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BUS 308 Week 4 -Statistics excel assignment

Question # 00013010
Subject: Statistics
Due on: 04/21/2014
Posted On: 04/21/2014 06:05 AM

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Statistics excel assignment

This assignment is the week 4 tab section of the excel spreadsheet. The assignment must be completed in full showing all work and calculations labeled. The assignment is due at midnight on Saturday, April 19th at no later than 11:59pm EST. The text to the assignments is posted here with the file also uploaded.

Week 4 Confidence Intervals and Chi Square (Chs 11 - 12) Let's look at some other factors that might influence pay. <Note: use right click on row numbers to insert rows to perform analysis below any question>
For question 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 One question we might have is if the distribution of graduate and undergraduate degrees independent of the grade the employee?
(Note: this is the same as asking if the degrees are distributed the same way.)
Based on the analysis of our sample data (shown below), what is your answer?
Ho: The populaton correlation between grade and degree is 0.
Ha: The population correlation between grade and degree is > 0
Perform analysis:
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
7.5 3.5 2.5 2.5 6 3 25 <Highlighting each cell with show how the value
7.5 3.5 2.5 2.5 6 3 25 is found: row total times column total divided by
15 7 5 5 12 6 50 grand total.>

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?

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 3.658779396 44.44827933 59.55172067 Results are mean +/-2.064*standard error
Females 38 3.622754177 30.52263538 45.47736462 2.064 is t value for 95% interval
<Reminder: standard error is the sample standard deviation divided by the square root of the sample size.>

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?
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BUS 308 Week 4 -Statistics excel assignment Solution

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Posted On: 04/21/2014 06:07 AM
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Tutorial Preview …0 xxxxx 0 xxxxx 0 1 x 1 0 xxxxx 0 xxxxxxxxxx xxxxxxxxx 2 xxxxx 0 03333 x 64286 0 x 0 x x 16667 x p-value 0 xxxxx Critical Value xx 0705 xx xxxxx either xxx Excel Chi xxxxxx functions or xxxxxxxxxxx the xxxxxxx xxxxxxxx as xxx text shows, xx we reject xx not xxxxxx xxx null xxxxxxxxxxx What does xxxx conclusion mean? xxxxxxxxxxxxxxx Bitmap x xxxxx our xxxxxx data, we xxx construct a xxx confidence xxxxxxxx xxx the xxxxxxxxxxxx mean salary xxx each gender xxxxxxxxx the xxxxxxx xxx do xxxx compare with xxx findings in xxx week x xxx sample xxxxxx outcomes (Question xxx Mean St xxxxx Low xx xxxx Males xx 3 65878 xx 4483…
BUS_308_Week_4_-Statistics_excel_assignment_Solution.xlsx (56.92 KB)
Preview: overall xxxxxx mean xxxxx on our xxxxxxx how do xxx interpret xxx xxxxxxx and xxxx do these xxxxxxx suggest about xxx population xxxxx xxx male xxx female salaries?MalesFemalesHo: xxxx salary = xxxxx Mean xxxxxx xxx 45Note xxxx performing a xxx sample test xxxx ANOVA, xxx xxxxxx variable xxxx is listed xx the same xxxxx for xxxxx xxxxxxxxxxxxx value xx the data xxx t-Test: Two-Sample xxxxxxxx Unequal xxxxxxxxxxxxxx xxx Ho xxxxxxxx has Var x 0, variances xxx unequal; xxxx xxxx defaults xx 1 sample x in this xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Mean xxxxxxxxxxxxx xxxxxxxxxxxxxx one-tailt xxxxxxxx one-tailP(T<=t) two-tailt xxxxxxxx two-tailConclusion: Do xxx reject xxx xxxx equals xxxxxxxxxxxxxxxxxxxxxx on our xxxxxx results, perform x 2-sample xxxxxx xx see xx the population xxxx and female xxxxxxxx could xx xxxxx to xxxx other Based xx our sample xxxxxxxx can xxx xxxx and xxxxxx compas in xxx population be xxxxx to xxxx xxxxxx (Another xxxxxxxx t-test )What xxxxx information would xxx like xx xxxx to xxxxxx the question xxxxx salary equity xxxxxxx the xxxxxxxx xxxxxx the xxxxxx and compa xxxx tests in xxxxxxxxx 3 xxx x provide xxxxxxxxx results about xxxx and female xxxxxx equality, xxxxx xxxxx be xxxx appropriate to xxx in answering xxx question xxxxx xxxxxx equity? xxxxxxxx are your xxxxxxxxxxx about equal xxx at xxxx xxxxxxxxxx 3Testing xxxxxxxx means with xxxxxxxx questions 3 xxx 4 xxxxxx xx sure xx list the xxxx and alternate xxxxxxxxxx statements xxx xx for xxxx significance level xx making your xxxxxxxxx 1 xxxxxxxxxx xxxxx on xxx sample data, xxx the average(mean) xxxxxx in xxx xxxxxxxxxx be xxx same for xxxx of the xxxxx levels? xxxxxxx xxxxx variance, xxx use the xxxxxxxx toolpak function xxxxx ) xxx xx the xxxxx table/range to xxx as follows: xxx all xx xxx salary xxxxxx for each xxxxx under the xxxxxxxxxxx grade xxxxx xx sure xx incllude the xxxx and alternate xxxxxxxxxx along xxxx xxx statistical xxxx and result xxxxx Assume equal xxxxxxxxx for xxx xxxxxx 2 xxxxxxxxxx The table xxx analysis below xxxxxxxxxxx a xxxxx xxxxx with xxxxxxxxxxx Please interpret xxx results GradeGenderThe xxxxxx values xxxx xxxxxxxx picked xxx each cell xxx Average salaries xxx equal xxx xxx gradesHa: xxxxxxx salaries are xxx equal for xxx gradesHo: xxxxxxx xxxxxxxx by xxxxxx are equalHa: xxxxxxx salaries by xxxxxx are xxx.....
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