Many Of You Struggle With Statistics But You Need At Least A

Many Of You Struggle With Statistics But You Need At Least A Basic Und

Many of you struggle with statistics but you need at least a basic understanding. Here are some tips to help complete Case 5: 1. What kind of relationship exists between employees’ scores on the manual dexterity test and their performance ratings? (See page 209.) 2. Suppose a candidate scored 44 on the manual dexterity test. The regression equation predicting job performance using the manual dexterity test is: 32.465 + (1.234 × Manual dexterity test score). What is the candidate’s predicted job performance? (Find the MEAN manual dexterity test score from the table. Multiply the numbers in parentheses and add to the first number.) 3. Assume that only candidates with predicted job performance above 85 are to be hired. This translates to a score of at least 43 on the manual dexterity test. Assume only those with scores above 43 were hired (20 of the 30 people in this sample). Would the use of this test have led to evidence of adverse impact based on sex or race? The relevant data on the 20 people exceeding the cutoff are above in Table B. The hiring rate for females is 81.25% (13 hired out of 16 or 13/16=.8125). This is the highest proportion hired of any group of candidates. According to the 4/5ths (also called the 80% rule), the hiring rate for any other groups (males in this case) should be at least 4/5 (80%) of the hiring rate for the group with the highest proportion hired. 0.8 (80%) × 0.8125 (hiring rate for females) = 0.65 (65%). The hiring rate for males is 50% (7 hired out of 14 or 7/14=.50) which is less than 65%. Thus, there is evidence for adverse impact against males because men were hired at a proportionally lower rate. Now use this same process to compare the Hispanic, Caucasian, and African American groups. Susan A. Student Embry-Riddle Aeronautical University 2.3 - CASE ANALYSIS: FUNDING THE RAILROADS 2 Abstract Funding the Transcontinental Railroad in the 19th century was a major issue for the United States Government. There were several possible courses of action. Two of these are included here as well as the problems and advantages of each. In conclusion, the rationale for government funding is presented. Keywords: railroads, intercontinental, funding, entrepreneur 2.3 - CASE ANALYSIS: FUNDING THE RAILROADS .3 - Case Analysis: Funding the Railroads I. Summary The speculative benefits of a transcontinental railroad were easy enough to articulate: there was fertile land out west for migrants to farm, gold and silver to be mined in California, and of course it was a matter of national pride (Ambrose, 2000). According to Ambrose (2000), the whole country was clamoring for it to be done, yet few were crazy enough to invest as “the risks of financial failure and ruin were huge†(Union Pacific, n.d. para. 3). Ultimately, funding was provided by the United States government via the Pacific Railroad Act of 1862, “mostly in the form of land grants to the railroads; the railroads would sell the unused land to fund the construction†(Ambrose, 2000, p. 47). Much of the land was all but worthless at the time, but it was assumed that as transportation cost were reduced, the land would become more valuable (Garrison & Levinson, 2014; Ambrose, 2000). II. Problem The problem is multifaceted. Unfortunately for the railroad companies, they could not sell most of the land until after the railroad was built, and they could not build the railroad without the proceeds of the land sales (Ambrose, 2000). Some relief came with the Pacific Railroad Act of 1864 which doubled land grants and (more importantly) provided the ability to borrow against the land grants by issuing bonds (Union Pacific, n.d.). However, even with doubled bonds and the ability to borrow against them, the transcontinental railroad had major financing difficulties (Ambrose, 2000; Union Pacific, n.d.). On the other hand, Illinois representative E.B. Washburn (as quoted in Ambrose, 2000) called the 1864 bill “the most monstrous and flagrant attempt to overreach the government and 2.3 - CASE ANALYSIS: FUNDING THE RAILROADS 4 the people…†(p. 94), charging that the Wall Street elites pushing for funding were only out to profit off the public (Ambrose, 2000). Eglin Air Force Base Archaeologist Benjamin Aubuchon (personal communication, August 17, 2016) affirms that while the Pacific Railroad Acts were instrumental in building the transcontinental railroad, many railroad corporations in the Southeastern U.S. were formed with no intention of following through. In Northwest Florida, the timber-rich land was usually promptly sold for lumber (or turpentine operations in the early 1900s) as soon as it was acquired, whereupon shareholders pocketed the profits as corporations went bankrupt, abandoning the vast majority of the proposed railways (B. Aubuchon, personal communication, August 17, 2016). III. Significance of the Problem While the public was eager to see the transcontinental line built, putting taxpayer’s money behind the project was out of the question (Ambrose, 2000). Offering land grants was seen as a way to fund construction with little public risk, but some felt that this was still too much government meddling. Ultimately, those who acted in good faith by attempting to actually build the proposed railroads had extreme difficulty funding the construction, with many risking family fortunes and going deep into personal debt (Ambrose, 2000; Union Pacific, n.d.). Yet others took the public land without providing anything of value in return. IV. Development of Alternative Actions Alternative Action 1. The U.S. government could have abstained from providing financial assistance and allowed free market forces alone to drive development. Advantages. This alternative would have eliminated the risk of Robber-Baron types betraying the public trust. Disadvantages. Honest entrepreneurs were scarcely able to fund the rails west even with the Pacific Railroad Acts. While the railroad certainly would have been built at some point, it would have taken decades longer as it moved incrementally across the nation. Alternative Action 2. The U.S. government could have limited the number of lines funded. For example, companies could have bid on one or two lines to California, and maybe one north-south line. The bidding could have been for the whole line or in sections. More generous land grants would have better facilitated development and these would be feasible as total lands granted would be drastically reduced. Advantages. This alternative would have served to satisfy public demand with reduced risk of Robber-Barron types betraying public trust. Furthermore, lines could be privately funded off of the first lines as demand called for it. Disadvantages. While the distance to California would be crossed more quickly, privately funded lines with no land grants would have taken longer to spread. Limiting the number of companies funded could prompt charges of government favoritism. V. Recommendation. The demand for a transcontinental railroad was clear. It is reasonable to assume a majority of entrepreneurs will strive to maximize profits by satisfying demand. Therefore, publicly funding only the lines for which there was very clear public demand coupled with private refusal to invest would have ensured that funds were used for their intended purposes. For example, if there had been great demand for railroads in Northwest Florida, entrepreneurs who received the land grants to build would have been foolish to simply sell the land and back out. This makes Alternative Action 2 the superior solution to the transcontinental railroad-funding problem. References Ambrose, S. E. (2000). Nothing like it in the world. New York, NY: Simon & Schuster. Garrison, W. L., & Levinson, D. M. (2014). The transportation experience (2nd ed.). New York, NY: Oxford University Press. Union Pacific. (n.d.). Financing. Retrieved from 8/4/2018 Vitalsource: Strategic Staffing 1/9 PRINTED BY: [email protected] . Printing is for personal, private use only. No part of this book may be reproduced or transmitted without publisher's prior permission. Violators will be prosecuted. Develop Your Skills Exercise: This chapter’s Develop Your Skills feature gave you some tips on assessing job candidates. Based on what you read in this chapter, what are three additional tips that you would add to the list? (Additional exercises are available at the end of this chapter’s supplement that will enable you to build additional computational and decision-making skills when using data.) Opening Vignette Exercise: The opening vignette described how Xerox developed an assessment system to improve the performance and retention of its call center workers. Reread the vignette and answer the following questions: a. What other assessments do you think could be considered for the job given the company’s high–service quality goal? Why? b. If you applied to this company and were denied a job due to your personality assessment results, how would you feel? Would you think that these methods were fair? 8/4/2018 Vitalsource: Strategic Staffing 2/9 Case Study You just became the head of staffing for BabyBots, a manufacturer of small robots. You were surprised to learn that the company had never validated the manual dexterity test it uses to assess job candidates for its manufacturing jobs. You decided to do a concurrent validation study and administered the test to thirty manufacturing workers. Their scores are reported in Table 8-4, along with their ages, sex, race, and job performance ratings. You also calculated the correlation between the manual dexterity test and job performance to assess the test’s validity. You then examined the relationship between employees’ test scores and their performance ratings. The results of this analysis are shown in Tables 8-5 and 6. Questions 1. What kind of relationship exists between employees’ scores on the manual dexterity test and their performance ratings? 2. Suppose a candidate scored 44 on the manual dexterity test. The regression equation predicting job performance using the manual dexterity test is: 32.465 + (1.234 × Manual dexterity test score). What is the candidate’s predicted job performance? 3. Assume that only candidates with predicted performance above 85 are to be hired. This translates to a score of at least 43 on the manual dexterity test. Assume only those with scores above 43 were hired (20 of the 30 people in this sample). Would the use of this test have led to evidence of adverse impact based on sex or race? The relevant data on the 20 people exceeding the cutoff were presented earlier in the table. 4. Given the validity results you found, would you recommend use of this test as a selection device? If so, how would you use it? Semester-Long Active Learning Project Finish the assignment for Chapter 7 and begin researching, describing, and critically analyzing the alignment between the position you chose and the firm’s existing assessment practices. Devise a series of assessment methods (interviews, assessment centers, work samples, and so forth) for evaluating job candidates. Using what you learned in Chapter 4, identify how your assessment plan will enable the company to be compliant with equal employment opportunity (EEO) laws and other legal requirements. Case Study Assignment: Strategic Staffing at Chern’s See the appendix at the back of the book for this chapter’s Case Study Assignment. 32.465 + (1.234 × Manual dexterity test score) Vitalsource: Strategic Staffing 8/9 Chapter Supplement Attenuation Due to Unreliability Because correlations are an important tool for determining the strategic usefulness of a particular assessment tool and for legal defensibility, it is important to recognize that observed correlations can be influenced by some important factors that may exist in organizational contexts. Attenuation is the weakening of observed correlations. No measure is perfect, and unreliability of measures can attenuate correlations. Consider Figure 8-8. In the first scatter plot, we depicted a perfect correlation along with arrows indicating the addition of random error. In the second scatter plot, you can see the impact of the added measurement error (unreliability). You can easily see how unreliability adds “noise” or error to the system, attenuating the correlation. The observed correlation has moved from being perfect, +1.0, to about +0.67. In the most extreme case, a correlation with a random variable (a completely unreliable measure) will hover around zero. The impact of error is another illustration of why it is important to be systematic in your staffing system and procedures. If different interviewers are affected by noninterview factors, then they cannot be reliable, and their scores will not be as strongly correlated with later job performance. Observed correlations can be corrected for attenuation if you know the reliability of the measure(s). The formula is: Corrected r_XY = Observed r_XY / √(r_XX × r_YY). Range restriction is another factor that can influence correlations, as organizations often only hire top-performing employees, reducing the variance of scores and thus the correlation. For these reasons, understanding measurement reliability and range restriction effects is crucial for valid organizational assessments.

Paper For Above instruction

In organizational settings, understanding the relationships between test scores and job performance is fundamental for effective personnel selection. A core concept in this context is the correlation between assessment measures and actual job outcomes, which impacts both validity and fairness. This paper discusses the nature of these relationships, particularly examining the use of manual dexterity tests and their statistical validation within a staffing framework, while also exploring issues such as adverse impact and measurement reliability.

Understanding the Relationship Between Test Scores and Job Performance

The relationship between employees’ scores on assessments such as manual dexterity tests and their performance ratings typically manifests as a positive correlation. This indicates that higher test scores tend to be associated with better job performance. In the case examined, a correlation coefficient (r) quantifies this relationship, providing a measure of the test’s validity (Salgado et al., 2003). A robust positive correlation signifies that the test can predict job performance effectively, aiding organizations in screening candidates more accurately.

Assessing the specific strength of this relationship involves statistical analysis. For instance, the correlation data in the case study indicated a meaningful relationship, which supports the test's use as a screening tool if the correlation is sufficiently high. However, the magnitude of the correlation also suggests the degree of measurement error and the potential attenuation of the relationship. As noted by Hunter and Schmidt (2004), unreliability in measurement tools can weaken observed correlations, leading organizations to underestimate the true relationship between test scores and job performance.

Predicting Performance Using Regression Analysis

Regression equations serve as practical tools for predicting individual job performance based on assessment scores. In the given case, the regression equation is:

32.465 + (1.234 × test score)

For a candidate with a test score of 44, the predicted performance is calculated as:

32.465 + (1.234 × 44) = 32.465 + 54.249 = 86.714

This prediction indicates that the candidate’s expected job performance score is approximately 86.71 on the performance rating scale. Using such equations helps employers make informed decisions, ensuring that only candidates with predicted performance scores above the threshold are considered for hiring.

Adverse Impact and Fairness in Selection

Adverse impact occurs when selection practices disproportionately exclude certain groups based on protected characteristics such as sex or race. Regulatory frameworks like the Civil Rights Act require organizations to monitor and mitigate such impacts (Pfeffer & Fong, 2005). In the case study, by imposing a cutoff score on the manual dexterity test, the organization effectively filters candidates; however, this can inadvertently favor or disadvantage particular demographic groups.

If only candidates scoring above 43 are hired, and the data show that a lower proportion of males or minority groups exceed this threshold compared to their counterparts, an adverse impact might be evident. The four-fifths rule provides a benchmark: if the hiring rate for any group is less than 80% of the highest group’s rate, adverse impact is suspected (Blum, 2017). For example, if the highest group (females) has an 81.25% hiring rate, a group with a rate below approximately 65% may be considered disadvantaged, which can violate equal employment opportunity principles.

In the case, the male hiring rate was 50%, which is below 65%, indicating potential adverse impact against males. Similarly, comparing Hispanic, Caucasian, and African American groups via this rule can reveal disparities. It is essential that organizations continuously analyze selection procedures to ensure fairness and legal compliance, adjusting methods accordingly (Bretz & Yavuz, 2008).

Measurement Validity, Reliability, and Attenuation

The validity of a selection test is the degree to which it accurately predicts job performance, which relies heavily on its reliability—the consistency of the measurement (Cohen et al., 2018). Unreliable measures introduce error, leading to attenuation, or weakening, of observed correlations. As shown in the example, measurement error inflates the “noise” in data, resulting in lower-than-actual correlations, which can cause organizations to underestimate the true predictive power of assessments.

The formula for correcting attenuation is:

Corrected rXY = Observed rXY / √(rXX × rYY)

where r_XX and r_YY are the reliabilities of the respective measures. Improving measurement reliability through standardized procedures and training enhances the accuracy of predictions. Additionally, range restriction, which occurs when only top performers are hired, reduces variability in scores and diminishes the observed correlation, further impacting validity (Schmidt & Hunter, 1998). Therefore, organizations must consider these factors when validating and applying assessment tools to ensure fair and effective personnel decisions.

Conclusion

Effective personnel selection hinges on understanding and utilizing the relationship between assessment scores and job performance. Valid and reliable measures enable organizations to predict future performance and