1. A bank surveyed a sample ofcustomersregarding theirsatisfaction levels, on a scale from0 (very unsatisfied) to10 (very satisfied).The clients vary by location (urban, suburban, rural, or remote) and byemployment (working, student,or retired). The samplecontains10 customersfrom each combination of location and employment, for a total of 120. The bank then analyzed the satisfaction scores using ANOVA and obtained the results shown below.

Sourcedfp-value

Sample 2 0.043

Columns 30.017

Interaction 60.046

Within108

Total 119

Does employment and/or location have any influence on customer satisfaction?

	Employment has a statistically significant influence on satisfaction
	Location has a statistically significant influence on satisfaction
	Neither employment, nor location, nor their interaction have any statistically significant influence on satisfaction
	Employment, location, and their interaction all have statistically significant influences on satisfaction

2. A winery is examininghowgrape sweetness andgrape acidity influencewine taste. The winery tested 10 batches of grapes and the wine that they were made into. Each characteristic (sweetness, acidity, and taste) was evaluated on a scale of 0 (low) to 10 (high). The winery then analyzed the30 scores using linear regressionand obtained the following results.

Multiple R 0.071

R Square 0.005

Coefficient P-value

Intercept 5.10 0.021

Sweetness 0.020.961

Acidity0.130.037

Which oneof the following statementsbest describes the influence of grape acidityon wine taste?

	The relationship is statistically significant, and it explains a lot
	The relationship is statistically significant, but it explains very little
	The relationship is not statistically significant, but it explains a lot
	The relationship is not statistically significant, and it explains very little

3. Acourier companyis trying to understand why it is receiving complaints about late deliveries. For a sample of 120 deliveries, thecompany recorded the weight of the package (kg), the distance it traveled (km), and theshipping time (days). The company then analyzed thedata using linear regressionand obtained the following results.

Multiple R 0.139

R Square 0.019

Coefficient P-value

Intercept 0.96 0.043

Weight 0.020.973

Distance0.130.018

Which oneof the following statementsbest describes this analysis ofshipping times?

	The relationship with distance is statistically significant, and the overall regression explains a lot
	The relationship with distance is statistically significant, but the overall regression explains very little
	The relationship with distance is not statistically significant, but the overall regression explains a lot
	The relationship with distance is not statistically significant, and the overall regression explains very little