Discussion: Develop a test for mean differences between the genders on a variable

Discussion: Develop a test for mean differences between the genders on a variable ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Discussion: Develop a test for mean differences between the genders on a variable Looking at the data, develop a test for mean differences between the genders on a variable – other than compa-ratio or salary – you feel might be important in answering our equal pay for equal work question. Interpret your results. Discussion: Develop a test for mean differences between the genders on a variable You’ll use the data set in the excel spreadsheet and answer on a word document _12_canvas_bus_308_dec_student_worksheet_copy.xlsx c_canvas_lecture_week Week 1: Descriptive Statistics, including Probability Gender1 Salary While the lectures will examine our equal pay question from the compa-ratio viewpoint, our weekly assignments will focus on F 35 examining the issue using the salary measure. F 41.4 F 21.8 The purpose of this assignmnent is two fold: F 23.9 1. Demonstrate mastery with Excel tools. F 23.3 2. Develop descriptive statistics to help examine the question. F 42.5 3. Interpret descriptive outcomes F 23.8 F 22.8 The first issue in examining salary data to determine if we – as a company – are paying males and females equally for doing equal work is to develop some F 65.9 descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not. F 34.6 F 34.2 1 Descriptive Statistics: Develop basic descriptive statistics for Salary F 56.1 The first step in analyzing data sets is to find some summary descriptive statistics for key variables. Discussion: Develop a test for mean differences between the genders on a variable F 22.9 Suggestion: Copy the gender1 and salary columns from the Data tab to columns T and U at the right. F 54.6 Then use Data Sort (by gender1) to get all the male and female salary values grouped together. F 22.8 F 76 a. Use the Descriptive Statistics function in the Data Analysis tab Place Excel outcome in Cell K19 F 24.3 to develop the descriptive statistics summary for the overall F 23.5 group’s overall salary. (Place K19 in output range.) F 23.6 Highlight the mean, sample standard deviation, and range. F 22.9 F 35.9 F 23.3 F 76.1 F 52.8 b. Using Fx (or formula) functions find the following (be sure to show the formula F 70.2 and not just the value in each cell) asked for salary statistics for each gender: M 55.6 Male Female M 27.2 Mean: M 59.5 Sample Standard Deviation: M 48.3 Range: M 76.7 M 75.8 M 61.2 M 42.6 M 25.6 2 Develop a 5-number summary for the overall, male, and female SALARY variable. M 73.1 For full credit, show the excel formulas in each cell rather than simply the numerical answer. M 24.8 Overall Males Females M 45.5 Max M 77.5 3rd Q M 45.5 Midpoint M 27.5 1st Q M 55.9 Min M 27.7 M 59.5 3 Location Measures: comparing Male and Female midpoints to the overall Salary data range. M 23.8 For full credit, show the excel formulas in each cell rather than simply the numerical answer. Discussion: Develop a test for mean differences between the genders on a variable M 40.1 Using the entire Salary range and the M and F midpoints found in Q2 Male Female M 69.7 a. What would each midpoint’s percentile rank be in the overall range? Use Excel’s =PERCENTRANK.EXC function M 61.5 b. What is the normal curve z value for each midpoint within overall range? Use Excel’s =STANDARDIZE function M 62.3 M 62 M 59.1 4 Probability Measures: comparing Male and Female midpoints to the overall Salary data range For full credit, show the excel formulas in each cell rather than simply the numerical answer. Using the entire Salary range and the M and F midpoints found in Q2, find Male Female a. The Empirical Probability of equaling or exceeding (=>) that value for Show the calculation formula = value/50 or =countif(range,”>=”&cell)/50 b. The Normal curve Prob of => that value for each group Use “=1-NORM.S.DIST” function 5 Conclusions: What do you make of these results? Be sure to include findings from this week’s lectures as well. In comparing the overall, male, and female outcomes, what relationship(s) see, to exist between the data sets? What does this suggest about our equal pay for equal work question? Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10

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Discussion: Develop a test for mean differences between the genders on a variable

Discussion: Develop a test for mean differences between the genders on a variable ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Discussion: Develop a test for mean differences between the genders on a variable Looking at the data, develop a test for mean differences between the genders on a variable – other than compa-ratio or salary – you feel might be important in answering our equal pay for equal work question. Interpret your results. Discussion: Develop a test for mean differences between the genders on a variable You’ll use the data set in the excel spreadsheet and answer on a word document _12_canvas_bus_308_dec_student_worksheet_copy.xlsx c_canvas_lecture_week Week 1: Descriptive Statistics, including Probability Gender1 Salary While the lectures will examine our equal pay question from the compa-ratio viewpoint, our weekly assignments will focus on F 35 examining the issue using the salary measure. F 41.4 F 21.8 The purpose of this assignmnent is two fold: F 23.9 1. Demonstrate mastery with Excel tools. F 23.3 2. Develop descriptive statistics to help examine the question. F 42.5 3. Interpret descriptive outcomes F 23.8 F 22.8 The first issue in examining salary data to determine if we – as a company – are paying males and females equally for doing equal work is to develop some F 65.9 descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not. F 34.6 F 34.2 1 Descriptive Statistics: Develop basic descriptive statistics for Salary F 56.1 The first step in analyzing data sets is to find some summary descriptive statistics for key variables. Discussion: Develop a test for mean differences between the genders on a variable F 22.9 Suggestion: Copy the gender1 and salary columns from the Data tab to columns T and U at the right. F 54.6 Then use Data Sort (by gender1) to get all the male and female salary values grouped together. F 22.8 F 76 a. Use the Descriptive Statistics function in the Data Analysis tab Place Excel outcome in Cell K19 F 24.3 to develop the descriptive statistics summary for the overall F 23.5 group’s overall salary. (Place K19 in output range.) F 23.6 Highlight the mean, sample standard deviation, and range. F 22.9 F 35.9 F 23.3 F 76.1 F 52.8 b. Using Fx (or formula) functions find the following (be sure to show the formula F 70.2 and not just the value in each cell) asked for salary statistics for each gender: M 55.6 Male Female M 27.2 Mean: M 59.5 Sample Standard Deviation: M 48.3 Range: M 76.7 M 75.8 M 61.2 M 42.6 M 25.6 2 Develop a 5-number summary for the overall, male, and female SALARY variable. M 73.1 For full credit, show the excel formulas in each cell rather than simply the numerical answer. M 24.8 Overall Males Females M 45.5 Max M 77.5 3rd Q M 45.5 Midpoint M 27.5 1st Q M 55.9 Min M 27.7 M 59.5 3 Location Measures: comparing Male and Female midpoints to the overall Salary data range. M 23.8 For full credit, show the excel formulas in each cell rather than simply the numerical answer. Discussion: Develop a test for mean differences between the genders on a variable M 40.1 Using the entire Salary range and the M and F midpoints found in Q2 Male Female M 69.7 a. What would each midpoint’s percentile rank be in the overall range? Use Excel’s =PERCENTRANK.EXC function M 61.5 b. What is the normal curve z value for each midpoint within overall range? Use Excel’s =STANDARDIZE function M 62.3 M 62 M 59.1 4 Probability Measures: comparing Male and Female midpoints to the overall Salary data range For full credit, show the excel formulas in each cell rather than simply the numerical answer. Using the entire Salary range and the M and F midpoints found in Q2, find Male Female a. The Empirical Probability of equaling or exceeding (=>) that value for Show the calculation formula = value/50 or =countif(range,”>=”&cell)/50 b. The Normal curve Prob of => that value for each group Use “=1-NORM.S.DIST” function 5 Conclusions: What do you make of these results? Be sure to include findings from this week’s lectures as well. In comparing the overall, male, and female outcomes, what relationship(s) see, to exist between the data sets? What does this suggest about our equal pay for equal work question? Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10

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