Please see attached. Week 1 only

Data
    ID    Salary    Compa-ratio    Midpoint     Age    Performance Rating    Service    Gender    Raise    Degree    Gender1    Grade        Do not manipuilate Data set on this page, copy to another page to make changes
    1    66.8    1.172    57    34    85    8    0    5.7    0    M    E        The ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)?
    2    27.4    0.884    31    52    80    7    0    3.9    0    M    B        Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
    3    34.7    1.118    31    30    75    5    1    3.6    1    F    B
    4    57.1    1.001    57    42    100    16    0    5.5    1    M    E        The column labels in the table mean:
    5    48.1    1.002    48    36    90    16    0    5.7    1    M    D        ID – Employee sample number             Salary – Salary in thousands
    6    74.4    1.110    67    36    70    12    0    4.5    1    M    F        Age – Age in years            Performance Rating - Appraisal rating (employee evaluation score)
    7    40.6    1.015    40    32    100    8    1    5.7    1    F    C        Service – Years of service (rounded)            Gender – 0 = male, 1 = female
    8    22.9    0.997    23    32    90    9    1    5.8    1    F    A        Midpoint – salary grade midpoint             Raise – percent of last raise
    9    78.1    1.166    67    49    100    10    0    4    1    M    F        Grade – job/pay grade            Degree (0= BS\BA 1 = MS)
    10    25    1.088    23    30    80    7    1    4.7    1    F    A        Gender1 (Male or Female)            Compa-ratio - salary divided by midpoint
    11    22.4    0.976    23    41    100    19    1    4.8    1    F    A
    12    58.3    1.022    57    52    95    22    0    4.5    0    M    E
    13    42.2    1.055    40    30    100    2    1    4.7    0    F    C
    14    23.9    1.041    23    32    90    12    1    6    1    F    A
    15    24.6    1.071    23    32    80    8    1    4.9    1    F    A
    16    42.6    1.064    40    44    90    4    0    5.7    0    M    C
    17    68.1    1.194    57    27    55    3    1    3    1    F    E
    18    35.9    1.157    31    31    80    11    1    5.6    0    F    B
    19    24.5    1.067    23    32    85    1    0    4.6    1    M    A
    20    35    1.128    31    44    70    16    1    4.8    0    F    B
    21    72    1.074    67    43    95    13    0    6.3    1    M    F
    22    54.8    1.142    48    48    65    6    1    3.8    1    F    D
    23    23.8    1.036    23    36    65    6    1    3.3    0    F    A
    24    52.2    1.087    48    30    75    9    1    3.8    0    F    D
    25    24.4    1.063    23    41    70    4    0    4    0    M    A
    26    23.9    1.037    23    22    95    2    1    6.2    0    F    A
    27    37.7    0.942    40    35    80    7    0    3.9    1    M    C
    28    77.1    1.150    67    44    95    9    1    4.4    0    F    F
    29    76.4    1.141    67    52    95    5    0    5.4    0    M    F
    30    48    1.001    48    45    90    18    0    4.3    0    M    D
    31    24    1.045    23    29    60    4    1    3.9    1    F    A
    32    27.3    0.881    31    25    95    4    0    5.6    0    M    B
    33    63.4    1.112    57    35    90    9    0    5.5    1    M    E
    34    27.9    0.899    31    26    80    2    0    4.9    1    M    B
    35    23.6    1.027    23    23    90    4    1    5.3    0    F    A
    36    23.4    1.016    23    27    75    3    1    4.3    0    F    A
    37    23    0.998    23    22    95    2    1    6.2    0    F    A
    38    60    1.052    57    45    95    11    0    4.5    0    M    E
    39    35    1.128    31    27    90    6    1    5.5    0    F    B
    40    24    1.045    23    24    90    2    0    6.3    0    M    A
    41    44.2    1.106    40    25    80    5    0    4.3    0    M    C
    42    22.6    0.981    23    32    100    8    1    5.7    1    F    A
    43    78.4    1.170    67    42    95    20    1    5.5    0    F    F
    44    62.9    1.103    57    45    90    16    0    5.2    1    M    E
    45    52.5    1.093    48    36    95    8    1    5.2    1    F    D
    46    57.2    1.004    57    39    75    20    0    3.9    1    M    E
    47    63    1.105    57    37    95    5    0    5.5    1    M    E
    48    63.4    1.113    57    34    90    11    1    5.3    1    F    E
    49    63.7    1.118    57    41    95    21    0    6.6    0    M    E
    50    58.1    1.019    57    38    80    12    0    4.6    0    M    E
Week 1
    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    36.2
    examining the issue using the salary measure.                                                                            F    42.1
                                                                                F    22.8
    The purpose of this assignmnent is two fold:                                                                            F    23
    1. Demonstrate mastery with Excel tools.                                                                            F    21.8
    2. Develop descriptive statistics to help examine the question.                                                                            F    40.5
    3. Interpret descriptive outcomes                                                                            F    23.6
                                                                                F    23.4
    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    67.5
    descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not.                                                                            F    34.1
                                                                                F    35.2
    1    Descriptive Statistics: Develop basic descriptive statistics for Salary                                                                        F    51.1
        The first step in analyzing data sets is to find some summary descriptive statistics for key variables.                                                                         F    25.3
        Suggestion: Copy the gender1 and salary columns from the Data tab to columns T and U at the right.                                                                        F    51
        Then use Data Sort (by gender1) to get all the male and female salary values grouped together.                                                                        F    24.4
                                                                                F    77.2
        a.     Use the Descriptive Statistics function in the Data Analysis tab                                                                     F    22.7
            to develop the descriptive statistics summary for the overall                                 Salary                                    F    23.9
            group's overall salary. (Place K19 in output range.)                                                                    F    22.8
            Highlight the mean, sample standard deviation, and range.                                Mean    44.454                                F    22.6
                                            Standard Error    2.7040728314                                F    33.5
                                            Median    42.2                                F    24.1
                                            Mode    23                                F    74.5
                                            Standard Deviation    19.1206823591                                F    48.9
        b.    Using Fx (or formula) functions find the following (be sure to show the formula                                 Sample Variance    365.6004938776                                F    65.6
            and not just the value in each cell) asked for salary statistics for each gender:                                Kurtosis    -1.2688729185                                M    57.7
                Male    Female                        Skewness    0.3392633171                                M    27.9
            Mean:    51.396    37.512                        Range    57.3                                M    63.7
            Sample Standard...