QNT 275 FINAL EXAM26/30 for a 87%
A researcher wants to test if the mean annual salary of all lawyers in a city is different than $110,000. The null hypothesis for this example will be that the population mean is:
•
equal to $110,000
A sample of 16 from a population produced a mean of 8...
qnt 275 final exam 2630 for a 87 a researcher wants to test if the mean annual salary of all lawyers in a city is different than 110
000 the null hypothesis for this example will be that the popu
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QNT 275 FINAL EXAM
26/30 for a 87%
A researcher wants to test if the mean annual salary of all lawyers in a city is different than
$110,000. The null hypothesis for this example will be that the population mean is:
equal to $110,000
A sample of 16 from a population produced a mean of 86.9 and a standard deviation of 14.3. A
sample of 18 from another population produced a mean of 75.4 and a standard deviation of 15.9.
Assume that the two populations are normally distributed and the standard deviations of the two
populations are equal. The null hypothesis is that the two population means are equal, while the
alternative hypothesis is that the mean of the first population is greater than the man of the
second population. The significance level is 1%.
What is the critical value of t for the hypothesis test? 2.449
In a hypothesis test, a Type I error occurs when: a true null hypothesis is rejected
A continuous random variable x has a right-skewed distribution with a mean of 80 and a standard
deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from
this population is: skewed to the right
A quantitative variable is the only type of variable that can: assume numeric values for which arithmetic
operations make sense
If you divide the number of elements in a sample with a specific characteristic by the total number of
elements in the sample, the dividend is the: sample mean
An error that occurs because of chance is called: sampling error
The regression model y = A + Bx + e is: an exact relationship
In a one-way ANOVA, we analyze only one: variable
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