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A quantitative variable is the only type of variable that can

A quantitative variable is the only type of variable that can

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A quantitative variable is the only type of variable that can


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Tutorial

QNT 275 Week 5 Final Exam Link

https://uopcourses.com/category/qnt-275-exam/

A quantitative variable is the only type of variable that can

have no intermediate values

assume numeric values for which arithmetic operations make sense

be graphed

be used to prepare tables

 

 

 

A qualitative variable is the only type of variable that

can assume numerical values

cannot be graphed

can assume an uncountable set of values

cannot be measured numerically

 

the cumulative frequency distribution of the commuting time (in minutes) from home to work  

 

The following table gives the cumulative frequency distribution of the commuting time (in minutes) from home to work for a sample of 400 persons selected from a city.

Time (minutes)

f

0 to less than 10

66

0 to less than 20

148

0 to less than 30

220

0 to less than 40

294

0 to less than 50

356

0 to less than 60

400

The sample size is:

The percentage of persons who commute for less than 30 minutes, rounded to two decimal places, is:

%

The cumulative relative frequency of the fourth class, rounded to four decimal places, is:

The percentage of persons who commute for 40 or more minutes, rounded to two decimal places, is:

%

The percentage of persons who commute for less than 50 minutes, rounded to two decimal places, is:

%

The number of persons who commute for 20 or more minutes is:

 

 

The temperatures (in degrees Fahrenheit) observed during seven days of summer in Los Angeles are

78,99,68,91,97,75,85

The range of these temperatures is:

The variance of these temperatures, rounded to three decimals, is:

The standard deviation, rounded to three decimals, of these temperatures is:

 

 

 

 

The following table gives the two-way classification of 500 students based on sex and whether or not they suffer from math anxiety

 

Suffer From Math Anxiety

Sex

Yes

No

Male

151

89

Female

184

76

 

If you randomly select one student from these 500 students, the probability that this selected student is a female is: (round your answer to three decimal places, so 0.0857 would be 0.086)

If you randomly select one student from these 500 students, the probability that this selected student suffers from math anxiety is: (round your answer to three decimal places, so 0.0857 would be 0.086)

If you randomly select one student from these 500 students, the probability that this selected student suffers from math anxiety, given that he is a male is: (round your answer to three decimal places, so 0.0857 would be 0.086)

If you randomly select one student from these 500 students, the probability that this selected student is a female, given that she does not suffer from math anxiety is: (round your answer to three decimal places, so 0.0857 would be 0.086)

Which of the following pairs of events are mutually exclusive?

Male and no

No and yes

Male and yes

Female and yes

Female and male

Female and no

Are the events "Has math anxiety" and "Person is female" independent or dependent? Detail the calculations you performed to determine this.

dependent

 

 

For the probability distribution of a discrete random variable x, the sum of the probabilities of all values of x must be

equal to 1

equal to zero

in the range zero to 1

equal to 0.5

 

 

 

The following table lists the probability distribution of a discrete random variable x

x

2

3

4

5

6

7

8

P(x)

0.15

0.3

0.24

0.13

0.1

0.06

0.02

 

The mean of the random variable x is:

The standard deviation of the random variable x, rounded to three decimal places, is:

 

 

The daily sales at a convenience store produce a distribution that is approximately normal with a mean of 1270 and a standard deviation of 136

The probability that the sales on a given day at this store are more than

1,405, rounded to four decimal places, is:

The probability that the sales on a given day at this store are less than

1,305, rounded to four decimal places, is:

The probability that the sales on a given day at this store are between

1,200 and 1,300, rounded to four decimal places, is:

 

 

The width of a confidence interval depends on the size of the

population mean

margin of error

sample mean

none of these

 

 

A sample of size 67 from a population having standard deviation= 41 produced a mean of 248.00. The 95% confidence interval for the population mean (rounded to two decimal places) is

The lower limit is

The upper limit is

 

 

The null hypothesis is a claim about a

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be true until it is declared false

 

 

 

 

 

The alternative hypothesis is a claim about a

statistic, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be false until it is declared true

population parameter, where the claim is assumed to be true until it is declared false

 

 

 

In a one-tailed hypothesis test, a critical point is a point that divides the area under the sampling distribution of a

statistic into one rejection region and one nonrejection region

population parameter into one rejection region and one nonrejection region

statistic into one rejection region and two nonrejection regions

population parameter into two rejection regions and one nonrejection region

 

 

 

In a two-tailed hypothesis test, the two critical points are the points that divide the area under the sampling distribution of a

statistic into two rejection regions and one nonrejection region

statistic into one rejection region and two nonrejection regions

population parameter into two rejection regions and one nonrejection region

population parameter into one rejection region and one nonrejection region

 

 

 

In a hypothesis test, a Type I error occurs when

a true null hypothesis is rejected

a false null hypothesis is rejected

a false null hypothesis is not rejected

a true null hypothesis is not rejected

 

          

In a hypothesis test, a Type II error occurs when

Entry field with correct answer

        

a false null hypothesis is not rejected

        

a true null hypothesis is rejected

        

a true null hypothesis is not rejected

        

a false null hypothesis is rejected

          

In a hypothesis test, the probability of committing a Type I error is called the

Entry field with correct answer

        

confidence interval

        

significance level

        

beta error

        

confidence level