Inferential Statistics and Findings
Inferential Statistics
Jaceilia Ajanaku
QNT/561
April 29, 2015
Patricia Towne
Inferential Statistics Inferential statistics can be used to qualify certain data analysis figures. These figures can be mostly found in descriptive statistics. As stated in previous research, the situation at hand is a human resource firm being able to acquire new personnel and process them to be ready for employment. The most important issue is the time between dates of hire to the date the personnel actually begin work. This has been an issue to all of the future employees of the firm. Many factors will be held accountable as far as this particular process goes. This study will focus on the relationship between the time of hire and the time to complete a background check of the individual.
Research Question, Hypothesis and Interpretation
Research Question: Is there a relationship between the speed of hiring a new employee and the required background tests?
The hypothesis Presented: It takes 45 days to process an employee due to background checks.
It takes more than 45 days to process an employee due to background checks. 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. This is proved to be 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.
Appendix
Here are the calculations for the null hypothesis in support of the problem outlined in the body of the paper.
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
.5
25 n
23 df
-34.815 t
0.1071 0.1043 p value (upper and lower for 95% confidence level)
1.0000 p-value (one-tailed, upper)
References
Cooper, D. R., & Schindler, P.S. (2011). Business
Jaceilia Ajanaku
QNT/561
April 29, 2015
Patricia Towne
Inferential Statistics Inferential statistics can be used to qualify certain data analysis figures. These figures can be mostly found in descriptive statistics. As stated in previous research, the situation at hand is a human resource firm being able to acquire new personnel and process them to be ready for employment. The most important issue is the time between dates of hire to the date the personnel actually begin work. This has been an issue to all of the future employees of the firm. Many factors will be held accountable as far as this particular process goes. This study will focus on the relationship between the time of hire and the time to complete a background check of the individual.
Research Question, Hypothesis and Interpretation
Research Question: Is there a relationship between the speed of hiring a new employee and the required background tests?
The hypothesis Presented: It takes 45 days to process an employee due to background checks.
It takes more than 45 days to process an employee due to background checks. 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. This is proved to be 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.
Appendix
Here are the calculations for the null hypothesis in support of the problem outlined in the body of the paper.
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
.5
25 n
23 df
-34.815 t
0.1071 0.1043 p value (upper and lower for 95% confidence level)
1.0000 p-value (one-tailed, upper)
References
Cooper, D. R., & Schindler, P.S. (2011). Business
References: Cooper, D. R., & Schindler, P.S. (2011). Business Research Methods (11th ed.). New York, NY: McGraw-Hill/Irwin.