DQ Responses week 5
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
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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 mpg with a standard deviation of 14. So when this was used we have only the sample standard deviation(Cooper & Schindler 2011).
Dolores Lovato
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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). 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
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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 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
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