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Owner: terrycrews
Created: Jun 3, 2016
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!Marc Gestopa Difference in Salary of Education and Engineer Majors by Gender

State: μF -μ= the true difference in mean salary of male and female education and engineer majors like those in the sample.

HoμF -μ= 0

HA : μF -μM≠ 0

Plan: 2-sample t-test for difference in means

α = 0.05

Random: 2 independent random samples

10 % Rule: Females= 10(1088) = 10880 is less than the total population of females

Males= 10(1144) = 11440 is less than the total population of males

LCC: Females: 1088 is more than 30 so is a large sample size and therefore the sampling distribution is normally distributed.

Males: 1144 is more than 30 so it is a large sample size and therefore the sampling distribution is normally distributed.

Do: t = -23.335772 P-value= <0.0001 df = 2202.1975

Conclude: Since the p- value is less than the alpha (<0.0001 < .05) we reject the null and have convincing evidence that there is a difference in the the mean salary of male and female education and engineering majors like those in the sample.

Result 1: Two Sample T   [Info]
Hypothesis test results:
μ1 : Mean of Salary where Gender="Female"
μ2 : Mean of Salary where Gender="Male"
μ1 - μ2 : Difference between two means
H0 : μ1 - μ2 = 0
HA : μ1 - μ2 ≠ 0
(without pooled variances)
DifferenceSample Diff.Std. Err.DFT-StatP-value
μ1 - μ2-9481.2569406.297122202.1975-23.335772<0.0001

Result 2: Summary Stats fem   [Info]
Summary statistics for Salary:
Where: Gender="Female"
Group by: Gender
GendernMeanVarianceStd. dev.Std. err.MedianRangeMinMaxQ1Q3
Female108841107.556976339829880.9909299.56154363693120933070642793551437634.5

Result 3: Summary Stats Male   [Info]
Summary statistics for Salary:
Where: Gender="Male"
Group by: Gender
GendernMeanVarianceStd. dev.Std. err.MedianRangeMinMaxQ1Q3
Male114450588.813861892259283.8152274.481755447132506290276153352079.556060

Data set 1. Fictitious Salary Data for Recent Graduates   [Info]