BUS 308 Week 1 Assignment
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BUS 308 Week 1 Assignment in EXCEL (A+ Grade Assured, Latest Data)
| Week 1. | Measurement and Description - chapters 1 and 2 | ||||||||||||
| The goal this week is to gain an understanding of our data set - what kind of data we are looking at, some descriptive measurse, and a | |||||||||||||
| look at how the data is distributed (shape). | |||||||||||||
| 1 | Measurement issues. Data, even numerically coded variables, can be one of 4 levels - | ||||||||||||
| nominal, ordinal, interval, or ratio. It is important to identify which level a variable is, as | |||||||||||||
| this impact the kind of analysis we can do with the data. For example, descriptive statistics | |||||||||||||
| such as means can only be done on interval or ratio level data. | |||||||||||||
| Please list under each label, the variables in our data set that belong in each group. | |||||||||||||
| Nominal | Ordinal | Interval | Ratio | ||||||||||
| b. | For each variable that you did not call ratio, why did you make that decision? | ||||||||||||
| 2 | The first step in analyzing data sets is to find some summary descriptive statistics for key variables. | ||||||||||||
| For salary, compa, age, performance rating, and service; find the mean, standard deviation, and range for 3 groups: overall sample, Females, and Males. | |||||||||||||
| You can use either the Data Analysis Descriptive Statistics tool or the Fx =average and =stdev functions. | |||||||||||||
| (the range must be found using the difference between the =max and =min functions with Fx) functions. | |||||||||||||
| Note: Place data to the right, if you use Descriptive statistics, place that to the right as well. | |||||||||||||
| Some of the values are completed for you - please finish the table. | |||||||||||||
| Salary | Compa | Age | Perf. Rat. | Service | |||||||||
| Overall | Mean | 35.7 | 85.9 | 9.0 | |||||||||
| Standard Deviation | 8.2513 | 11.4147 | 5.7177 | Note - data is a sample from the larger company population | |||||||||
| Range | 30 | 45 | 21 | ||||||||||
| Female | Mean | 32.5 | 84.2 | 7.9 | |||||||||
| Standard Deviation | 6.9 | 13.6 | 4.9 | ||||||||||
| Range | 26.0 | 45.0 | 18.0 | ||||||||||
| Male | Mean | 38.9 | 87.6 | 10.0 | |||||||||
| Standard Deviation | 8.4 | 8.7 | 6.4 | ||||||||||
| Range | 28.0 | 30.0 | 21.0 | ||||||||||
| 3 | What is the probability for a: | Probability | |||||||||||
| a. Randomly selected person being a male in grade E? | |||||||||||||
| b. Randomly selected male being in grade E? | |||||||||||||
| Note part b is the same as given a male, what is probabilty of being in grade E? | |||||||||||||
| c. Why are the results different? | |||||||||||||
| 4 | A key issue in comparing data sets is to see if they are distributed/shaped the same. We can do this by looking at some measures of where | ||||||||||||
| some selected values are within each data set - that is how many values are above and below a comparable value. | |||||||||||||
| For each group (overall, females, and males) find: | Overall | Female | Male | ||||||||||
| A | The value that cuts off the top 1/3 salary value in each group | "=large" function | |||||||||||
| i | The z score for this value within each group? | Excel's standize function | |||||||||||
| ii | The normal curve probability of exceeding this score: | 1-normsdist function | |||||||||||
| iii | What is the empirical probability of being at or exceeding this salary value? | ||||||||||||
| B | The value that cuts off the top 1/3 compa value in each group. | ||||||||||||
| i | The z score for this value within each group? | ||||||||||||
| ii | The normal curve probability of exceeding this score: | ||||||||||||
| iii | What is the empirical probability of being at or exceeding this compa value? | ||||||||||||
| C | How do you interpret the relationship between the data sets? What do they mean about our equal pay for equal work question? | ||||||||||||
| 5. | What conclusions can you make about the issue of male and female pay equality? Are all of the results consistent? | ||||||||||||
| What is the difference between the sal and compa measures of pay? | |||||||||||||
| Conclusions from looking at salary results: | |||||||||||||
| Conclusions from looking at compa results: | |||||||||||||
| Do both salary measures show the same results? | |||||||||||||
| Can we make any conclusions about equal pay for equal work yet? | |||||||||||||
12 years ago
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