Hr Statistical Techniques
Running Head: HR STATISTICAL TECHNIQUES
HR Statistical Techniques
Dona Palermo
HRM/558
Donna Wyatt
January 23, 2012
HR Statistical Techniques
Ayles Networks is an IT networking company employing over 3,000 people across the Southwestern United States. Although, centrally located, the Human Resources (HR) office is up to 500 miles from several corporate offices. The HR department has been tasked with using HR statistical techniques to assess the effectiveness of current staffing, training, and HR assessments (University of Phoenix, 2011). The HR department will identify the type of data needed, the application of t-test, ANOVA, and regression analysis statistical techniques will be discussed and additional techniques will be reviewed.
Required Data
Testing of hypotheses is the basis for research and that results in statistical findings. A null hypothesis is presumed true until proven otherwise by statistical testing. If the null hypothesis is rejected then the alternative hypothesis is accepted. To begin statistical testing to determine the effectiveness of training and staffing programs requires several types of data including current and required staffing levels, labor availability, and skill sets data is required for each position and location. Results of hiring and promotion assessments such as pre-employment, selection, required training, and performance evaluation scores are also required.
T-test
A t-test is used to evaluate the differences in means between two groups, which can be either independent or dependent (StatSoft, Inc., 2011, para. 1). The dependant variable is affected by the independent or predictor variable. Levels of measurement using a t-test include numeric, consisting of numbers as values and nominal, consisting of numbers assigned to names, categories, groups, or levels (Hopkins, 2000, para. 1; McIntire & Miller, 2007, p. 135). T-test can be used to analyze training, HR assessment, and staffing effectiveness
HR Statistical Techniques
Dona Palermo
HRM/558
Donna Wyatt
January 23, 2012
HR Statistical Techniques
Ayles Networks is an IT networking company employing over 3,000 people across the Southwestern United States. Although, centrally located, the Human Resources (HR) office is up to 500 miles from several corporate offices. The HR department has been tasked with using HR statistical techniques to assess the effectiveness of current staffing, training, and HR assessments (University of Phoenix, 2011). The HR department will identify the type of data needed, the application of t-test, ANOVA, and regression analysis statistical techniques will be discussed and additional techniques will be reviewed.
Required Data
Testing of hypotheses is the basis for research and that results in statistical findings. A null hypothesis is presumed true until proven otherwise by statistical testing. If the null hypothesis is rejected then the alternative hypothesis is accepted. To begin statistical testing to determine the effectiveness of training and staffing programs requires several types of data including current and required staffing levels, labor availability, and skill sets data is required for each position and location. Results of hiring and promotion assessments such as pre-employment, selection, required training, and performance evaluation scores are also required.
T-test
A t-test is used to evaluate the differences in means between two groups, which can be either independent or dependent (StatSoft, Inc., 2011, para. 1). The dependant variable is affected by the independent or predictor variable. Levels of measurement using a t-test include numeric, consisting of numbers as values and nominal, consisting of numbers assigned to names, categories, groups, or levels (Hopkins, 2000, para. 1; McIntire & Miller, 2007, p. 135). T-test can be used to analyze training, HR assessment, and staffing effectiveness
References: Ghauri, P., & Grønhaug, K. (2005). Research methods in business studies: A practical guide (3rd ed). New Jersey: Prentice Hall. Hopkins, W. G. (2000). A new view of statistics. Retrieved from http://www.sportsci.org/resource/stats/ttest.html McIntire, S. A., & Miller, L. A. (2007). Foundations of psychological testing: A practical approach (2nd ed.). London: Sage StatSoft, Inc. (2011). Electronic statistics textbook. Tulsa, OK. Retrieved from http://www.statsoft.com/textbook/ University of Phoenix. (2011). Week Six syllabus. Retrieved from University of Phoenix HRM/558—Research in Human Resource Management course website