DQ Responses week 5 RES 351 Hi Professor Jeff and class, The Z-test and T-test are frequently used parametric for independent samples. The Z-test is used with large sample sizes (exceeding 30 with both independent samples) or with smaller samples when the data are normally distributed and population variances are known (Cooper & Schindler, 2011). With small sample sizes, normally distributed populations, and the assumption of equal population variances, the T-test is appropriate (Cooper & Schindler, 2011). Similarities · A Z-test and T-test are each a type of parametric tests. · Parametric tests are resultant data from the given ranges which have given theconsumers to choose from intervals, such as 1-5. · Parametric tests such as the Z test and t test are used to “conclude if there is a statistical significance among the sample distribution average and a parameter(Cooper, D. & Schindler, P., 2011). · A Z test and a t-test could be opted as one sample test. One sample tests are opted when one sample is derived from a populace and a hypothesis “from the specified population” (Cooper, D. & Schindler, P., 2011), is tested. · A Z test and a t-test could be used as a two sample test with each of its samples being independent. · The Z test and t tests are matching while the sampling size is more than 120. Differences · The Z test and t test differ when the sample size is lower than 120. · The t test is suitable for minute sample sizes. · The Z test is suitable for huge or minute sample sizes. · A t test can be opted as a two sample test by pairing the samples. Reference Cooper, D., & Schindler, P. (2011). Business Research Methods (11th ed.). New York, NY: McGraw-Hill/Irwin Robert wolfe Response- A Parametric tests are defined as the Z test or t-test is used to determine the statistical significance between a sample distribution mean and a parameter. The Z distribution and t distribution differ. The t has more tail area than found in the normal distribution. This is a compensation for the lack of information about the population standard deviation. although the sample standard deviation is used as a proxy figure, the imprecisions makes it necessary to go farther away from 0 to include the percentage of values in the t distribution necessarily found in the standard normal. some of the real-world applications examples; are listed as; finding the average monthly balance of credit card holders compared to the average monthly balance five years ago. Comparing the failure rate of computers in a 20 hour test of quality specifications. Discovering the proportion of people who would shop in a new district compared to the assumed population proportion. Comparing the average product revenues this year to last years revenues. (Cooper & Schindler,2011). The example in the text stands out a great deal to me because I just purchased a hybrid-vehicle. The sample was 100 vehicles, the researcher found that the mean miles per gallon for the car is 52.5 mp ...

1. DQ Responses week 5 RES 351
Hi Professor Jeff and class,
The Z-test and T-test are frequently used parametric for
independent samples. The Z-test is used with large sample sizes
(exceeding 30 with both independent samples) or with smaller
samples when the data are normally distributed and population
variances are known (Cooper & Schindler, 2011). With small
sample sizes, normally distributed populations, and the
assumption of equal population variances, the T-test is
appropriate (Cooper & Schindler, 2011).
Similarities
· A Z-test and T-test are each a type of parametric tests.
· Parametric tests are resultant data from the given ranges which
have given theconsumers to choose from intervals, such as 1-5.
· Parametric tests such as the Z test and t test are used to
“conclude if there is a statistical significance among the sample
distribution average and a parameter(Cooper, D. & Schindler,
P., 2011).
· A Z test and a t-test could be opted as one sample test. One
sample tests are opted when one sample is derived from a
populace and a hypothesis “from the specified population”
(Cooper, D. & Schindler, P., 2011), is tested.
· A Z test and a t-test could be used as a two sample test with
each of its samples being independent.
· The Z test and t tests are matching while the sampling size is
more than 120.
Differences
· The Z test and t test differ when the sample size is lower than
120.
· The t test is suitable for minute sample sizes.

2. · The Z test is suitable for huge or minute sample sizes.
· A t test can be opted as a two sample test by pairing the
samples.
Reference
Cooper, D., & Schindler, P. (2011). Business Research Methods
(11th ed.). New York, NY: McGraw-Hill/Irwin
Robert wolfe
Response-
A Parametric tests are defined as the Z test or t-test is used to
determine the statistical significance between a sample
distribution mean and a parameter. The Z distribution and t
distribution differ. The t has more tail area than found in the
normal distribution. This is a compensation for the lack of
information about the population standard deviation. although
the sample standard deviation is used as a proxy figure, the
imprecisions makes it necessary to go farther away from 0 to
include the percentage of values in the t distribution necessarily
found in the standard normal. some of the real-world
applications examples; are listed as; finding the average
monthly balance of credit card holders compared to the average
monthly balance five years ago.
Comparing the failure rate of computers in a 20 hour test of
quality specifications.
Discovering the proportion of people who would shop in a new
district compared to the assumed population proportion.
Comparing the average product revenues this year to last years
revenues.
(Cooper & Schindler,2011).
The example in the text stands out a great deal to me because I
just purchased a hybrid-vehicle. The sample was 100 vehicles,

3. the researcher found that the mean miles per gallon for the car
is 52.5 mpg with a standard deviation of 14. So when this was
used we have only the sample standard deviation(Cooper &
Schindler 2011).
Dolores Lovato
Response-
Distinguish between a Z-test and a t-test. These types of tests
are not concerned with differentiating between dependent and
independent variables. They rely upon probability theory to
assess whether a difference calculation in the sample data
represents acceptable variation or rather a significant different
from acceptable variation. In the case of a one sample test we
are comparing a sample value to population parameter, whereas
in a two sample test we compare the difference in two sample
values compared to their respective population parameters.
Provide an example of each one that might be appropriate for
your current or previous place of employment.
According to Cooper and Schindler, the Z-test determine the
statistical significance between the sample distribution mean
and a parameter (Cooper & Schindler, 2011; pp. 468). The t-test
has 'more tail area' than found in a normal distribution and
makes up for the lack of information about the population
standard deviation (Cooper & Schindler, 2011; pp. 468). The t-
tests are normally used for independent samples, whereas the Z
test is used with large sample sizes that exceed 30 for both
independent samples or with 'smaller samples when the data are
normally distributed and population variances are known'
(Cooper & Schindler, 2011; 471).

4. At Target, we can use the z-test to sample and find the amount
of customers who apply for Target's credit or debit cards based
on 1000 transactions through the day. The z-test is appropriate
in the situation because the number is higher than 30 for the
independent sample. For each customer who applies for the
Target credit card, the score is converted to determine the
sample size. The t-test may be appropriate in the same situation
to compare the number of applicants in the current year versus
the previous five years, assuming that the standard deviation is
normal.
References
Cooper, D. & Schindler, P. (2011). Business Research Methods
(11th ed.). New York, NY: McGraw-Hill/Irwin.
Thomas Barbarak
Response-
The Z test and T test are used to determine the statistical
significance between a sample distribution mean and parameter.
The T test has more tail area that that found in normal
distribution. This is a compensation for the lack of information
about the population standard deviation. Even though the
sample standard deviation is used as a proxy figure, the
imprecision make it necessary to go farther away from zero to
include the percentage value in the T distribution necessarily
found in the standard normal. You would use a T test is used for
large groups where the population is independent of one
another. The Z test is used when they are not independent of
one another.
An example of the T test at my current employer would be using
two different products on the same type of car. From that we
can draw a hypothesis to find the best or more useful product.
We are located near a community college and a University the Z
test could be used to find out how many customers are from the

5. age 18-25 and in school.
Reference
1. Cooper, D., & Schindler, P. (2011). Business research
methods (11th ed.). New York, NY: McGraw-Hill/Irwin.
Michael Norris
Response-