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:



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
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