For this Knowledge Assessment, you calculate the concurrent validity coefficient between a predictor scale and criterion measure in the dataset provided. First, you will be guided through the process of how to create new variable scales. Then, you calculate the validity measure on one of the scales. The MoneyData.sav dataset that you have been provided contains three scales that measure financial attitudes: LIFESTYLE (L1 to L6) measures the desire for a luxurious lifestyle DEPENDENCE (D1 to D6) measures the tendency to depend on others for financial support (high scores) vs. supporting others (low scores) RISKTAKING (R1 to R6) measures the tendency to take financial risks in investments and careers Create Three New Variables Showing the Scores on These Three Scales To create the RISKTAKING scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “RISKTAKING.” In the “Numeric Expression” field, type SUM(R1 TO R6). To create the DEPENDENCE scale click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “DEPENDENCE.” In the “Numeric Expression” field, type SUM(D1 TO D6). On the LIFESTYLE items, item L6 (“I’d rather have a modest lifestyle because it is less stressful”) is scored in the reverse direction from the other items. People endorsing this item want a less extravagant lifestyle; endorsing the other items suggests the desire for a more extravagant lifestyle. The scoring on this item needs to be reversed. To create the reversed L6 item click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “L6R.” In the “Numeric Expression” field, type “6 – L6.” By subtracting the item responses from six, they are reversed: 5 becomes 1, 4 becomes 2, etc. To create the LIFESTYLE scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “LIFESTYLE.” In the “Numeric Expression” field, type SUM(L1 TO L5, L6R). Calculate a Validity Measure for One of the Scales There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between Dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = - .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale. Think of another relationship that might support the validity of one of the scales and then test your hypothesis using the data. You will need to submit: Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported The results of your statistical test of your validity hypothesis Your conclusion about validity, given the results of your statistical test Description Instructions For this Knowledge Assessment, you calculate the concurrent validity coefficient between a predictor scale and criterion measure in the dataset provided. First, you will be guided through the process of how to create new variable scales. Then, you calculate the validity measure on one of the scales. The MoneyData.sav dataset that you have been provided contains three scales that measure financial attitudes: LIFESTYLE (L1 to L6) measures the desire for a luxurious lifestyle DEPENDENCE (D1 to D6) measures the tendency to depend on others for financial support (high scores) vs. supporting others (low scores) RISKTAKING (R1 to R6) measures the tendency to take financial risks in investments and careers Create Three New Variables Showing the Scores on These Three Scales To create the RISKTAKING scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “RISKTAKING.” In the “Numeric Expression” field, type SUM(R1 TO R6). To create the DEPENDENCE scale click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “DEPENDENCE.” In the “Numeric Expression” field, type SUM(D1 TO D6). On the LIFESTYLE items, item L6 (“I’d rather have a modest lifestyle because it is less stressful”) is scored in the reverse direction from the other items. People endorsing this item want a less extravagant lifestyle; endorsing the other items suggests the desire for a more extravagant lifestyle. The scoring on this item needs to be reversed. To create the reversed L6 item click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “L6R.” In the “Numeric Expression” field, type “6 – L6.” By subtracting the item responses from six, they are reversed: 5 becomes 1, 4 becomes 2, etc. To create the LIFESTYLE scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “LIFESTYLE.” In the “Numeric Expression” field, type SUM(L1 TO L5, L6R). Calculate a Validity Measure for One of the Scales There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between Dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = - .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale. Think of another relationship that might support the validity of one of the scales and then test your hypothesis using the data. You will need to submit: Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported The results of your statistical test of your validity hypothesis Your conclusion about validity, given the results of your statistical test Description Instructions For this Knowledge Assessment, you calculate the concurrent validity coefficient between a predictor scale and criterion measure in the dataset provided. First, you will be guided through the process of how to create new variable scales. Then, you calculate the validity measure on one of the scales. The MoneyData.sav dataset that you have been provided contains three scales that measure financial attitudes: LIFESTYLE (L1 to L6) measures the desire for a luxurious lifestyle DEPENDENCE (D1 to D6) measures the tendency to depend on others for financial support (high scores) vs. supporting others (low scores) RISKTAKING (R1 to R6) measures the tendency to take financial risks in investments and careers Create Three New Variables Showing the Scores on These Three Scales To create the RISKTAKING scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “RISKTAKING.” In the “Numeric Expression” field, type SUM(R1 TO R6). To create the DEPENDENCE scale click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “DEPENDENCE.” In the “Numeric Expression” field, type SUM(D1 TO D6). On the LIFESTYLE items, item L6 (“I’d rather have a modest lifestyle because it is less stressful”) is scored in the reverse direction from the other items. People endorsing this item want a less extravagant lifestyle; endorsing the other items suggests the desire for a more extravagant lifestyle. The scoring on this item needs to be reversed. To create the reversed L6 item click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “L6R.” In the “Numeric Expression” field, type “6 – L6.” By subtracting the item responses from six, they are reversed: 5 becomes 1, 4 becomes 2, etc. To create the LIFESTYLE scale, click TRANSFORM>COMPUTE VARIABLE. In the “Target Variable” field, type “LIFESTYLE.” In the “Numeric Expression” field, type SUM(L1 TO L5, L6R). Calculate a Validity Measure for One of the Scales There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between Dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = - .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale. Think of another relationship that might support the validity of one of the scales and then test your hypothesis using the data. You will need to submit: Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported The results of your statistical test of your validity hypothesis Your conclusion about validity, given the results of your statistical test 

Individuals have a variety of personality traits, values, and attitudes that they bring with them into the workplace. These characteristics, whether stable or transient, are termed dispositional factors. Because dispositional factors can be useful in predicting individual behavior and performance across diverse situations, organizations value this information when hiring, developing, and promoting employees.The concepts of personal dispositions often are referred to interchangeably in the literature as traits, personality, and individual characteristics. Job attitudes research commonly uses situational variables (e.g., pay, work environment, task characteristics) as well as dispositional variables (e.g., conscientiousness, neuroticism) as determinants of job attitudes. In this Discussion, you will take a position on whether job attitudes are influenced more by situational or dispositions variables. You will also explore how certain aspects such as gender, age, industry, or employee educational level might also play a mediating role.To prepare for this Discussion:Think about whether job attitudes are affected most by dispositional or situational factors. Consider aspects of gender, age, industry, or educational level that might influence perceptions of situational and/or dispositional factors.Read the article “The Relationship Between Personality and Job Satisfaction Across Occupations.” Consider how individual personality influences career choice and the impact on P-E fit and commitment.Read the article “Person-Environment Fit: A Review of its Basic Tenets.” Think about the individual and organizational attributes that employees consider most important to them. Consider the impact of this and personality profiles on fit and job satisfaction.Part 1Post a response to the following: Provide your position on whether job attitudes are affected most by situational factors or by a person’s disposition and justify your position. Explain any aspects of gender, age, industry or employee educational level (or other factors in the literature) that can play a significant role in how situational and dispositional factors affect job attitudes.

Provide a comprehensive response to the question(s) below. Be sure to draft your response in your own words (do not quote verbatim from the textbook or internet).  Should be 200 - 300 words long. Read Chapters 13-14 and the Emancipation Proclamation. Once all reading is complete, respond to the following items: In early 1863, President Lincoln issued the Emancipation Proclamation. Why did Lincoln decide to issue the Proclamation at this particular time?What factors determined this decision?What did the President hope to gain?What were the limitations of the Proclamation, and what was its larger historical significance? The Emancipation Proclamation ·  The Emancipation Proclamation (page 1) Record Group 11 General Records of the United States President Abraham Lincoln issued the Emancipation Proclamation on January 1, 1863, as the nation approached its third year of bloody civil war. The proclamation declared "that all persons held as slaves" within the rebellious states "are, and henceforward shall be free." Despite this expansive wording, the Emancipation Proclamation was limited in many ways. It applied only to states that had seceded from the Union, leaving slavery untouched in the loyal border states. It also expressly exempted parts of the Confederacy that had already come under Northern control. Most important, the freedom it promised depended upon Union military victory. Although the Emancipation Proclamation did not end slavery in the nation, it captured the hearts and imagination of millions of Americans and fundamentally transformed the character of the war. After January 1, 1863, every advance of federal troops expanded the domain of freedom. Moreover, the Proclamation announced the acceptance of black men into the Union Army and Navy, enabling the liberated to become liberators. By the end of the war, almost 200,000 black soldiers and sailors had fought for the Union and freedom. From the first days of the Civil War, slaves had acted to secure their own liberty. The Emancipation Proclamation confirmed their insistence that the war for the Union must become a war for freedom. It added moral force to the Union cause and strengthened the Union both militarily and politically. As a milestone along the road to slavery's final destruction, the Emancipation Proclamation has assumed a place among the great documents of human freedom. The original of the Emancipation Proclamation of January 1, 1863, is in the National Archives in Washington, DC. With the text covering five pages the document was originally tied with narrow red and blue ribbons, which were attached to the signature page by a wafered impression of the seal of the United States. Most of the ribbon remains; parts of the seal are still decipherable, but other parts have worn off. The document was bound with other proclamations in a large volume preserved for many years by the Department of State. When it was prepared for binding, it was reinforced with strips along the center folds and then mounted on a still larger sheet of heavy paper. Written in red ink on the upper right-hand corner of this large sheet is the number of the Proclamation, 95, given to it by the Department of State long after it was signed. With other records, the volume containing the Emancipation Proclamation was transferred in 1936 from the Department of State to the National Archives of the United States.