Question

--In a sampling distribution of sample mean differences, each “building block” represents:

a.) a person

b.) a sample mean

c.) the difference between a sample mean and the population mean

d.) the difference between two sample means

--Perhaps kids who live in communities with more potential for face-to-face interaction text less than kids from other types of communities. Using the ANOVA below, compare rural, suburban, and urban youth on the number of texts per day. Explain the results. Given the fairly large observable different in means, why do you think the results turned out the way they did?

Descriptives

On an average day, about how many texts messages do you send and receive on you cell phone?

					95% Confidence Interval For Mean
	N	Mean	Std. Deviation	Std. Error	Lower Bound	Upper Bound
Rural	65	107.63	129.202	16.026	75.62	139.65
Suburban	328	122.29	147.139	8.124	106.31	138.28
Urban	219	123.28	147.711	9.981	103.61	142.95
Total	612	121.09	145.402	5.878	109.55	132.63

ANOVA

On an average day, about how many text messagest do you send and receive on your cell phone?

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	13298.185	2	6649.093	0.314	0.731
Within Groups	12904323.05	609	21189.365
Total	12917621.23	611

Answer 1

--In a sampling distribution of sample mean differences, each “building block” represents:

d.) the difference between two sample means

--------------------

The firt thing all intervals are overlap. So on the basis of confidence interval we cannot say that there is a significanr difference between the means.

Using ANOVA, the p-value is 0.731. This is large so we fail to reject the null hypothesis that all populaiton meana are equal. It is because between group variance (MSB) is less than within group variance (MSE). That is we can say that difference is due to chance alone.