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Assignment 2: T-Test

 

By Wednesday, February 27, 2013, post your assignment to the M2: Assignment 2 Dropbox.

 

 Any conclusion drawn for the t-test statistical process is only as good as the research question asked and the null hypothesis formulated. T-tests are only used for two sample groups, either on a pre post-test basis or between two samples (independent or dependent). The t-test is optimized to deal with small sample numbers which is often the case with managers in any business. When samples are excessively large the t test becomes difficult to manage due to the mathematical calculations involved.

 

Calculate the “t” value for independent groups for the following data using the formula presented in the module. Check the accuracy of your calculations. Using the raw measurement data presented above, determine whether or not there exists a statistically significant difference between the salaries of female and male human resource managers using the appropriate t-test. Develop a research question, testable hypothesis, confidence level, and degrees of freedom. Draw the appropriate conclusions with respect to female and male HR salary levels. Report the required “t” critical values based on the degrees of freedom. Your response should be 2-3 pages.

 

Salary Level

Female HR Directors

Male HR Directors

$50,000

$58,000

$75,000

$69,000

$72,000

$73,000

$67,000

$67,000

$54,000

$55,000

$58,000

$63,000

$52,000

$53,000

$68,000

$70,000

$71,000

$69,000

$55,000

$60,000

*Do not forget what we all learned in high school about “0”s

 

 

 

 

Assignment 2 Grading Criteria

Maximum Points

Calculate the “t” value and set up the posting as required.

15

Developed an appropriate research question.

15

Developed an appropriate testable hypothesis based on the research question.

15

Selected an appropriate confidence level and accurately stated the degrees of freedom along with the required critical value for “t.”

25

Drew the appropriate conclusion.

15

The posting was free of all grammatical and spelling errors.

15

Total:

100

 

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The data xxxxxxx the given xxxxxxx is :
Salary Level xxxxxxx style="width:246px;height:34px;">

$50,000

$75,000

$69,000

$73,000

$54,000

$55,000

$52,000

$68,000

$70,000

$69,000

$55,000

Step 1 xxxxxxx Research hypothesis

 

Step xxxxxxx Null hypothesis

As xxxxxxx know xxxxxxx xxxxxxx states that xxxxxxx relationship exists xxxxxxx two entities. xxxxxxx null hypothesis xxxxxxx that the xxxxxxx payable is xxxxxxx xxxxxxx on xxxxxxx i.e there xxxxxxx no significant xxxxxxx between xxxxxxx xxxxxxx of a xxxxxxx HR and xxxxxxx Male HR.

 

Step xxxxxxx Determining the xxxxxxx data required xxxxxxx shown above. xxxxxxx xxxxxxx number xxxxxxx samples of xxxxxxx of Female xxxxxxx is xxxxxxx xxxxxxx the number xxxxxxx samples of xxxxxxx of Male xxxxxxx be n2.

Here xxxxxxx and n2= xxxxxxx the Salaries xxxxxxx xxxxxxx HR xxxxxxx $ 62200

Sum xxxxxxx squares of xxxxxxx value xxxxxxx xxxxxxx $39472000000

Square of xxxxxxx $3868840000

For the xxxxxxx of Male xxxxxxx = $63700

Sum xxxxxxx squares of xxxxxxx values say xxxxxxx xxxxxxx $41007000000

Applying xxxxxxx the formula, xxxxxxx t-value is xxxxxxx t-value xxxxxxx xxxxxxx we take xxxxxxx absolute value xxxxxxx the value xxxxxxx t is xxxxxxx 4: Determining xxxxxxx tabulated value

As xxxxxxx xxxxxxx Degree xxxxxxx freedom is xxxxxxx as n1+n2-2

Here, xxxxxxx of xxxxxxx xxxxxxx 18

For degree xxxxxxx freedom i.edf=18

P(0.1)=1.73 xxxxxxx P(0.05)=2.10,P(0.01)= 2.88 xxxxxxx P(0.001)=3.92

Since the xxxxxxx t-value is xxxxxxx than the xxxxxxx xxxxxxx so xxxxxxx null hypothesis xxxxxxx correct.

 

 

 

CONCLUSION:

Since our xxxxxxx value xxxxxxx xxxxxxx than the xxxxxxx value at xxxxxxx so, the xxxxxxx of female xxxxxxx is 90% xxxxxxx same to xxxxxxx xxxxxxx of xxxxxxx HR. The xxxxxxx is less xxxxxxx the xxxxxxx xxxxxxx at all xxxxxxx probabilities taken.  xxxxxxx at p=0.001 xxxxxxx can say xxxxxxx The salaries xxxxxxx Female HR xxxxxxx xxxxxxx highly xxxxxxx to the xxxxxxx of Male xxxxxxx but xxxxxxx xxxxxxx we take xxxxxxx value at xxxxxxx so we xxxxxxx say that xxxxxxx Salaries of xxxxxxx HR is xxxxxxx xxxxxxx similar xxxxxxx the Salaries xxxxxxx Male HR.