1. The time series component(s) that reflectsvariations of low frequency in a time seriesis called the
	a	seasonal component.
	b	trend component.
	c	cyclical component.
	d	all of these.

2. Suppose that observe that everytime around the holidays, sales at retail stores go up in a time series. This would be an example of a...

	a	seasonal component.
	b	trend component.
	c	cyclical component.
	d	all of these.

3. A sample of 11 individuals shows the following monthly incomes.

	Individual	Income ($)
	1	1,500
	2	2,000
	3	2,500
	4	4,000
	5	4,000
	6	2,500
	7	2,000
	8	4,000
	9	3,500
	10	3,000
	11	43,000

Which of the following is the least representative measure of the "central value" for this data set?

	a	Mean
	b	Median
	c	Mode
	d	Range

4. Below we have the monthly incomes of 11 individuals.

	Individual	Income ($)
	1	4,500
	2	2,000
	3	2,500
	4	1,000
	5	1,000
	6	2,500
	7	2,000
	8	5,000
	9	3,500
	10	3,000
	11	13,000

Depending on whether or not this data represents the population, or asampleof the population, then

	a	The sum of squared errors may differ in both cases and, the population standard deviation will be smaller than the sample standard deviation.
	b	Although the sum of squared errors are the same in both cases, the population standard deviation will be smaller than the sample standard deviation.
	c	The sum of squared errors are the same in both cases, as well as the the population and sample standard deviations.
	d	Although the sum of squared errors are the same in both cases, the population standard deviation will be larger than sample standard deviation.
	e	Interestingly, it turns out that the population mean and standard deviations are actually the same as our estimates of them.

5. To find out whether violent crime rates differ by region, a researcher has regressed the violent crime rate (measured in acts per 100 000 residents) on a constant and regional dummy variables. How would you interpret the regression coefficient for the "West" dummy?

Multiple Regression for Violent Crime Rate
	Multiple	R-Square	Adjusted	StErr of
Summary	R	R-Square	Estimate
	0.4660	0.2172	0.1672	240.273231
	Degrees of	Sum of	Mean of	F-Ratio	p-Value
ANOVA Table	Freedom	Squares	Squares
Explained	3	752760.9105	250920.3035	4.3464	0.0088
Unexplained	47	2713367.599	57731.22552
	Coefficient	Standard	t-Value	p-Value	Confidence Interval 95%
Regression Table	Error	Lower	Upper
Constant	423.3076923	66.63980418	6.3522	< 0.0001	289.2456984	557.3696862
North	-97.86324786	104.1894626	-0.9393	0.3524	-307.4654109	111.7389151
West	-61.14102564	96.18627221	-0.6357	0.5281	-254.6428463	132.360795
South	200.7511312	88.52580383	2.2677	0.0280	22.66018515	378.8420773

a. The violent crime rate in the South is 200.75 acts per 100 000 residents higher than in the East.

b. The violent crime rate in the South is 200.75 acts per 100 000 residents lower than in the North.

c. The violent crime rate in the South is 200.75 acts per 100 000 residents lower than in the rest of the country.

d. The violent crime rate in the South is 200.75 acts per 100 000 residents.