Business Research Project Part 5: Research Report and Presentation

Topics: Sample size, Statistics, Sampling Pages: 8 (1332 words) Published: May 13, 2015

Business Research Project Part 5: Research Report
Jaceilia Ajanaku, Anthony Beltran, Alysande Carrington, Tennile Connor, Charles Foster QNT/561
May 6, 2015
Patricia A. Towne

Business Research Project Part 5: Research Report
Accomplishing the daily office goals at XYZ Relations takes complete teamwork from all employees. Being able to attend to all potential applicants in a timely manner demands dedication, effort and understanding. The tedious work required, presses employees to focus on tasks and depend on one another to accomplish goals. With an abundance amount of paperwork to deal with, XYZ Relations has been able to keep a steady pace by hiring the right employees and completing all required screening before employees begin work.

Inferential Statistics and Findings Review
XYZ Relation’s HR Department had some of their team member’s research inferential statistics; a statistical hypothesis is a statement about the numerical value of a population parameter.” (McClave, Benson, & Sincich, 2011). The question at hand, is there a relationship between the speed of onboarding a new employee and the days it takes to complete required background tests? . “The average time-to-fill for companies of 1,000 employees and more is 43 days, compared with 29 days for companies having fewer employees.” (Lytle, 2013) Surprisingly, all the team members came back with same search results using a t-test and random sampling. Based on the teams finds, unanimously, the decision was to reject the null hypothesis due to the calculated p values being lower than the error () value. Using a t-test has many advantages. One is that the understanding of the output is easy to translate and interpret statistical differences. Two, even with a small sample set; the t-test is still relevant and needs one value from each test subject. Since many people today are not forth coming with personal information using a small sample set was not an issue for Survey’s 2000 as they knew the data is still relevant regardless of the sample size. Three, the formula for a t-test is simple and easy; not requiring statistical training. The down side to a t-test is that the confidence interval can be manipulated to attain a desired outcome. Skewing with data is unethical and XYZ Relations needed to ensure that the date was not going to be manipulated, hence why XYZ hired Survey’s 2000. Another weakness of the t-test is outcomes are only correct with normal populations. We all know real populations are not typically “normal”. There are always exceptions. The happy path is never a true test. Business Research Report

The research question posed for XYZ Relations was: is there a relationship between the speed of onboarding a new employee and the days it takes to complete required background tests? After reviewing the below testing, we do find that the speed of onboarding is hampered by the time it takes to complete the background checks. The hypothesis presented is that it takes longer than the average human resources company (45 days) to receive results from background checks. H0: Days to Hire ≤ 45; HA: Days to Hire > 45. The most appropriate statistical tool to test the hypothesis is the t-test to compare the data set from XYZ Relations to the average of other HR corporations. The hypothesis test will use a 95% confidence level with an upper tail test performed. The data computed with the 95% confidence level allows the rejection of the null hypothesis due to the calculated p values being lower than the error () value. Hypothesis Test: Paired Observations

45.000 hypothesized value
53.880 mean Calculated Date to Hire
36.200 mean Days to complete background check
17.680 mean difference
3.923 std. dev.
0.785 std. error
25 n
24 df
-34.816 t
0.10710.1043p value (upper and lower for 95% confidence level) 1.0000 p-value (one-tailed, upper)

The data collected for this research was normally distributed and...

References: Lytle, T. (2013). Streamline hiring. HRMagazine, 58(4), 63-65. Retrieved from
McClave, J. T., Benson, P. G., & Sincich, T. (2011). Statistics for Business and Economics (11th ed.). Boston, MA: Prentice Hall.
Mueller, J. R., & Baum, B. (2011). The definitive guide to hiring right. The Journal of Applied Business and Economics, 12(3), 140-153. Retrieved from
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