation:

a.

In research, a subject can be referred to as a person, place, thing, or phenomenon that is being measured of observed. In the question above, the observation is focused on the area of cacti/km² plot of land near Tucson, AZ; hence, it'll be taken as the research subject.

b. Explanatory variables are those variables that are not totally independent and are used to predict or explain differences in the response variable.

Having pointed what an explanatory variable is, we'll list the explanatory variable(s) in the question, using the definition above.

1. Year;

The question compares the growth of cacti per km² in 1970 and 2001. The differences in the growth are then measured in order to determine if there's indeed a growth or a decline in growth of cacti.

Hence, year is an explanatory variable and it's numerical

2. Using the same yardstick, another explanatory variable in the question above is the average number of cacti per km².

It is considered an explanatory variable because it represent the numerical value of cacti present in a km² area.

It is also numerical

c.

The most appropriate type of test in this kind of observation is the independent sample t test.

An Independent Samples t Test takes into consideration the means or averages of two independent groups and then make makes comparison between them in order to determine whether there is statistical evidence that the associated population means are significantly different.

The question compares the average of cactus in 1970 and 2001.

The keyword here is average and that is what is being described by the independent sample t test. I.e. the average of cactus per km² in both years.