Analyze data from hr hiring process

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Reference no: EM131643398

Discussion

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Data is crucial for any department in business, particularly human resources. If the "data are numerical (consisting only of numbers), alphabetic (consisting only of letters), or alphanumerical (mixed numbers and letters), they are useless unless we know what they represent" (Sharpe, De Veaux, Velleman, p. 3). That is why the Five W's are critical to gathering useful information, particularly answering the who and the what. Quantitative variables tend to be measured numerically or with units while qualitative is separated by the name of the category. When determining a method of collecting this data, it's often broken down into cross-sectional and time series data. Cross-sectional data measures several variables all at the same point. Cross-sectional data is used in many areas of research "although this study design is appropriate mainly for descriptive investigations" or qualitative data (Lee, 1994). To the contrary, time series measures data in an ordered sequence in a single quantitative measurement over regular intervals. This method tends to be used more commonly in business with monthly, quarterly, and annual reports.

When specifically looking at the HR department they deal with hiring new candidates and that may consume a lot of their time. In order to analyze data from their hiring process, they can measure certain data off of a resume. This would include degree level, years of experience, age, and expected salary. By using a cross sectional method to gather all this information from current employees, they can use this data to build a multiple linear regression model. Once they have the data from current employees and the model is complete, HR can use this information from resumes to help them further vet the new applicants and get the qualified ones in for interviews. Overall, HR has access to a great deal of information and statistics can be used to help increase the efficiency in the organization.

Reference no: EM131643398

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