The Network Compromise Percentage (NCP) metric is used to indicate the

  

QUESTION 1

The Network Compromise Percentage (NCP) metric is used to indicate the percentage of network assets an attacker can compromise. A sample of 7 locations were assessed, with average NCP=51.23% with sample standard deviation of 15%. Find the 90% confidence interval for NCP, assuming a normal distribution.

  

(36.6, 65.8)

 

(30.2, 72.2)

 

(41.9, 60.6)

 

(40.2, 62.2)

QUESTION 2

A one-sample t-test can test if the population mean is equal to 100.

True

False

QUESTION 3

What is the correct interpretation of the following 95% confidence interval for mean # of cruffins (hybrid croissant + muffin) sold at a bakery? 95% CI: (130,180)

  

The average number of cruffins is   between 130 and 180, 95% of the time.

 

We are 95% confident that the average   number of cruffins sold at the bakery is less than 130 and greater than 180.

 

We are 100% confused about what a   cruffin is.

 

We are 95% confident that the average   number of cruffins sold at the bakery is between 130 and 180.

QUESTION 4

If the population standard deviation is known and sample is large enough (at least 30), we can use the standard normal Z to calculate a confidence interval.

True

False

QUESTION 5

A social media marketing specialist is assessing audience activity of a company's website and wanted to check if it's different than its competitor's activity of 10 retweets per hour. From a sample, the 99% confidence interval was calculated as (11.6, 14.9). Does the company have audience activity significantly different from 10 retweets per hour?

  

Conclude mean retweets per hour is   significantly different than 10.

 

Cannot perform this test. We require   a p-value.

 

Conclude mean retweets per hour is   NOT significantly different than 10.

QUESTION 6

To calculate the confidence interval for average # of coffees that college students drink before a final exam, you find the sample average, sample size, and sample standard deviation. Which of these will change if I increase the sample size?

  

t

 

Z

 

mu

 

sigma

QUESTION 7

An analyst wants to know calculate the visibility of PricewaterhouseCoopers among the general public right after the 2017 Oscars blunder involving announcing the wrong winner. A survey asking how familiar people were with PwC using an index from 1 to 10 (10 being extremely familiar) was given to n=20 people at random. From this sample, the average was  with sample standard deviation s=2.3.  Calculate the 99% confidence interval for the average familiarity index. It is not known whether or not this data is normally distributed.

  

Cannot solve this problem.

 

(3.45, 4.53)

 

(6.36, 8.64)

 

(5.66, 8.34)

QUESTION 8

An alpha of α=0.10 means that a p-value greater than 0.10 shows a test is statistically significant.

True

False

QUESTION 9

If you are looking up a t value on a t-table for a confidence interval, the t for sample size n=6 for 90% confidence interval is

  

2.447

 

1.943

 

2.015

 

2.571

QUESTION 10

A small p-value less than alpha indicates that our data is unlikely to be from a hypothetical distribution that we are testing. That's why smaller p-values are stronger evidence than larger p-values.

True

False

QUESTION 11

Smaller p-values are stronger evidence and support that a statistical test is significant.

True

False

QUESTION 12

An investor would like to know if their stock portfolio average CAGR (compound annual growth rate) is different from 10%. From a sample of 30 periods, the average CAGR was 12.2% with standard deviation of s=9%. Calculate the 95% confidence interval. Perform the appropriate one-sample test with results.

  

Based on the one-sample t test,   conclude that the average CAGR is significantly different from 10%.

 

Based on the one-sample t test,   conclude that the average CAGR is NOT significantly different from 10%.

 

Based on the one-sample Z test,   conclude that the average CAGR is NOT significantly different from 10%.

 

Based on the one-sample Z test,   conclude that the average CAGR is significantly different from 10%.

QUESTION 13

An intern at Nestle has been tasked to identify if average chocolate sales are impacted by how many chocolate brands are stocked by a supermarket.

Data was collected and a linear regression was run with α=0.05.

What should the intern conclude?

  

A significant linear relationship   exists between # of brands stocked and average chocolate sales. For   every 1 additional brand stocked, total sales increases by $0.40.

 

# of brands stocked by a supermarket   does not significantly predict chocolate sales, on average.

 

A significant linear relationship   exists between # of brands stocked and average chocolate   sales. For every 1 additional brand stocked, total sales   increases by $611.

 

# of brands stocked by a   supermarket DOES significantly predict chocolate sales, on   average. However, there is no practical significance as it only raises   it by $0.40.

QUESTION 14

A pearson correlation coefficient r can be greater than 1.

True

False

QUESTION 15

A global economist is interested in identifying if factors such as GDP, GNP, labor force, and other variables can predict the international trade volume of import shipping containers. Which would be the correct statistical test to run?

  

Pear   Cheese Test

 

Cronbach's   Alpha

 

Chi-square   test

 

Linear   regression

QUESTION 16

For the linear regression equation y=3x+1 and y=number of pizza slices and x=number of final exams a student has, what is the correct interpretation of 3?

  

For   every 1 final exam that a student has, they eat 3 more slices of pizza, on   average.

 

For   every 1 pizza slice a student eats, they have to take 3 more final exams, on   average.

 

For   every 3 pizza slices a student eats, they have to take an additional final   exam, on average.

 

For   every 3 final exams a student has, they eat 4 slices of pizza more, on   average.

QUESTION 17

Kaiser Permanente wants to assess if in-hospital mortality (died vs. didn't die) can predict total hospital costs per patient ($USD). A linear regression was run, with the output below. Use α=0.05 and choose the answer that is TRUE.

  

In-hospital mortality does not   significantly predict total hospital costs, on average.

 

For every 1 in-hospital death,   total hospital costs increase by $622 on average.

 

If a patient dies, total   hospital costs increase by $427 compared to if they did not die.

 

If a patient dies, total   hospital costs increase by $622 compared to if they did not die.

QUESTION 18

A helicopter flight academy is interested in looking to see if there is a relationship between takeoff gross weight of their helicopters and in ground effect (IGE) hover ceiling. Both of these measures are quantitative. Which statistical test would look at this relationship?

  

Poisson   Regression

 

One-sample   t-test

 

Pearson   Correlation

 

Chi-square

QUESTION 19

A marine transportation company would like to know which economic efficiencies (measured as quantitative numbers) are related (positive or negative) to number of organizations within an industry (also measured as quantitative numbers). Which of the following would be an appropriate test to check this hypothesis?

  

Mauchly's   test of sphericity

 

One-sample   t-test

 

Chi-square   test

 

Pearson   Correlation

QUESTION 20

A small business believes that their restaurant reviews (good or bad) may be affected by certain employees (Employee 1, Employee 2, or Employee 3). To identify if there is an association between two these variables, which test should be conducted?

  

Chi-square   test

 

Generalized   Estimating Equations

 

One-sample   t-test

 

Independent-samples   t-test

QUESTION 21

An airline would like to conduct a marketing study to identify if passenger satisfaction (yes or no) is associated with type of free snack provided (either peanuts, pretzels, or chocolate). Which test would look at this association?

  

One-sample   t-test

 

Chi-square   test

 

Sidak   post-hoc test

 

One-sample   Z-test

QUESTION 22

A crosstabulation was run between two variables, Studied? (Yes or No) vs. Difficulty of Exam (Low, Medium, or High). Interpret the 40% below.

  

Sum of col

Column Labels

 

Row Labels

Low

Medium

High

Grand Total

 

Yes

40.00%

0.00%

60.00%

100.00%

 

No

6.82%

18.18%

75.00%

100.00%

 

Grand Total

20.27%

10.81%

68.92%

100.00%

 

40% of people who did not   study, thought the exam was very difficult.

 

40% of my grade comes from exams in this   class. Oh wait, it really does. But this is not the correct answer. Please   don't select it...

 

40% of people who said the exam   was low difficulty, studied for the exam.

 

40% of people who studied for the   exam said it was low difficulty.

QUESTION 23

A biotech startup specializing in CRISPR gene-editing technology wants to know if the community would be interested in gene editing services in the future. They ask a sample of people if they agree gene editing is good, and split based on age group.

Which of the following is true?

  

Gene Editing is good

Column Labels

 

Row Labels

Age less than 35

35 or more

Grand Total

 

Agree

50.00%

16.67%

33.33%

 

Neutral

33.33%

33.33%

33.33%

 

Disagree

16.67%

50.00%

33.33%

 

Grand Total

100.00%

100.00%

100.00%

 

These percents are row percents.

 

50% of people age less than 35, agree   that gene editing is good.

 

The correct statistical test to look   at this association would be linear regression.

 

16.67% of people who agreed gene   editing was good, were age 35 or more.

QUESTION 24

A chi-square test was conducted between two variables. Both variables must have been quantitative.

True

False

QUESTION 25

A manager of UCSD Dining Services wants to know if students/faculty who wear UCSD attire on Fridays spend more money than those who do not wear UCSD attires. An independent-samples t-test was run using data collected. If the manager used α=0.05 for their level of significance, what should they conclude?

  

t-Test:   Two-Sample Assuming Unequal Variances

 

 

Yes,UCSD   Attire

No   UCSD Attire

 

Mean

                       $10.50

                       $ 6.59

 

Variance

2.81

4.37

 

Observations

34

34

 

Hypothesized   Mean Difference

0

 

df

63

 

t   Stat

10.67151969

 

P(T<=t)   one-tail

4.66393E-16

 

t   Critical one-tail

1.669402222

 

P(T<=t)   two-tail

9.32786E-16

 

t   Critical two-tail

1.998340543

 

Since   p is less than α, conclude that there is a   significant difference in average amount spent by people who wore or didn't   wear CSUSB attire.  People who wore CSUSB attire spend MORE than those   who did not, on average.

 

Since   p is greater than α, conclude that there is no   significant difference in average amount spent by people who wore or didn't   wear CSUSB attire.

 

Since p-value is greater than 1,   there is a computer error and we automatically get the points for this   question!

QUESTION 26

Amazon is interested in identifying if their average return dissatisfaction rate (RDR) is significantly different than 30%. Based on the results of the one-sample t-test, which of the following is FALSE? Use α=0.01

  

p-value is less than alpha.

 

Hey, this doesn't look like the   answer on Chegg!! I paid good $$$ for that 

 

Average RDR for Amazon is less   than 30%.

 

The average return dissatisfaction   rate is NOT significantly different from 30%.

QUESTION 27

A bar owner wants to know if creating a signature drink for the establishment increases total revenue. They compared average revenue for each of its bartenders before the signature drink to 30 days after for each of the same bartenders. The correct statistical test to use is a:

  

Pearson   Correlation

 

Chi-square   test

 

paired-samples   t-test

 

independent-samples   t-test

QUESTION 28

A Macys survey was sent out to designated Macys Star Advisors asking if they would be more likely to purchase accessories such as handbags, wallets, purses, etc. that had smart technology in it. On a scale of 1 to 10 (10=most likely), Macy's would consider offering these accessories if the average interest was at least 7. Based on the output below and α=0.10, what should Macy's do?

  

t-Test: Paired Two Sample for Means

 

 

Purchase

Blank

 

Mean

8.5

0

 

Variance

1.595238

0

 

Observations

22

22

 

Pearson Correlation

#DIV/0!

 

Hypothesized Mean Difference

7

 

df

21

    

t Stat

5.570444

 

P(T<=t) one-tail

7.9E-06

 

t Critical one-tail

1.720743

 

P(T<=t) two-tail

1.58E-05

 

t Critical two-tail

2.079614

 

  

The average was NOT     significantly different from 7. Although the sample average was 8.5, Macy's     should NOT continue with this line of apparel since this average could have     happened by chance.

  

The average was significantly       different from 7. Since the sample average was 8.5, Macy's should       continue with this line of apparel.

 
 

 

Not enough information to     answer this question.

QUESTION 29

An independent-samples t-test showed that there was a significant difference in mean # of donut holes eaten between group A and B (p-value was less than 0.05). The average # of donut holes eaten was 20 in group A and 30 in group B. The average difference (30-20=10) can be thought of as the practical significance.

True

False

QUESTION 30

A manager is interested in improving the productivity of its employees. They looked at average productivity of a group of employees before and after adding a recreation center to improve intra-employee relations. The results of the test are below using α=0.01. Which of the following is TRUE?

  

The p-value   is greater than alpha.

 

There was a   significant difference in average productivity before and after. The average   productivity went UP by 1.7 points.

 

There was   NO significant difference in average productivity before and after. The   average productivity went up by 1.7 points.

 

There was a   significant difference in average productivity before and after. The   average productivity went DOWN by 1.7 points.

QUESTION 31

1. A marketing department is interested in testing if adding testimonials can increase sales on their website. They compare average total sales before and after adding testimonials. Which statistical test would be most appropriate?

  

Chi-square   test

 

Paired-samples   t-test

 

One-sample   t-test

 

Cox   Proportional Hazards Regression

 

 

QUESTION 32

1. A manager wanted to test if a new employee group activity would improve self-rated worker performance. A paired t-test was used with α=0.10.

What should the manager conclude?

     

The employee group activity was   successful.

 

The employee group activity   showed a significant difference in average self-rated worker performance.

 

There was a significant drop in   performance by 2.5. 

 

No significant difference in   average self-rated worker performance. The drop seen could have occurred   due to chance.