How will the outlier in this data set affect the correlation coefficient?

Go to Link(https://rconnect.byu.edu/Stat121App/On the left panel, select "Regression". Select the "Graduate Admission for Indian Students" dataset, then select "GRE.score" as your explanatory variable and "Chance.of.Admit" as your response variable. We want to see if there is a correlation between GRE scores and their chance of admission into a university's master's program.

1. Generate a scatterplot of the variables. Describe the relationship between GRE scores and the chance of admission.

Group of answer choices

A linear, strong, negative relationship

A linear, strong, positive relationship

A linear, weak, negative relationship

A linear, weak, positive relationship

2. Calculate the correlation coefficient.

Group of answer choices

-0.9234

-0.8027

0.8026

0.9234

3. True or False: If you switch your variables around, or make "Chance.of.Admit" your explanatory variable and "GRE.score" as your response variable, then the correlation coefficient changes.

Group of answer choices

True

False

4. The accompanying data resulted from an experiment in which weld diameter and shear strength (in pounds) were determined for five different spot welds on steel.

Below are the data collected and the regression equation.

Diameter	Strength
200.1	813.7
210.1	785.3
220.1	960.4
230.1	1118.0
240.0	1076.2

Strength = -941.6992 + 8.5988*Diameter

The predicted y-hat value for a diameter of 201 is 786.7. Interpret this predicted value.

A.If the diameter were to increase by one unit, we expect the mean strength to increase by 786.7.

B.If the diameter were 0, ten we would expect the mean strength to be 786.7.

C.If the diameter were to increase by 20, then we would expect the mean strength to increase by 786.7.

D.If the diameter is 201 then we would expect the mean strength to be 786.7.

5. Referring to question 1, what is the predicted strength of a weld with a diameter of 51?

A.-812.7172

B.-941.69916

C.-81.821301

D.We should not use the least squares regression line to calculate this value

6. Referring to question 1, if we observed a weld that had a diameter of 235 that had a strength 1000, what would be its residual?

A.79

B.-79

C.59

D.-59

7. It has been found that lower test scores are highly correlated with higher amounts of tutoring. Because of this high correlation can we say that lower tests scores are caused by tutoring?

A.Yes, because tutors are not very good and therefore, they just impede the students' ability to do well.

B.No, because those who need tutors are usually those who have trouble with that material.

8. True or False: Extrapolation is the use of the regression line to estimate a mean of y-values for an x-value that is far outside the x-range of data.

A.True

B.False

9. True or False: Simpson's paradox occurs whenever including a lurking variable causes you to rethink the direction of an association.

10. A research clinic is interested in understanding the impact of a new anti-anxiety medication. They conduct a study to determine if there is a difference in anxiety scores (on a scale of 0 to 100) among participants who take the new medication, a traditional medication, and placebo. A random sample of study participants were assigned to one of three groups: new anti-anxiety medication (38 participants), traditional anti-anxiety medication (36 participants) and placebo (39 participants). Is there evidence to conclude that there is a difference among the three groups in terms of average anxiety scores? What statistical procedure should be used to answer this research question?

A.A one-sample t-test for means

B.A one-sample t-confidence interval for means

C.A matched-pairs t-test for means

D.A matched-pairs t-confidence interval for means

E.A two-sample t-test for means

F.A two-sample t-confidence interval for means

G.A one-sample z-test for proportions

H.Analysis of Variance (ANOVA)

I.A two-sample z-confidence interval for proportions

J.A two-sample z-test for proportions

11. A research clinic is interested in understanding the impact of a new anti-anxiety medication. A random sample of patients who previously experienced high anxiety levels were assigned to the new anti-anxiety medication (38 participants) and placebo (39 participants). Their anxiety levels (low or high) were then measured after taking the medication or placebo for a prescribed amount of time. Is there sufficient evidence to conclude that the proportion of those who took the new anti-anxiety medication had low anxiety compared to the proportion who took the placebo who had low anxiety? What statistical procedure should be used to answer this research question?

A.A one-sample t-test for means

B.A one-sample t-confidence interval for means

C.A matched-pairs t-test for means

D.A matched-pairs t-confidence interval for means

E.A two-sample t-test for means

F.A two-sample t-confidence interval for means

G.A one-sample z-test for proportions

H.A one-sample z-confidence interval for proportions

I.A two-sample z-test for proportions

J.A two-sample z-confidence interval for proportions

12. A study was conducted to determine if there is an association between the type of anti-anxiety medication (new type, traditional type, and placebo) and anxiety levels (low and high). 393 study participants were randomly assigned to the three different medications. 138 participants were assigned to the new medication group, 126 to the traditional medication group, and 129 to the placebo group. Is there sufficient evidence to conclude that there is an association between the type medication taken (three types) and the levels of anxiety (two levels)? What statistical procedure should be used to answer this research question?

A.A one-sample t-test for means

B.A one-sample t-confidence interval for means

C.A matched-pairs t-test for means

D.A matched-pairs t-confidence interval for means

E.Chi Square test for independence

F.A two-sample t-test for means

G.A two-sample t-confidence interval for means

H.A one-sample z-test for proportions

I.A one-sample z-confidence interval for proportions

J.A two-sample z-test for proportions