Question;Week 1Week 1.Describing the data. 1Using the Excel Analysis ToolPak function descriptive statistics, generate and show the descriptive statistics for each appropriate variable in the sample data set.a. For which variables in the data set does this function not work correctly for? Why?2Sort the data by Gen or Gen 1 (into males and females) and find the mean and standard deviation for each gender for the following variables:sal, compa, age, sr and raise.Use either the descriptive stats function or the Fx functions (average and stdev).3What is the probability for a:a. Randomly selected person being a male in grade E?b. Randomly selected male being in grade E?c. Why are the results different?4Find:a.The z score for each male salary, based on only the male salaries.b.The z score for each female salary, based on only the female salaries.c.The z score for each female compa, based on only the female compa values.d.The z score for each male compa, based on only the male compa values.e.What do the distributions and spread suggest about male and female salaries?Why might we want to use compa to measure salaries between males and females?5Based on this sample, what conclusions can you make about the issue of male and female pay equality?Are all of the results consistent with your conclusion? If not, why not?Week 2Week 2;Testing;means with the t-test;For;questions 2 and 3 below, be sure to list the null and alternate hypothesis;statements. Use.05 for your;significance level in making your decisions.;For;full credit, you need to also show the statistical outcomes - either the;Excel test result or the calculations you performed.;1;Below are 2 one-sample;t-tests comparing male and female average salaries to the overall sample;mean.;Based on our sample, how;do you interpret the results and what do these results suggest about the;population means for male and female salaries?;Males;Females;Ho: Mean salary = 45;Ho: Mean salary = 45;Ha: Mean salary =/= 45;Ha: Mean salary =/= 45;Note when performing a;one sample test with ANOVA, the second variable (Ho) is listed as the same;value for every corresponding value in the data set.;t-Test: Two-Sample;Assuming Unequal Variances;t-Test: Two-Sample;Assuming Unequal Variances;Since the Ho variable has;Var = 0, variances are unequal, this test defaults to 1 sample t in this;situation;Male;Ho;Female;Ho;Mean;52;45;Mean;38;45;Variance;316;0;Variance;334.667;0;Observations;25;25;Observations;25;25;Hypothesized Mean Difference;0;Hypothesized Mean Difference;0;df;24;df;24;t Stat;1.96890383;t Stat;-1.9132;P(T<=t) one-tail;0.03030785;P(T<=t) one-tail;0.03386;t Critical one-tail;1.71088208;t Critical one-tail;1.71088;P(T<=t) two-tail;0.0606157;P(T 0;Perform analysis;OBSERVED;A;B;C;D;E;F;Total;COUNT - M or 0;7;5;3;2;5;3;25;COUNT - F or 1;8;2;2;3;7;3;25;total;15;7;5;5;12;6;50;EXPECTED;7.5;3.5;2.5;2.5;6;3;25;By using either the;Excel Chi Square functions or calculating the results directly as the text;shows, do we;reject or not reject the;null hypothesis? What does your;conclusion mean?;Interpretation;2;Using our sample data;we can construct a 95% confidence interval for the population's mean salary;for each gender.;Interpret the;results. How do they compare with the;findings in the week 2 one sample t-test outcomes (Question 1)?;Males;Mean;St error;Low;to;High;52;3.65878;44.4483;59.5517;Results are mean;+/-2.064*standard error;Females;38;3.62275;30.5226;45.4774;2.064 is t value for 95%;interval;Interpretation;3;Based on our sample;data, can we conclude that males and females are distributed across grades in;a similar pattern within the population?;4;Using our sample data;construct a 95% confidence interval for the population's mean service;difference for each gender.;Do they intersect or;overlap? How do these results compare;to the findings in week 2, question 2?;5;How do you interpret;these results in light of our question about equal pay for equal work?
Paper#62075 | Written in 18-Jul-2015Price : $32