From the histogram above, which of the following would we expect to be true?

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from_the_histogram_above_q.doc

Exam 4

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image1.wmf

A827617549674C

 

image2.png

1.

From the histogram above, which of the following would we expect to be true?

image3.wmf A.

The median would be less than the mean

image4.wmf B.

The median would be greater than the mean

image5.wmf C.

The median would be equal with the mean

Answer: A

2.

Which one of the following variables is discrete?

image6.wmf A.

The number of automobiles produced by Ford

image7.wmf B.

The daily high temperature in Chicago

image8.wmf C.

The age of the students in our class

image9.wmf D.

The weight of the students in our class

image10.wmf E.

The manufacturer of an automobile

Answer: A

3.

A magazine publisher asks readers to log onto their website and vote on a topic. The website allows visitors to select one of two choices and submit a vote. The results of the poll are reported in the next issue of the magazine. The population to which the results of these polls can be extended is:

image11.wmf A.

Only readers who voted in that specific poll.

image12.wmf B.

All readers of the magazine.

image13.wmf C.

All visitors to the website.

image14.wmf D.

All readers who have voted in any of the polls.

Answer: A

4.

A six-sided die is made that has four Green sides and two Red sides. Any side is equally likely to land face up when the die is tossed. The die is tossed three times. Which of these sequences (in the order shown) has the highest probability

image15.wmf A.

Green, Green, Green

image16.wmf B.

Red, Red, Red

image17.wmf C.

Green, Green, Red

image18.wmf D.

Green, Red, Green

Answer: A

5.

The sample mean is an estimate of:

image19.wmf A.

The average value in the population

image20.wmf B.

The average value in the sample

Answer: A

 

A study found that students who procrastinate are more likely to get colds. A sample of 300 college students was asked how often they procrastinate and if they’ve had a cold in the last two months. Below is a two-way table of counts (rows = had a cold).

image21.png

6.

State the appropriate null hypotheses for this study.

image22.wmf A.

There is no relationship in the population between Having a Cold and Procrastination

image23.wmf B.

There is no relationship in the sample between Having a Cold and Procrastination

image24.wmf C.

There is relationship in the population between Having a Cold and Procrastination

image25.wmf D.

There is relationship in the sample between Having a Cold and Procrastination

Answer: A

image26.png

7.

If the p-value is 0.008 for the Chi-Square Analysis of this data, which of the following is the BEST conclusion?

image27.wmf A.

statistically significant in the population.

image28.wmf B.

statistically significant in the sample.

image29.wmf C.

NOT statistically significant in the sample.

image30.wmf D.

NOT statistically significant in the population.

Answer: A

image31.png

8.

What is the relative risk of often procrastinating between those having a cold compared to those not having a cold?

image32.wmf A.

(50/200)/(40/100)

image33.wmf B.

(40/100)/(50/200)

image34.wmf C.

(50/150)/(40/60)

image35.wmf D.

(50/90)/(40/90)

Answer: A

 

image36.png

9.

Using the above regression output, what is the correct regression equation?

image37.wmf A.

y-hat = - 21.04 + 0.5666X1

image38.wmf B.

y-hat = 0.5666 – 21.04X1

image39.wmf C.

y-hat = 16.00 + 0.1475X1

image40.wmf D.

y-hat = 16.00 + 0.5666X1

Answer: A

image41.png

10.

Using the above regression output, what is the correct conclusion for test of the slope?

image42.wmf A.

Since p-value of 0.001 is less than 0.05 we reject Ho and conclude that X1 is a significant linear predictor of Y.

image43.wmf B.

Since p-value of 0.001 is less than 0.05 we do not reject Ho and conclude that X1 is NOT a significant linear predictor of Y.

image44.wmf C.

Since p-value of 0.205 is greater than 0.05 we reject Ho and conclude that X1 is a significant linear predictor of Y.

image45.wmf D.

Since p-value of 0.205 is greater than 0.05 we do not reject Ho and conclude that X1 is NOT a significant linear predictor of Y.

Answer: A

image46.png

11.

Using the above regression output, then the correlation between X1 and Y would be calculated by taking:

image47.wmf A.

The positive square root of 0.45

image48.wmf B.

0.45 times 0.45

image49.wmf C.

The negative square root of 0.45

image50.wmf D.

Either the positive OR negative square root of 0.45

Answer: A

image51.png

12.

Using the above regression output, how much of the variation in Y is explained by X1?

image52.wmf A.

45%

image53.wmf B.

42%

image54.wmf C.

The positive square root of 0.45

image55.wmf D.

3.98537%

Answer: A

 

The following Minitab output is based on the responses of 35 students randomly selected from ALL sections of Stat 200 to the question "Do you smoke cigarettes?”

image56.png

13.

Based on the output above, what are the null and alternative hypotheses?

image57.wmf A.

  Ho: p = 0.2   Ha: p ≠ 0.2

image58.wmf B.

  Ho: p−hat = 0.2   Ha: p−hat ≠ 0.2

image59.wmf C.

  Ho: p = 0.2   Ha: p < 0.2

image60.wmf D.

  Ho: p−hat = 0.2   Ha: p−hat < 0.2

image61.wmf E.

  Ho: μ = 0.2   Ha: μ < 0.2

image62.wmf F.

  Ho: μ = 0.2   Ha: μ ≠ 0.2

Answer: A

image63.png

14.

Based on the output above, what statistical conclusion should you reach? The percentage of STAT 200 students who smoke:

image64.wmf A.

does not differ from 20%

image65.wmf B.

is less than 20%

image66.wmf C.

is different than 20%

image67.wmf D.

is greater than 14%

Answer: A

 

The following is the Minitab output for randomly selected responses to "What is your GPA" from a survey given to all sections of STAT 200.

image68.png

15.

Based on the output above, what are the null and alternative hypotheses?

image69.wmf A.

  Ho: μ = 3.5  Ha: μ < 3.5

image70.wmf B.

  Ho: μ = 3.15  Ha: μ < 3.15

image71.wmf C.

  Ho: x-bar = 3.5  Ha: x-bar < 3.5

image72.wmf D.

  Ho: x-bar = 3.15  Ha: x-bar < 3.15

image73.wmf E.

  Ho: μ = 3.5  Ha: μ ≠ 3.5

image74.wmf F.

  Ho: μ < 3.5  Ha: μ = 3.5

Answer: A

image75.png

16.

Based on the above output what is the standard error of the mean?

image76.wmf A.

0.10

image77.wmf B.

0.50

image78.wmf C.

12.5

image79.wmf D.

About 0.6

Answer: A

17.

The primary purpose of a confidence interval is to:

image80.wmf A.

Estimate the population parameter

image81.wmf B.

Make decisions on differences

image82.wmf C.

Estimate the accuracy of the sample statistic

Answer: A

18.

From a class survey, 90% confidence intervals were created for both the females and males who responded Yes to having smoked marijuana. The 90% confidence intervals were 0.417 to 0.565 for the females and 0.437 to 0.609 for the males. What conclusions can we draw in regards to the population proportions of females and males who said that they have tried marijuana?

image83.wmf A.

We cannot conclude there is a difference between the population proportions.

image84.wmf B.

We cannot conclude there is a difference between the sample proportions.

image85.wmf C.

Males are more likely than females to have tried marijuana.

image86.wmf D.

Males are less likely than females to have tried marijuana.

Answer: A

19.

If you were conducting a two sample T−test to compare two means, which of the following would allow you to properly use the pooled method in order to perform the test?

image87.wmf A.

If the larger sample standard deviation was 5 and the smaller sample standard deviation was 4

image88.wmf B.

If the larger sample mean was 5 and the smaller sample mean was 4

image89.wmf C.

If the larger standard error was 5 and the smaller standard error was 4

Answer: A

 

image90.png

20.

From the output above comparing GPA between Females and Males, was this test done using Independent or Paired methods?

image91.wmf A.

Independent

image92.wmf B.

Paired

Answer: A

image93.png

21.

From the output above comparing GPA between Females and Males, what decision can be made?

image94.wmf A.

With a p-value of 0.029 we can reject the null hypothesis and conclude that there is a difference in mean GPA between Females and Males.

image95.wmf B.

With a p-value of 0.029 we cannot reject the null hypothesis and conclude that there is a difference in mean GPA between Females and Males.

image96.wmf C.

With a p-value of 0.029 we can reject the alternative hypothesis and conclude that there is a difference in mean GPA between Females and Males.

image97.wmf D.

With a p-value of 0.029 we cannot reject the alternative hypothesis and conclude that there is a difference in mean GPA between Females and Males.

Answer: A

 

image98.png

22.

Based on the above ANOVA output, how many means are being tested?

image99.wmf A.

4

image100.wmf B.

3

image101.wmf C.

301

image102.wmf D.

304

Answer: A

image103.png

23.

Based on the above ANOVA output, what conclusion should be made regarding the means?

image104.wmf A.

With p-value of 0.000 conclude that not all of the means are equal.

image105.wmf B.

With p-value of 0.000 conclude that all of the means are different

image106.wmf C.

With p-value of 0.000 conclude that all of the means are equal

Answer: A

24.

Which of the following is a matched pairs design?

image107.wmf A.

Measure levels of depression for a random sample of internet users and for a random sample of non-users.

image108.wmf B.

Measure level of depression for a random sample on non-internet users: provide them with internet use for a year and then measure their level of depression.

Answer: B

25.

Which of the the following techniques is best used for QUANTITATIVE data?

image109.wmf A.

Histogram

image110.wmf B.

Pie Chart

image111.wmf C.

Two-way Table

image112.wmf D.

Bar Chart

Answer: A

26.

In general, which is more likely to contain the unknown population mean?

image113.wmf A.

A 90% confidence interval

image114.wmf B.

A 95% confidence interval

image115.wmf C.

A 99% confidence interval

image116.wmf D.

They are all equally likely

Answer: C

 

Select the most appropriate display for each of the following:

27.

Rent charged and apartment size of a sample of one-bedroom apartments in State College:

image117.wmf A.

Bar Graph

image118.wmf B.

Histogram

image119.wmf C.

Two-way table

image120.wmf D.

Scatterplot

image121.wmf E.

Side-by-Side Boxplots

Answer: D

 

Select the most appropriate statistical test for each of the following:

28.

We examine a random sample of State College apartments to see if overall there is a relationship between rent charged and size:

image122.wmf A.

Z-test about a proportion

image123.wmf B.

t-test about a mean with a one-sided alternative

image124.wmf C.

t-test about a mean with a two-sided alternative

image125.wmf D.

Two-sample t-test with a one-sided alternative

image126.wmf E.

Two-sample t-test with a two-sided alternative

image127.wmf F.

Chi-square test

image128.wmf G.

One-way Analysis of Variance (ANOVA)

image129.wmf H.

Regression

Answer: H

29.

We take random samples of African-American, White, Asian, and Hispanic workers to determine if mean earnings differ among these groups:

image130.wmf A.

Z-test about a proportion

image131.wmf B.

t-test about a mean with a one-sided alternative

image132.wmf C.

t-test about a mean with a two-sided alternative

image133.wmf D.

Two-sample t-test with a one-sided alternative

image134.wmf E.

Two-sample t-test with a two-sided alternative

image135.wmf F.

Chi-square test

image136.wmf G.

One-way Analysis of Variance (ANOVA)

image137.wmf H.

Regression

Answer: G

 

Identify whether the comparison is based on two independent samples or paired data.

30.

Students are asked whether they have ever missed class as a result of drinking alcohol. Results for fraternity and sorority members are compared to results for non-Greeks.

image138.wmf A.

Independent

image139.wmf B.

Paired

Answer: A

31.

Fifty students have their blood pressures before and after an exam. We wish to know if there is an increase, on average.

image140.wmf A.

Independent

image141.wmf B.

Paired

Answer: B

 

Select the proper NULL hypothesis.

32.

Mean scores on a memory test are compared for women aged 50 to 59 years old versus women aged 60 to 69 years old.

image142.wmf A.

H0:p1 - p2 = 0

image143.wmf B.

H0:p-hat1 - p-hat2 = 0

image144.wmf C.

H0:μ1 - μ2 = 0

image145.wmf D.

H0:x-bar1 - x-bar2 = 0

Answer: C

33.

A class survey is used to compare the GPAs of male and female students.

image146.wmf A.

H0:p1 - p2 = 0

image147.wmf B.

H0:p-hat1 - p-hat2 = 0

image148.wmf C.

H0:μ1 - μ2 = 0

image149.wmf D.

H0:x-bar1 - x-bar2 = 0

Answer: C

image150.png

34.

From the above regression output, what is the p-value and decision regarding the test of the slope for X1?

image151.wmf A.

The p-value is 0.003 so we reject Ho and conclude that X1 is a significantly linear predictor of Y when the variable X2 is in the model.

image152.wmf B.

The p-value is 0.003 so we do not reject Ho and conclude that X1 is not a significantly linear predictor of Y when the variable X2 is in the model.

image153.wmf C.

The p-value is 0.003 so we reject Ho and conclude that X1 is not a significantly linear predictor of Y when the variable X2 is in the model.

image154.wmf D.

The p-value is 0.003 so we do not reject Ho and conclude that X1 is a significantly linear predictor of Y when the variable X2 is in the model.

image155.wmf E.

The p-value is 0.281 so we do not reject Ho and conclude that X1 is not a significantly linear predictor of Y when the variable X2 is in the model.

image156.wmf F.

The p-value is 0.001 so we reject Ho and conclude that X1 is a significantly linear predictor of Y when the variable X2 is in the model.

image157.wmf G.

The p-value is 0.002 so we reject Ho and conclude that X1 is a significantly linear predictor of Y when the variable X2 is in the model.

Answer: A

image158.png

35.

From the above regression output, what is the p-value and decision regarding the test of the slope for X2?

image159.wmf A.

The p-value is 0.281 so we reject Ho and conclude that X2 is a significantly linear predictor of Y when the variable X1 is in the model.

image160.wmf B.

The p-value is 0.281 so we do not reject Ho and conclude that X2 is not a significantly linear predictor of Y when the variable X1 is in the model.

image161.wmf C.

The p-value is 0.281 so we reject Ho and conclude that X2 is not a significantly linear predictor of Y when the variable X1 is in the model.

image162.wmf D.

The p-value is 0.281 so we do not reject Ho and conclude that X2 is a significantly linear predictor of Y when the variable X1 is in the model.

image163.wmf E.

The p-value is 0.003 so we do not reject Ho and conclude that X2 is not a significantly linear predictor of Y when the variable X1 is in the model.

image164.wmf F.

The p-value is 0.298 so we do not reject Ho and conclude that X2 is not a significantly linear predictor of Y when the variable X1 is in the model.

image165.wmf G.

The p-value is 0.342 so we do not reject Ho and conclude that X2 is not a significantly linear predictor of Y when the variable X1 is in the model.

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