# Bus 308 Week 5 Assignment Composition

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Week 5 Correlation and Regression Create a correlation table for the variables in our data set. (Use analysis ToolPak or StatPlus:mac LE function Correlation.) a. Reviewing the data levels from week 1, what variables can be used in a Pearson's Correlation table (which is what Excel produces)? b. Place table here (C8 in Output range box): Salary Compa Midpoint Age Performance Rating Service Raise Salary 1 Compa 0.61647174 1 Midpoint 0.98897178 0.5006577 1 Age 0.54357969 0.195218 0.567111 1 Performance Rating 0.15130696-0.101271 0.191751 0.1392384 1 Service 0.45170496 0.1820746 0.471147 0.5651332 0.2257007594 1 Raise-0.04142104-0.042731 -0.028913-0.180427 0.673659763 0.1027869 1 c. Using r = approximately .28 as the signicant r value (at p = 0.05) for a correlation between 50 values, what variables are significantly related to Salary? Compa, Midpoint, Age, Service To compa? Salary, Midpoint d. Looking at the above correlations - both significant or not - are there any surprises -by that I mean any relationships you expected to be meaningful and are not and vice-versa? I expected a strong positive correlation between Performance Rating and Salary, but the correlation between the two variables ended up being weak. It was surprising that the correlation between Performance Rating and Compa was negative. I also expected the variable Raise to have positive correlations with Salary, Compa, Midpoint and Age, but Raise has negative correlations with all these variables. e. Does this help us answer our equal pay for equal work question? 2 Below is a regression analysis for salary being predicted/explained by the other variables in our sample (Midpoint, age, performance rating, service, gender, and degree variables. (Note: since salary and compa are different ways of expressing an employee’s salary, we do not want to have both used in the same regression.) Plase interpret the findings. Ho: The regression equation is not significant. Ha: The regression equation is significant. Ho: The regression coefficient for each variable is not significant Note: technically we have one for each input variable. Ha: The regression coefficient for each variable is significant Listing it this way to save space. Final Paper2Statistics in general is the practice of the numerical data being collected, analyzed, and interpreted with the use of various mathematical methods in order to obtain the range of estimated conclusions that would be needed. It would also be used for the purpose of coming up with the sums in a whole from those in a representative sample. The collection of the statistical data would occur on an everyday basis in all aspects of life, and then it would be analyzed using a number of analytical tools. The results would then be used in the making of more informed decisions. Statistics are now being used in the military, and throughout any organizations, and even in the simplest of everyday things such as grocery shopping. The reason for this paper is to identify what my understanding of the basic of statistics that I have learned throughout this course. The topics mentioned consist of descriptive and inferential statistics, hypothesis development and testing, selection of appropriate statistical tests, and evaluating those results.Descriptive statisticsDescriptive statistics is the analysis of the data that describes and summarizes the data in a way that configuration may develop from the data. In plain terms, it describes what is going on within the data collections that are being conducted. It does not let us make the assumptions that would go outside the range of the data that was already analyzed or reached and let us reach any conclusions with regards to the hypotheses we already stated. “Descriptive statistics are very important because if we simply presented our raw data it would be hard to visualize what the data was showing, that is if there was a lot of data (Laerd statistics, 2013 page 1, para 3).” In the case where there are larger amounts of data, it would be tested and then assimilated into the less complex structures. From these structures patterns can be formulated. The importance of -->